Monitoring in Neurocritical Care [1st ed.] 1437701671, 9781455727537, 9781437701678

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Monitoring in Neurocritical Care

Monitoring in Neurocritical Care Peter D. le Roux,

MD, FACS

Associate Professor of Neurosurgery Perelman School of Medicine at the University of Pennsylvania; Department of Neurosurgery Pennsylvania Hospital Philadelphia, Pennsylvania

Joshua M. Levine,

MD

Assistant Professor Departments of Neurology, Neurosurgery, and Anesthesiology and Critical Care Perelman School of Medicine at the University of Pennsylvania; Co-Director, Neurointensive Care Unit Hospital of the University of Pennsylvania Philadelphia, Pennsylvania

W. Andrew Kofke,

MD, MBA, FCCM

Professor Departments of Anesthesiology and Critical Care and Neurosurgery Perelman School of Medicine at the University of Pennsylvania; Director, Neuroanesthesia Department of Anesthesiology and Critical Care University of Pennsylvania Health System; Co-Director, Neurointensive Care Unit Hospital of the University of Pennsylvania Philadelphia, Pennsylvania

1600 John F. Kennedy Blvd. Ste 1800 Philadelphia, PA 19103-2899

MONITORING IN NEUROCRITICAL CARE ISBN: 978-1-4377-0167-8 Copyright © 2013 by Saunders, an imprint of Elsevier Inc. Chapter 22: “Renal, Electrolyte, and Acid Base Assessment”: Guy M. Dugan retains copyright to his original contribution. Chapter 23: “Gastrointestinal and Hepatic Disorders” by Christiana E. Hall and Aashish R. Patel: Christiana E. Hall retains copyright to her original portion of the contribution only. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the Publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).

Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods, they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. With respect to any drug or pharmaceutical products identified, readers are advised to check the most current information provided (i) on procedures featured or (ii) by the manufacturer of each product to be administered, to verify the recommended dose or formula, the method and duration of administration, and contraindications. It is the responsibility of practitioners, relying on their own experience and knowledge of their patients, to make diagnoses, to determine dosages and the best treatment for each individual patient, and to take all appropriate safety precautions. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. Library of Congress Cataloging-in-Publication Data   Monitoring in neurocritical care / [edited by] Peter D. Le Roux, Joshua M. Levine, W. Andrew Kofke.     p. ; cm.    Includes bibliographical references and index.    ISBN 978-1-4377-0167-8 (hardcover : alk. paper)    I. Le Roux, Peter D.  II. Levine, Joshua M.  III. Kofke, W. Andrew.    [DNLM:1.  Monitoring, Intraoperative–methods.  2.  Neurosurgical Procedures.  3.  Central Nervous System Diseases–surgery.  4.  Intensive Care–methods.  5.  Intensive Care Units–organization & administration. WL 368]    616.02’8–dc23 2012036807 Content Strategist: Charlotta Kryhl Senior Content Development Specialist: Janice Gaillard Content Development Specialist: Angela Rufino Publishing Services Manager: Anne Altepeter Senior Project Manager: Cheryl A. Abbott Project Manager: Louise King Design Direction: Louis Forgione Printed in China Last digit is the print number:  9  8  7  6  5  4  3  2  1 

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To the ICU nurses who take care of all our patients

Preface Neurocritical care has evolved rapidly in the past 10 years. It is a specialty that focuses on the critical care management of patients with catastrophic neurologic diseases, including primary neurologic pathologies such as traumatic brain injury (TBI), ischemic stroke, intracerebral hemorrhage (ICH), subarachnoid hemorrhage (SAH), brain tumors, infection (e.g., HIV, TB, meningitis), spinal cord injury, and acute ascending neuropathies. In addition, neurologic dysfunction occurs in many diverse systemic disorders, including hypoxia (e.g., post cardiac arrest, near drowning), liver dysfunction, electrolyte abnormalities, high altitude sickness, eclampsia, lead intoxication, and malignant hypertension. There are many reasons why brain injury or damage occurs in patients with neurologic disorders. In particular, multiple experimental and clinical studies have demonstrated a close relationship between variables such as hypoxia, increased intracranial pressure, arterial hypotension, hyperglycemia, fever, and seizures with neurologic outcome, and accumulating evidence suggests that brain damage evolves over time. Minimizing the burden of this delayed, or “secondary,” brain injury, has become the focus of modern neurocritical care. However, despite much research, trials in neuroprotection have largely failed, in part because of their association with prognostic heterogeneity, multiple mechanisms of cellular damage, and a paucity of early mechanistic endpoints. This has led to a realization that strategies of care, or “bundles,” rather than single agents, and approaches that are tailored to individual patient physiology and pathophysiology are necessary to improve outcome. In daily practice neurointensivists focus on the recognition of subtle changes in the neurologic condition, interactions between the brain and systemic derangements, and brain physiology. The challenge for intensivists today is to identify individuals who are at risk of developing disease or secondary injury, determine disease severity, and distinguish responders from nonresponders to therapy (i.e., individualized and targeted medicine). Monitoring is one tool that may answer these challenges, and it has become central to the management of secondary brain injury and to individualized care. In recent years (interestingly in concert with the evolution of neurocritical care as a distinct specialty), technology developments have resulted in several new monitoring techniques that provide the neurointensivist with information about brain and cellular function. Techniques to better monitor function of the heart, lung, liver, kidney, and blood also have evolved. In addition, when the various techniques are combined (“multimodal monitoring”), a more accurate overall picture of brain function is produced. This approach, along with new computer systems that integrate data at the bedside, and the emerging field of bioinformatics may change the way patients with brain injury are managed in the future. In the last decade, there have been many advances in neurocritical care monitoring technology and a better

understanding of what information the technology provides. These advances have been chronicled in numerous contributions to the scientific literature, the sheer volume of which makes it difficult for healthcare providers and device engineers to keep up to date with the knowledge necessary to provide the best patient care. In addition, although several textbooks on critical care or head injury briefly discuss monitoring in a chapter or two, there is a paucity of information that summarizes all aspects of neuromonitoring and no textbook that is dedicated to monitoring in neurocritical care. This book, Monitoring in Neurocritical Care, represents a comprehensive review of neuromonitoring. We have designed this textbook to provide the reader with a practical but indepth reference that describes the scientific basis and rationale for use of a particular monitor, the information it provides, and how this information can be used to manage the neurocritical care patient in an integrated fashion. We have been fortunate to have chapters written by authors from around the world. The contributors are clinicians, engineers, information technology experts, and researchers who have extensive experience in the field, and each has provided an excellent and timely review. We hope that the reader will gain a comprehensive understanding about neuromonitoring and neurocritical care and an insight into existent controversies and potential future management. Its contents will be relevant to neurologists, neurosurgeons, neuroanesthesiologists, neurointensivists, and neuroscience nurses, and will serve as a useful resource to intensivists working in medical and surgical ICUs. For those who are interested in clinical or laboratory research on brain injury in its broad sense, this book will provide many ideas and references and will be a stepping-stone to further progress in understanding a complex problem. The text also will serve as a reference and guide for many engineers, bioengineers, and computer experts who work on medical device and bioinformatics development. We have divided the book into seven sections. Section I, Background, provides information about cerebral metabolism, the principles of neurocritical care, informatics, quality assessment, the role of ICU design and nursing, specific considerations in children, the effects of anesthetic agents on monitors, and a discussion on the relationship between bioethics and monitoring. Section II, Clinical and Laboratory Assessment, reviews clinical evaluation, sedation, pain, delirium, outcomes such as neuropsychological and brain death, extracerebral organ systems, laboratory analysis, and the role of biomarkers. Section III, Electrophysiology, is devoted to evoked potentials and electroencephalography. Section IV, Radiology, discusses the use and integration of various techniques, including computed tomography, xenon-CT, MRI, PET, and SPECT in neurocritical care. Section V, Cerebral Blood Flow, is a review of techniques such as neurosonology, laser Doppler flowmetry, thermal diffusion flowmetry, jugular bulb oximetry, and near infrared spectroscopy. Section VI, vii

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Preface

Intracranial Monitoring, provides an in-depth review of invasive techniques, including intracranial pressure, brain oxygen, cerebral microdialysis, and brain temperature. The final section, Computers, Engineering, and the Future, provides a description of device development, engineering, simulation, telemedicine, robotics, information processing, data acquisition and storage, medical informatics and multimodality monitoring, noninvasive brain monitoring, and a discussion of potential future developments. It is important for the reader to realize that the “ideal brain monitor” does not yet exist and no single monitor will by itself affect outcome. Instead, it is the information provided by a monitor and how we as healthcare providers interpret and apply the information that has the potential to improve outcome and lead to new insights into disease processes.

We would like to express our appreciation and acknowledge the efforts of all contributors to this volume. We also thank the editorial, design, and production staff at Elsevier Science, in particular Janice Gaillard, Charlotta Kryhl, Julie Goolsby, Kate Crowley, Angela Rufino, Louis Forgione, Cheryl Abbott, Louise King, and Anne Altepeter, who have been very helpful in producing this volume, and Yolanda Caban who provided excellent administrative assistance. Finally, we thank Barbara Williams who provided outstanding editorial assistance and made this book possible. Peter D. le Roux, MD, FACS Joshua M. Levine, MD W. Andrew Kofke, MD, MBA, FCCM

Contributors Pippa G. Al-Rawi, BSc

Rosette C. Biester, PhD

Maurizio Cereda, MD

Research Associate Neurosurgery Unit Department of Clinical Neurosciences University of Cambridge/Addenbrooke’s Hospital Cambridge, United Kingdom

Polytrauma Neuropsychologist Department of Behavioral Health Philadelphia Veterans Affairs Medical Center; Auxiliary Health Care Provider Department of Physical Medicine and Rehabilitation University of Pennsylvania Health System Philadelphia, Pennsylvania

Assistant Professor Department of Anesthesiology and Critical Care Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

Pamela J. Amelung, MD Clinical Associate Professor Department of Medicine University of Maryland School of Medicine; Physician Liaison Philips VISICU Baltimore, Maryland

Michal Arkuszewski, MD, PhD Department of Neurology, Central University Hospital Medical University of Silesia Katowice, Poland; Department of Radiology, Neuroradiology Division Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

Peter M. Black, MD, PhD Center for Advanced Brain and Spine Surgery Natick, Massachusetts; Professor of Neurosurgery Department of Surgery Harvard Medical School Boston, Massachusetts

Thomas P. Bleck, MD, FCCM Professor Departments of Neurological Sciences, Neurosurgery, Anesthesiology, and Medicine Rush Medical College; Associate Chief Medical Officer for Critical Care Rush University Medical Center Chicago, Illinois

Syed T. Arshad, MD

Jens Bracht, Dipl.-Phys.

Neuro-Intensivist Department of Neurosurgery Sacramento Medical Center/Kaiser Permanente North Valley Sacramento, California

Technical Director R&D, PD GMS mbH Kiel, Germany

Ramani Balu, MD, PhD Fellow Department of Neurology Division of Neurocritical Care Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

Sarice L. Bassin, MD Assistant Professor Department of Neurology Northwestern University Feinberg School of Medicine; Program Director, Neurocritical Care Fellowship Division of Neurocritical Care Northwestern Memorial Hospital Chicago, Illinois

David M. Benglis, Jr., MD Atlanta Brain and Spine Care Atlanta, Georgia

M. Ross Bullock, MD, PhD Professor Department of Neurological Surgery Director, Clinical Neurotrauma Department of Neurological Surgery University of Miami Miller School of Medicine Miami, Florida

Andrew P. Carlson, MD Department of Neurological Surgery University of New Mexico School of Medicine Albuquerque, New Mexico

Emmanuel Carrera, MD Department of Neurology Centre Hospitalier Universitaire Vaudois (CHUV) Lausanne University Hospital Lausanne, Switzerland

Randall M. Chesnut, MD, FCCM, FACS Integra Endowed Professor of Neurotrauma Department of Neurological Surgery Department of Orthopaedic Surgery Adjunct Professor, School of Global Health Harborview Medical Center, University of Washington Seattle, Washington

Jan Claassen, MD Attending Neurointensivist Department of Neurology Division of Neurocritical Care Columbia University College of Physicians and Surgeons New York, New York

Wendy A. Cohen, MD Professor Departments of Radiology and Neurological Surgery University of Washington School of Medicine Seattle, Washington

E. Sander Connolly, Jr., MD Bennett M. Stein Professor and Vice Chairman Department of Neurological Surgery Columbia University College of Physicians and Surgeons; Director, Cerebrovascular Research Laboratory Surgical Director, Neuro-Intensive Care Unit Department of Neurological Surgery Columbia University Medical Center/New York-Presbyterian New York, New York

Marek Czosnyka, PhD Reader in Brain Physics Department of Clinical Neurosciences, Neurosurgery Unit University of Cambridge/Addenbrooke’s Hospital Cambridge, United Kingdom

John A. Detre, MD Professor Departments of Neurology and Radiology Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

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Contributors

Martin E. Doerfler, MD

Thomas Geeraerts, MD, PhD

K.T. Henrik Huttunen, MD

Associate Professor Departments of Medicine and Science Education Hofstra North Shore-LIJ School of Medicine at Hofstra University Hempstead, New York; Vice President, Evidence Based Clinical Practice and Clinical Integration North Shore-LIJ Health System Lake Success, New York

Anesthesiology and Critical Care Department University Hospital of Toulouse University Paul Sabatier Toulouse, France

Clinical Assistant Professor of Anesthesiology Department of Anesthesiology, Pharmacology, and Therapeutics University of British Columbia Faculty of Medicine; Attending Anesthesiologist, Vancouver Acute Department of Anesthesia Division of Neuroanesthesia Vancouver General Hospital Vancouver, British Columbia, Canada

Guy M. Dugan, MD, FCCP Director Department of Critical Care and Neurocritical Care Alexian Brothers Medical Center Elk Grove Village, Illinois

Richard P. Dutton, MD, MBA Clinical Associate Department of Anesthesia and Critical Care University of Chicago; Executive Director American Quality Institute (AQI) American Society of Anesthesiologists Park Ridge, Illinois

E. Wesley Ely, MD, MPH, FACP, FCCM Professor of Medicine and Critical Care Department of Medicine Center for Health Services Research Vanderbilt University School of Medicine; Associate Director of Aging Research, VA GRECC Veterans Affairs Tennessee Valley Healthcare System Nashville, Tennessee

Ronald G. Emerson, MD Adjunct Professor of Clinical Neurology Department of Neurology Columbia University Medical Center; Attending Neurologist Department of Neurology Hospital for Special Surgery New York, New York

Per Enblad, MD, PhD Professor of Neurosurgery Department of Neuroscience Section of Neurosurgery Uppsala University Uppsala University Hospital Uppsala, Sweden

Anthony A. Figaji, MD, FCS, PhD Professor Division of Neurosurgery University of Cape Town; Head of Pediatric Neurosurgery Red Cross Children’s Hospital Cape Town, Western Cape, South Africa

Damien Galanaud, MD, PhD CNRS UPR 640 LENA Université Pierre et Marie Curie (Paris VI); Neuroradiology Pitié Salêtrière Hospital Paris, France

Vicente H. Gracias, MD Professor Department of Surgery Chief, Trauma/Surgical Critical Care UMDNJ-Robert Wood Johnson Medical School; Director, Level I Trauma Center Robert Wood Johnson University Hospital New Brunswick, New Jersey

David M. Greer, MD, MA, FCCM, FAHA Dr. Harry M. Zimmerman and Dr. Nicholas and Viola Spinelli Professor and Vice Chairman Director, Neurosciences Intensive Care Unit Neurology Residency Program Director Director of Medical Studies Department of Neurology Yale School of Medicine New Haven, Connecticut

Peter J. Kirkpatrick, MSc, FRCS(SN), FMedSci

Fellow of Medical Academy of Sciences Society of British Neurosurgeons (SBNS) Consultant Neurosurgeon Honorary University Lecturer Department of Neurosurgery Addenbrooke’s Hospital Cambridge University Hospitals Cambridge, United Kingdom

Michel Kliot, MD

Associate Professor of Neurology and Neurotherapeutics and Neurological Surgery Division of Neurocritical Care University of Texas Southwestern Dallas, Texas

Professor of Clinical Neurosurgery Department of Neurological Surgery University of California, San Francisco School of Medicine; Director, Center for Management and Surgery of Peripheral Nerve Disorders San Francisco, California

J. Claude Hemphill III, MD, MAS

W. Andrew Kofke, MD, MBA, FCCM

Professor of Clinical Neurology Department of Neurology University of California, San Francisco School of Medicine; Director, Neurocritical Care Department of Neurology San Francisco General Hospital San Francisco, California

Professor Departments of Anesthesiology and Critical Care and Neurosurgery Perelman School of Medicine at the University of Pennsylvania; Director, Neuroanesthesia Department of Anesthesiology and Critical Care University of Pennsylvania Health System; Co-Director, Neurointensive Care Unit Hospital of the University of Pennsylvania Philadelphia, Pennsylvania

Christiana E. Hall, MD, MS

Jiri Horak, MD Assistant Professor of Clinical Anesthesiology and Critical Care Department of Anesthesiology and Critical Care Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

Peter Horn, MD Associate Professor of Neurosurgery Department of Neurosurgery Charité Universitätsmedizin Berlin Berlin, Germany

David A. Horowitz, MD Assistant Professor of Clinical Medicine Perelman School of Medicine at the University of Pennsylvania; Associate Chief Medical Officer University of Pennsylvania Health System Philadelphia, Pennsylvania

Jaroslaw Krejza, MD, PhD Research Associate Professor Department of Radiology Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania; Al-Imam Muhammad Ibn Saud Islamic University Riyadh, Saudi Arabia

Monisha A. Kumar, MD Assistant Professor Departments of Neurology, Neurosurgery, and Anesthesiology and Critical Care Perelman School of Medicine at the University of Pennsylvania; Director, Neurocritical Care Fellowship Program Hospital of the University of Pennsylvania Philadelphia, Pennsylvania

Contributors

Arthur M. Lam, MD, FRCPC

David K. Menon, MD, PhD, FRCP, FRCA,

DaiWai M. Olson, PhD, RN

Medical Director of Neuroanesthesia and Neurocritical Care Swedish Neuroscience Institute Swedish Medical Center; Clinical Professor of Anesthesiology and Pain Medicine University of Washington Member, Physician Anesthesia Services Seattle, Washington

FFICM, FMedSci

Assistant Professor Department of Medicine Division of Neurology Duke University School of Medicine Durham, North Carolina

Peter D. le Roux, MD, FACS Associate Professor of Neurosurgery Perelman School of Medicine at the University of Pennsylvania; Department of Neurosurgery Pennsylvania Hospital Philadelphia, Pennsylvania

Joshua M. Levine, MD Assistant Professor Departments of Neurology, Neurosurgery, and Anesthesiology and Critical Care Perelman School of Medicine at the University of Pennsylvania; Co-Director, Neurointensive Care Unit Hospital of the University of Pennsylvania Philadelphia, Pennsylvania

Geoffrey T. Manley, MD, PhD Professor and Vice Chairman Co-Director, Brain and Spinal Injury Center Department of Neurological Surgery University of California, San Francisco School of Medicine; Chief of Neurosurgery San Francisco General Hospital San Francisco, California

Basil F. Matta, MB, MA, BCh, FRCA Associate Lecturer Department of Medicine Division of Anaesthesia University of Cambridge/Addenbrooke’s Hospital; Divisional Director and Associate Medical Director Emergency and Perioperative Care Cambridge University Foundation Trust Hospitals Cambridge, United Kingdom

Jonathan McEwen, MD Clinical Assistant Professor of Anesthesiology Department of Anesthesiology, Pharmacology, and Therapeutics University of British Columbia Faculty of Medicine; Attending Anesthesiologist, Vancouver Acute Department of Anesthesia, Division of Neuroanesthesia Vancouver General Hospital Vancouver, British Columbia, Canada

Professor and Head Division of Anaesthesia University of Cambridge/Addenbrooke’s Hospital; Honorary Consultant Perioperative Care Addenbrooke’s Hospital; Co-Chair, Acute Brain Injury Program Wolfson Brain Imaging Centre University of Cambridge Cambridge, United Kingdom

Asako Miyakoshi, MD Assistant Professor Department of Radiology Division of Neuroradiology University of Washington School of Medicine Seattle, Washington

Richard S. Moberg, MSE President Moberg Research, Inc. Ambler, Pennsylvania

Pierre D. Mourad, PhD Associate Professor Department of Neurological Surgery Principal Physicist Applied Physics Laboratory University of Washington Seattle, Washington

Barnett R. Nathan, MD Associate Professor Departments of Neurology and Internal Medicine University of Virginia Charlottesville, Virginia

Patrick J. Neligan, MD Senior Clinical Lecturer of Anaesthesia and Intensive Care Galway University Hospitals National University of Ireland, Galway Galway, Ireland

Anoma Nellore, MD Fellow Department of Medicine Division of Infectious Disease Massachusetts General Hospital Harvard Medical School Boston, Massachusetts

Mauro Oddo, MD Staff Physician Department of Intensive Care Medicine CHUV-University Hospital Faculty of Biology and Medicine University of Lausanne Lausanne University Hospital Lausanne, Switzerland

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Pratik P. Pandharipande, MD, MSCI Associate Professor Department of Anesthesiology Division of Critical Care and Perioperative Medicine Vanderbilt University School of Medicine Nashville, Tennessee

Jose L. Pascual, MD, PhD, FRCS(C), FACS Assistant Professor Department of Surgery Division of Traumatology, Surgical Critical Care, and Emergency Surgery Perelman School of Medicine at the University of Pennsylvania; Attending Surgeon Department of Surgery Hospital of the University of Pennsylvania Philadelphia, Philadelphia

Aashish R. Patel, DO Fellow in Neurocritical Care Department of Neurological Surgery University of Texas Southwestern Dallas, Texas

Frederik A. Pennings, MD, PhD Assistant Professor Department of Neurosurgery University of Massachusetts Medical School Worcester, Massachusetts

Ian Piper, PhD Clinical Scientist Clinical Physics University of Glasgow; Brain-IT Group Coordinator, Intensive Care Monitoring Department of Clinical Physics Southern General Hospital Trust Glasgow, United Kingdom

Amit Prakash, MBBS, MD, FRCA, EDIC Consultant, Department of Anaesthesia and Intensive Care Addenbrooke’s Hospital Cambridge University Hospital Foundation Trust Cambridge, United Kingdom

J. Javier Provencio, MD, FCCM Associate Professor Departments of Neurology, Neurological Surgery, and Neurosciences Cleveland Clinic Lerner College of Medicine of Case Western Reserve University; Director, Neurocritical Care Fellowship Program Cleveland Clinic Cleveland, Ohio

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Contributors

Louis Puybasset, MD, PhD

J. Michael Schmidt, PhD, MSc

Martin Smith, MBBS, FRCA, FFICM

Département d’Anesthésie-Réanimation Université Pierre et Marie Curie (Paris VI); Neurosurgical Intensive Care Unit Pitié Salêtrière Hospital Paris, France

Assistant Professor of Clinical Neurophysiology in Neurology Department of Neurology Columbia University College of Physicians and Surgeons; Director Neuro-ICU Neuromonitoring and Informatics Columbia University Medical Center New York, New York

Consultant and Honorary Professor in Neurocritical Care The National Hospital for Neurology and Neurosurgery University College London Hospitals London, United Kingdom

Rohan Ramakrishna, MD Resident Department of Neurological Surgery University of Washington Medical Center Seattle, Washington

Mahbub Rashid, PhD Professor University of Kansas School of Architecture, Design and Planning Lawrence, Kansas

Gerald P. Roston, PhD, PE Technology Consultant and Managing Partner Pair of Docs Consulting, LLC Saline, Michigan

Stuart Russell, PhD Professor of Computer Science Michael H. Smith and Lotfi A. Zadeh Chair in Engineering Computer Science Division University of California, Berkeley Berkeley, California; Adjunct Professor Department of Neurological Surgery University of California, San Francisco San Francisco, California

Owen B. Samuels, MD Associate Professor of Neurosurgery and Neurology Emory University School of Medicine; Director, Division of Neuroscience Critical Care Emory Healthcare Atlanta, Georgia

Matthew R. Sanborn, MD Resident Department of Neurosurgery Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

Bernhard Schmidt, PhD Department of Neurology Chemnitz Medical Centre Chemnitz, Germany

Eric Albert Schmidt, MD, PhD Department of Neurosurgery Hôpital Purpan Toulouse, France

Sarah E. Schmitt, MD Assistant Professor of Clinical Neurology Department of Neurology Perelman School of Medicine at the University of Pennsylvania; Director, Electroencephalography Laboratory Department of Neurology Hospital of the University of Pennsylvania Philadelphia, Pennsylvania

Patricia D. Scripko, MD Resident Department of Neurology Massachusetts General Hospital Brigham and Women’s Hospital Boston, Massachusetts

†John M. Sewell, BSEE Chief Engineer Active Signal Technologies, Inc. Linthicum, Maryland

Robert G. Siman, PhD Research Professor Department of Neurosurgery Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

Carrie A. Sims, MD, FACS Assistant Professor Department of Surgery Division of Traumatology, Surgical Critical Care, and Emergency Surgery Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania

Richard O. Sinnott, PhD Director, eResearch University of Melbourne Melbourne, Australia

Alan Siu Resident Department of Neurological Surgery The George Washington University Medical Center Washington, District of Columbia

†Deceased

Marco D. Sorani, PhD Adjunct Assistant Professor Department of Neurological Surgery University of California, San Francisco San Francisco, California

Alejandro M. Spiotta, MD Resident Department of Neurosurgery Cleveland Clinic Cleveland, Ohio

John J. Stern, MD Clinical Professor Department of Medicine Perelman School of Medicine at the University of Pennsylvania; Chief, Division of Infectious Diseases Department of Medicine Pennsylvania Hospital Philadelphia, Pennsylvania

Nino Stocchetti, MD Professor of Anesthesia and Intensive Care Terapia Intensiva Neuroscienze Fondazione IRCCS Cà Granda University of Milan Milan, Italy

Jose I. Suarez, MD Professor Departments of Neurology and Neurosurgery Baylor College of Medicine; Director Vascular Neurology and Neurocritical Care Baylor College of Medicine Houston, Texas

Farzana Tariq, MD Cerebrovascular and Skull Base Fellow Department of Neurological Surgery University of Washington Seattle, Washington

Kyla P. Terhune, MD Assistant Professor of Surgery and Anesthesiology Division of General Surgery Vanderbilt University School of Medicine Nashville, Tennessee

Brett Trimble, BSME Director, Advanced Technology Integra LifeSciences Corporation San Diego, California

Contributors

David K. Vawdrey, PhD

Brandon von Tobel, MD, MBE

Elisa R. Zanier, MD

Assistant Professor of Clinical Biomedical Informatics Department of Biomedical Informatics Columbia University College of Physicians and Surgeons New York, New York

Vice President of Finance and Operations ImaCor, Inc. New York, New York

Department of Neuroscience Instituto Mario Negri Milan, Italy

Howard Yonas, MD

Craig Zimring, PhD

Professor and Chairman Department of Neurosurgery University of New Mexico School of Medicine Albuquerque, New Mexico

Professor of Architecture and Psychology Colleges of Architecture and Psychology Georgia Institute of Technology Atlanta, Georgia

Paul M. Vespa, MD Professor of Neurosurgery and Neurology Department of Neurosurgery David Geffen School of Medicine at UCLA; Director Neurocritical Care Ronald Reagan UCLA Medical Center Los Angeles, California

Brad E. Zacharia, MD Resident Department of Neurological Surgery Columbia University Medical Center/New York-Presbyterian New York, New York

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Abbreviations NOTE: Abbreviations may have more than one meaning, depending on their context. 3-H  hypertension, hemodilution, and hypervolemia AACN  American Association of Critical Care Nurses AAN  American Academy of Neurology AARP  American Association of Retired Persons ABA  American Bar Association ABM  acute bacterial meningitis ABP  arterial blood pressure ACA  anterior cerebral artery ACE  angiotensin converting enzyme ACEI/ARBs  angiotensin-converting enzyme inhibitor/ angiotensin-receptor blocker ACGME  Accreditation Council for Graduate Medical Education AChE  acetylcholinesterase ACCP  American College of Chest Physicians ACoA  anterior communicating artery ACS  abdominal compartment syndrome ACT  activated clotting time ACTH  adrenocorticotrophic hormone ACV  assist control ventilation AD  axial diffusivity ADC  apparent diffusion coefficient ADH  antidiuretic hormone ADL  activities of daily living ADNI  Alzheimer’s Disease Neuroimaging Database ADP  adenosine diphosphate ADQI  Acute Dialysis Quality Initiative ADR  alpha/delta ratio ADT  admission/discharge/transfer AED  antiepileptic drug aEEG  amplitude-integrated electroencephalography AEP  auditory evoked potentials AF  atrial fibrillation AG  anion gap AHA/ASA  American Heart Association/American Stroke Association AI  artificial intelligence AIS  acute ischemic stroke AKI  acute kidney injury AKIN  Acute Kidney Injury Network ALF  acute liver failure ALFSG  Acute Liver Failure Study Group ALI  acute lung injury AMA  American Medical Association AMID  active implantable medical device ANH  artificial nutrition and hydration ANN  artificial neural network APACHE  Acute Physiology and Chronic Health Evaluation aPL  antiphospholipid antibodies APN  advanced practice nurse APP  abdominal perfusion pressure aPTT  activated partial thromboplastin time ARAS  ascending reticular activating system ARC  absolute reticulocyte count ARDS  acute respiratory distress syndrome ARi (or ARI)  autoregulation index ASA  American Society of Anesthesiology aSAH  aneurysmal subarachnoid hemorrhage ASIA  American Spinal Injury Association ASL  arterial spin labeling

ASTM  American Society for Testing and Materials AT  antithrombin ATC  automatic tube compensation ATN  acute tubular necrosis ATP  adenosine triphosphate ATS  American Thoracic Society AU  arbitrary units AV  audiovisual AVDO2  arteriovenous difference in oxygen AVM  arteriovenous malformation BA  basilar artery BAEP  brainstem auditory evoked potential BAM  brain acoustic monitor BANN  Bayesian Artificial Neural Network BBB  blood-brain barrier BFV  blood flow velocity BG  blood glucose BHI  breath holding index BIS  bispectral index BMI  body mass index BMR  basal metabolic rate BOLD  blood oxygen level dependent BOOST  Brain Oxygen and Outcome Study in Traumatic Brain Injury BP  blood pressure BPI  bactericidal permeability-increasing protein BrainIT  brain monitoring with information technology BSI  bloodstream infection BSM  bedside monitors BT  brain temperature BTO  balloon test occlusion BUN  blood urea nitrogen CA  cerebral autoregulation (Chapters 30, 46) CA  cardiac arrest (Chapter 25) CA-BSI  catheter-associated bloodstream infection CAD  coronary artery disease CAM-ICU  Confusion Assessment Method for the ICU CAP  College of American Pathologists CAR  cerebral arterial resistance CAS  carotid angioplasty and stenting CASL  continuous arterial spin labeling CBF  cerebral blood flow CBFV  cerebral blood flow velocity CBV  cerebral blood volume CCAT  Computerized Cognitive Assessment Tool CCO  continuous cardiac output CCT  central conduction time Ccw  compliance of the chest wall CDC  Centers for Disease Control and Prevention CDSA  color density spectral array CEA  carotid endarterectomy cEEG  continuous electroencephalography CES  cholesterl emboli syndrome CEUs  continuing education units CFM  cerebral function monitoring C-FMZ  C-flumazenil Cho  choline CHr  reticulocyte hemoglobin content CI  coagulation index

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Abbreviations

CINMA  critical illness neuromuscular abnormalities CIPM  critical illness polyneuromyopathy CIPNM  critical illness polyneuropathy and myopathy CIRCI  critical illness related corticosteroid insufficiency CK  creatine kinase Cl  compliance of the lung CLIA 88  Clinical Laboratory Improvements Amendments of 1988 CLAB  central line-associated bacteraemia CLABSI  central line-associated bloodstream infection CMAP  compound muscle action potentials CMO  comfort measures only CMRO2  cerebral metabolic rate of oxygen CMRGluc  cerebral metabolic rate of glucose CMS  Centers for Medicare and Medicaid Services CMV  cytomegalovirus CNS  central nervous system CO  cardiac output CO2  carbon dioxide COGIF  Consensus on Grading Intracranial Flow COI  cerebral oxygenation index COM  communication COMBI  Center for Outcome Measurement in Brain Injury COMPACCS  Committee on Manpower for Pulmonary and Critical Care Societies COPD  chronic obstructive pulmonary disease COx  cerebral oximetry index CPAP  continuous positive airway pressure CPOE  computerized order entry CPP  cerebral perfusion pressure CPR  cardiopulmonary resuscitation CPSE  complex partial status epilepticus CPT  current procedural terminology Cr  creatine CRH  corticotropin-releasing hormone CRM  crew/crisis resource management CRMP  collapsin response mediator protein CRP  C-reactive protein CRRT  continuous renal replacement therapy CRS  Coma Recovery Scale CRS-R  Coma Recovery Scale–Revised Crs  compliance of respiratory system CSA  cross-sectional area CSD  cortical spreading depression CSE  convulsive status epilepticus CSF  cerebrospinal fluid CSW  cerebral salt wasting CT  computed tomography CTA  computed tomography angiography CTP  computed tomography perfusion (Chapters 13, 26) CTP  Child-Turcotte-Pugh (Chapter 23) CTT  central conduction time CTV  cerebral venous thrombosis CVC  central venous catheter CVP  central venous pressure CVR  cerebrovascular resistance CVT  cerebral venous thrombosis CVVH  continuous veno-venous hemofiltration CXR  chest x-ray D  diameter of conduit DAI  diffuse axonal injury dARi  dynamic autoregulation index DBN  dynamic Bayesian network DBP  diastolic blood pressure DBS  deep brain stimulator DC  decompressive craniectomy DCI  delayed cerebral ischemia DCS  diffuse correlation spectroscopy DHCA  deep hypothermic circulatory arrest

DHHS  Department of Health and Human Services DI  diabetes insipidus DIC  disseminated intravascular coagulation DIND  delayed ischemic neurologic deficit DIT  drug-induced thrombocytopenia DITP  drug-induced immune thrombocytopenia dIVC  inferior vena cava diameter DLCO  diffusing capacity of the lung for carbon monoxide DMN  default mode network DO2  oxygen delivery DoD  Department of Defense DoE  Department of Energy DRG  diagnostic related group DRS  Disability Rating Scale DS  Down syndrome DSA  digital subtraction angiography DSM  Diagnostic and Statistical Manual of Mental Disorders DSP  digital signal processing DTI  diffusion tensor imaging DUS  duplex ultrasonography DV  data validation DVT  deep vein thrombosis DWI  diffusion-weighted imaging EAA  excitatory amino acids EBM  evidence-based medicine EBNP  evidence-based nursing practice EBP  evidence-based practice EC-IC  extracranial to intracranial ECA  external carotid artery ECCO  Essentials of Critical Care Orientation ECF  extracellular fluid ECoG  electrocorticogram ED  emergency department EDC  extended differential count EDH  epidural hematoma EDM  esophageal Doppler monitor EDTA  ethylene diamine tetra acetate EEG  electroencephalography; electroencephalogram EF  ejection fraction E-GOS  Extended Glasgow Outcome Scale EHR  electronic health record EIT  electrical impedance tomography EKG  electrocardiogram ELISA  enzyme-linked immunological sample assay EMG  electromyogram EMI  electromagnetic interference EMR  electronic medical record EMS  emergency medical services EN  enteral nutrition eNAA  extracellular N-acetyl aspartate EOG  electrooculogram EP  evoked potential EPIC  extended prevalence of infection in intensive care EPL  estimated percent lysis EPO  erythropoietin EPOR  erythropoietin receptor ESA  erythropoiesis-stimulating agents ESICM  European Society of Intensive Care Medicine ESO  European Stroke Organization ESRD  end-stage renal disease ET  endotracheal tube etCO2  end-tidal carbon dioxide ETF  Emerging Technology Fund EU  European Union EVD  external ventricular drain EVLWI  extravascular lung water index FA  fractional anisotropy FC  Foley catheter

FDA  Food and Drug Administration FD&C  Food, Drug, and Cosmetic Act FDG  fluorodeoxyglucose Fe  iron FENa  fractional excretion of sodium FET  field effect transistor FFF  family, friends, and fools FFP  fresh frozen plasma FFT  fast-Fourier transformation FIM  Functional Independence Measure FiO2  inspiratory oxygen fraction FLAIR  fluid-attenuated inversion recovery fMRI  functional magnetic resonance imaging FNHTR  febrile non-hemolytic transfusion reactions FNN  Foundations of Neuroscience Nursing FOIA  Freedom of Information Act FOUR  Full Outline of UnResponsiveness FRBC  fragmented RBC FTc  flow time correction F/V  Flotrac-Vigileo FV  flow velocity FVl  flow velocity, left FVL  Factor V Leiden FVr  flow velocity, right GAAP  generally accepted accounting practices GABA  gamma-aminobutyric acid GAP  growth associated protein GB  gigabyte GCS  Glasgow Coma Scale GDP  gross domestic product GFAP  glial fibrillary acidic protein GFR  glomerular filtration rate GH  growth hormone GHBP  growth-hormone binding protein GHRP  GH-releasing peptide GI  gastrointestinal GMDI  Glioma Molecular Diagnostic Initiative GMP  good manufacturing practices GN  glomerulonephritis GNP  gross national product GOS  Glasgow Outcome Scale G-PEDs  generalized periodic epileptiform discharges 1 H-MRS  proton magnetic resonance spectroscopy HAC  hospital-acquired condition HAI  hospital-acquired infection HAP  hospital-acquired pneumonia HbO2  oxyhemoglobin HCAP  heathcare-associated pneumonia Hct  hematocrit HE  hepatic encephalopathy HELLP  hemolytic anemia, elevated liver enzymes, low platelets syndrome Hgb  hemoglobin HHb  deoxyhemoglobin HHCFA  Health Care Financing Organization HHNK  hyperglycemic hyperosmolar nonketotic HIE  hypoxic-ischemic encephalopathy HIPAA  Health Insurance Portability and Accountability Act HIT  heparin-induced thrombocytopenia HiTT  high dose thrombin time HIV  human immunodeficiency virus HLA  human leukocyte antigens HMG CoA  3-hydroxy-3-methylglutaryl coenzyme A HMS  Haemostasis Management System HPA  hypothalamic-pituitary axis HPS  human patient stimulator HR  heart rate HRS  hepatorenal syndrome

Abbreviations HSE  Herpes simplex encephalitis HSV  Herpes simplex virus HUS  hemolytic uremic syndrome HV  hyperventilation IAP  intra-abdominal pressure IBW  ideal body weight ICA  internal carotid artery ICAMs  intracellular adhesion molecules ICE  integrated clinical environment ICG  indocyanine green ICH  intracerebral hemorrhage ICP  intracranial pressure ICDSC  Intensive Care Delirium Screening Checklist ICU  intensive care unit IDE  investigational device exemption IDSA  Infectious Diseases Society of America IEEE  Institute of Electrical and Electronic Engineers iEEG  intermittent electroencephalography IFNα  interferon-α IH  intracranial hypertension IHD  ischemic heart disease IIT  intensive insulin therapy IJV  internal jugular vein IL  interleukin IMZ  iomazenil IND  investigational new drug INR  international normalized ratio IOM  Institute of Medicine IOP  intraocular pressure IP  intellectual property IPC  intermittent pneumatic compression IPF  immature platelet fraction IPS  intensive care unit physician staffing IRF  immature reticulocyte fraction ISF  International Sepsis Forum ISHEN  International Society for Hepatic Encephalopathy and Nitrogen Metabolism ISO  International Organization for Standardization ISS  Injury Severity Score IT  information technology ITAA  Information Technology Association of America ITBVI  intrathoracic blood volume index IV  intravenous IVC  inferior vena cava IVIg  intravenous immunoglobulin KIM-1  kidney injury molecular 1 LC  liquid chromatography LCD  liquid crystal display LDF  laser Doppler flowmetry LDH  lactate dehydrogenase LDUH  low-dose unfractionated heparin LGIB  lower gastrointestinal bleeding LGR  lactate : glucose ratio LIP  lower inflection point LMWH  low molecular weight heparin lp(a)  lipoprotein (a) LOC  loss of consciousness LOH  Loop of Henle LOI  lactate oxygen index LOS  length of stay LP  lumbar puncture LPR  lactate : pyruvate ratio LUS  lung ultrasound LV  left ventricle LVEDA  left ventricular end-diastolic area LVEDV  left ventricular end-diastolic volume MA  maximum amplitude MAC  mid arm circumference (Chapter 14)

xvii

xviii

Abbreviations

MAC  minimum alveolar concentration (Chapter 9) MAP  mean arterial pressure MAP2  microtubule-associate protein type 2 MB  megabyte MBP  myelin basic protein MBs  microbubbles MCA  middle cerebral artery MCHC  mean corpuscular hemoglobin concentration MCI  mild cognitive impairment MCMC  Monte Carlo Markov Chain MCS  minimally conscious state MCV  mean corpuscular volume MCVr  reticulocyte volume MD  mean diffusion (Chapter 28) MD  microdialysis (Chapters 36, 48) MDCT  multidetector computed tomography MDPnP  Medical Device Plug and Play MDS  myelodysplastic syndrome MEE  measured energy expenditure MEMS  micro electro-mechanical system MEP  motor evoked potential MES  microembolic signal MeSH  medical subject heading MFI  microcirculatory flow index mGy  milli-Gray MI  Maastricht Index (Chapter 14) MI  myocardial infarction (Chapter 15) MIB  Medical Information Bus MICU  medical intensive care unit MIPS  maximum intensity projections MMM  multi modality monitor MMP  matrix metalloproteinases MMPF  multimodal pressure-flow MMSE  Mini-Mental Status Examination MOANS  Mayo’s Older Americans Normative Studies MOCA  Montreal Cognitive Assessment MODS  Multiple Organ Dysfunction Syndrome MPAI  Mayo Portland Adaptability Inventory MPM  Mortality Probability Model MPV  mean platelet volume MR  magnetic resonance MRA  magnetic resonance angiography MRI  magnetic resonance imaging MRP  magnetic resonance perfusion MRS  magnetic resonance spectroscopy mRS  modified Rankin Scale MRSA  methicillin resistant Staphylococcus aureus MS  mass spectrometry mSv  milli-Sieverts MTT  mean transit time Mx  autoregulation NAA  N-acetyl aspartate NADH  nicotinamide adenine dinucleotide NAG  N-acetyl-glucosaminidase NBH  normobaric hyperoxia nCPPl  noninvasive cerebral perfusion pressure, left nCCPr  noninvasive cerebral perfusion pressure, right NCCU  neurocritical care unit NCS  nonconvulsive seizures NCSE  nonconvulsive status epilepticus NEMS  nano electro-mechanical system NFH  neurofilament heavy chain NFL  neurofilament light chain NFM  neurofilament middle chain NGAL  neutrophil gelatinase-associated lipocalin NHSN  National Healthcare Safety Network NIBP  noninvasive blood pressure NICE  National Institute for Clinical Excellence

NiCO  noninvasive cardiac output NICU  neurointensive care unit NIH  National Institutes of Health NIHSS  National Institutes of Health Stroke Scale NINDS  National Institute of Neurological Disease and Stroke NIRS  near infrared spectroscopy NMDA  N-methyl-D-aspartic NNIS  National Nosocomial Infections Surveillance NO  nitric oxide NOS  nitric oxide synthase NOx  nitric oxide metabolite NPH  normal pressure hydrocephalus NPV  negative predictive value NRBC  nucleated red blood cell NRCPR  National Registry of Cardiopulmonary Resuscitation NRI  Nutritional Risk Index NSAID  nonsteroidal anti-inflammatory drug NSE  neuron-specific enolase NSF  National Science Foundation (Chapter 38) NSF  nephrogenic systemic fibrosis (Chapter 22) NTIS  nonthyroidal illness syndrome NTP  Network Time Protocol OAST  Optimizing Analysis of Stroke Trials OEF  oxygen extraction fraction OGR  oxygen-glucose ratio ONS  optic nerve sheath OPS  orthogonal polarizing spectral OR  operating room P4P  pay-for-performance PA  pulmonary artery PAC  pulmonary artery catheter PaCO2  arterial carbon dioxide tension PACS  picture archiving and communication system PAD  pulmonary artery diastolic PAGE  polyacrylamide gel electrophoresis PAI  plasminogen activator inhibitor Palv  alveolar pressure PaO2  arterial oxygen tension PAOP  pulmonary artery occlusion pressure PAP  pulmonary pressures PAR  pressure autoregulation PAS  pulmonary artery systolic PASL  pulsed arterial spin labeling PAV  percent alpha variability PAV+  proportional assist ventilation Paw  airway pressures PbtO2  brain tissue oxygen tension PCA  posterior cerebral artery pCAM-ICU  Pediatric Confusion Assessment Method for Intensive Care Unit PCI  percutaneous coronary interventions PCM  pulse contour method PCR  polymerase chain reaction PCT  proximal convoluted tubule PCWP  pulmonary capillary wedge pressure PDSA  Plan-Do-Study-Act PE  pulmonary embolism PED  periodic epileptiform discharges PEEP  positive end-expiratory pressure PEEPi  intrinsic positive end-expiratory pressure Pes  esophageal pressure PET  positron emission tomography PF4  platelet factor 4 PI  pulsatility index PICARD  Program to Improve Care in Acute Renal Disease PICC  peripherally inserted central catheter PID  peri-infarct depolarizations PICU  pediatric intensive care unit

PILOT  Pediatric Intensity Level of Therapy PIM  Pediatric Index of Mortality Pip  peak inspiratory pressure Pl  transpulmonary pressure PLED  periodic lateralized epileptiform discharge Pleth-HR  heart rate from oxygen saturation monitor PMA  premarket approval PN  parenteral nutrition PO2  partial pressure of oxygen POC  point of care PoCoA  posterior communicating artery POCT  point of care testing Pplat  plateau pressure PPV  pulse pressure variation PRAM  pressure recording analytical method PRBC  packed red blood cell PRESS  posterior reversible leukoencephalopathy syndrome PRx  cerebrovascular pressure reactivity index PSV  pressure support ventilation PT  prothrombin time PT/INR  prothrombin time/international normative ratio PTS  Pediatric Trauma Score PTSD  post-traumatic stress disorder PTT  partial thromboplastin time PVD  patient-ventilator dyssynchrony PVI  pressure-volume index PvO2  oxygen partial pressure in venous blood PVS  persistent vegetative state PWI  perfusion-weighted imaging QFD  Quality Functional Deployment QI  quality initiatives qMRA  quantitative magnetic resonance angiography QODD  quality of dying and death QOL  quality of life QUASAR  quantitative STAR labeling of arterial regions RA  right atrium RAAS  renin-angiotensin-II-aldosterone system RAI  relative adrenal insufficiency RAIDs  redundant arrays of independent disks RALS  remote automated laboratory system RAP  cerebrospinal compensatory reserve RASS  Richmond Agitation-Sedation Scale RBC  red blood cell RBCT  red blood cell transfusion RC  reticulocyte count rCBF  regional cerebral blood flow RCM  radiocontrast media RCT  randomized clinical trial RDW  red cell distribution width REE  resting energy expenditure REG  rheoencephalography RF  radio frequency rhuEPO  recombinant human erythropoietin Ri  inspiratory resistance RN  registered nurse ROI  regions of interest ROSC  return of spontaneous circulation ROTEM  rotational thromboelastometry RPT  robotic telepresence RQ  respiratory quotient RR  respiratory rate RRT  renal replacement therapy RS  Ramsay Sedation Scale RSE  refractory status epilepticus rSO2  regional cerebral oxygen saturation rSO2C  regional cerebral tissue oxygenation rSO2R  regional renal tissue oxygenation rSO2S  regional splanchnic tissue oxygenation

Abbreviations

xix

rTEG  rapid thromboelastography rtPA  recombinant tissue plasminogen activator RTS  Revised Trauma Score RTV silicone  room temperature vulcanization silicone RV  right ventricle SAH  subarachnoid hemorrhage SaO2  arterial oxygen saturation SAPS  Simplified Acute Physiology Score SAS  Riker Sedation-Agitation Scale SATs  spontaneous awakening trial SBDP  spectrin breakdown degradation product SBI  secondary brain insults SBIR  Small Business Innovative Research SBP  systolic blood pressure SBP 120  spectrin breakdown products SBTs  spontaneous breathing trials SC  serum creatinine SCAT  Standardized Concussion Assessment Tool SCCM  Society of Critical Care Medicine SCI  spinal cord injury SCM  sternocleidomastoid muscle SCUF  slow continuous ultrafiltration ScVO2  oxygen saturation in superior vena cava (Chapters 19, 40) ScvO2  mixed venous oxygen saturation (Chapter 23) SDE  subdural empyema SDF  sidestream dark field SDH  subdural hematoma SE  status epilepticus SF  short form SIADH  syndrome of inappropriate antidiuretic hormone sICH  spontaneous intracerebral hemorrhage SIMV  Synchronized Intermittent Mechanical Ventilation SIP  Sickness Impact Profile SIRS  systemic inflammatory response syndrome SjvO2  jugular venous oxygen saturation SLE  systemic lupus erythematosus SLT  scanning laser tomography SMBG  self-monitoring blood glucose SMR  standardized mortality ratio SNAP  superlattice nano wire pattern transfer SOFA  Sequential Organ Failure Assessment SPECT  single photon emission computed tomography SpO2  oxygen saturation SR  suppression ratio SSC  Surviving Sepsis Campaign SSEP  somatosensory evoked potential STC  shock trauma center StcO2  transcranial oxygen saturation StO2  tissue oxygen saturation STTR  Small Business Technology Transfer SV  stroke volume SVC  superior vena cava SVM  support vector machine SVO2  venous oxygen saturation SVV  stroke volume variability SWI  susceptibility-weighted imaging T  body temperature (Chapters 45, 48) T  translational (Chapter 6) T3  triiodothyronine T4  thyroxine TBI  traumatic brain injury Tc99m-ECD  technetium-99m-ethylcysteinate dimer Tc99m-HMPAO  technetium-99m-hexamethylpropyleneamine oxide TCCS  transcranial color-coded duplex sonography TCD  transcranial Doppler TcE  transcranial electrical (stimulation) TcEMEP  transcranial electrical motor evoked potential TcMMEP  transcranial magnetic motor evoked potential

xx

Abbreviations

TDF  thermal diffusion flowmetry TDM  time division multiplex TEE  transesophageal echocardiography TEG  thromboelastography TF  tissue factor TH  therapeutic hypothermia THb  total hemoglobin THR  transient hyperemic response THx  total hemoglobin reactivity TI  thermal index TIBC  total iron binding capacity TIBI  thrombolysis in brain ischemia TIL  Therapeutic Intensity Level TLC  total lymphocyte count TNF  tumor necrosis factor TOI  tissue oxygen index TOR  brain tissue oxygen response tPA  tissue plasminogen activator TPL  transplant TR  tricuspid regurgitation TRALI  transfusion-related acute lung injury TRC  tanned red cell TRH  thyrotropin-releasing hormone TRICC  transfusion requirements in critical care TRISS  Trauma Injury Severity Score TS  test standard TSF  triceps skinfold thickness TSH  thyroid stimulating hormone T-tau  total tau TTE  transthoracic echocardiography TTP  thrombotic thrombocytopenic purpura TV  tidal volume UCH  ubiquitin C-terminal hydrolase UFH  unfractionated heparin UGIB  upper gastrointestinal bleeding UIP  upper inflection point UMLS  Unified Medical Language System UNa  urinary sodium concentration

UO  urine output US  ultrasound UTI  urinary tract infection UUN  urine urea nitrogen VA  vertebral artery VALI  ventilator-associated lung injury VAP  ventilator-associated pneumonia VASO  vascular space occupancy VC  venture capital (Chapter 38) VC  vital capacity (Chapter 20) VCAM-1  vascular cell adhesion molecule-1 VE  expired minute volume vEEG  video electroencephalography VEGF  vascular endothelial cell growth factor VEP  visual evoked potentials V’I  inspiratory flow VILI  ventilator-induced lung injury VKA  vitamin K antagonist VMRr  vasomotor reactivity VO  virtual organization VO2  oxygen consumption VPR  volume-pressure response VRE  vancomycin-resistant enterococcus VS  vegetative state VSP  vasospasm vT  tidal volume VTE  venous thromboembolism VTI  velocity time integral vWD  von Willebrand’s disease vWF  von Willebrand multimers WBC  white blood cell WDM  wavelength division multiplex WFNS  World Federation of Neurological Societies WHO  World Health Organization WNV  West Nile virus WNVE  West Nile virus encephalitis Xe-CT  xenon-enhanced computed tomography

I

Chapter

1

 

Principles of Cerebral Metabolism and Blood Flow Brad E. Zacharia and E. Sander Connolly, Jr.

Introduction The brain’s survival and function depend on its ability to maintain a constant supply of oxygen and energy-rich substrate. To accomplish this feat the complex architecture of the brain that accounts for approximately 2% of total body mass demands approximately 20% of the total cardiac output, and consumes roughly one quarter of resting total body oxygen consumption.1,2

Cerebral Hemodynamics An understanding of the complex cerebral circulation first requires an understanding of basic physical principles about flow. Ohm’s law predicts that flow (Q) is proportional to the pressure gradient between inflow and outflow (ΔP) divided by the resistance to flow (R). Q = ∆P / R Analogously in the brain, cerebral perfusion pressure (CPP), the difference between arterial inflow and venous outflow pressure, represents the driving pressure for cerebral blood flow (CBF). CPP is the difference between mean arterial pressure (MAP) and the pressure in the thin-walled veins.1 Venous pressure changes with changes in intracranial pressure (ICP) and is typically 2 to 5 mm Hg higher than the central venous pressure. CPP, therefore, can be described as: CPP = MAP − ICP Poiseuille’s law demonstrates that in addition to CPP (ΔP), blood viscosity (η) and vessel radius (r) are key determinants of CBF (Q). Vessel length (L) is generally not measured in physiologic systems. Q = (πr 4 ∆P)/ 8 η L) Viscosity, the internal friction of blood flow, is frequently overlooked because direct measurement is difficult. Importantly, however, viscosity is felt to vary directly with changes in hematocrit and any other process that alters blood’s cellular composition. Blood viscosity also varies inversely with vessel diameter. This is a consequence of the increased velocity gradient of laminar flow as vessel size decreases, a parameter known as the shear rate.3 Thus for a given blood velocity, shear rates are greater in smaller vessels and apparent viscosity is 2

consequently lower in the microcirculation. This effect is known as the Fahraeus-Lindquist effect.1,4 The most powerful factor in Poiseuille’s law that can influence CBF is vessel radius. For example, the maximum constriction that can be obtained by hyperventilation is approximately 20% from baseline. This, however, leads to a decrease in CBF of approximately 60%.5 From a practical standpoint, all of this diameter regulation takes place in the microcirculation. With knowledge about how much blood flows to the brain and how much oxygen the brain extracts from this blood (arteriovenous difference in oxygen, AVDO2), one can calculate cerebral metabolic rate of oxygen (CMRO2) consumption. CMRO2 = CBF × AVDO2

Physiology of Cerebral Blood Flow and Cerebral Blood Volume Normal CBF is approximately 50 mL/100 g brain tissue/min.6 Flow is normally greater in gray matter than white matter. Under normal conditions there are critical thresholds for CBF in the brain to maintain tissue health and cellular integrity. When CBF is reduced to 25 mL/100 g/min there is electroencephalographic slowing, and at 20 mL/100 g/min loss of consciousness occurs. When CBF is less than 18 mL/100 g/min, cellular homeostasis becomes jeopardized and neurons convert to anaerobic metabolism.2,7,8 At a CBF of 10 mL/100 g/min, membrane integrity is compromised and irreversible brain damage is inevitable (Table 1.1). Tissue infarction, however, is related not only to CBF, but to time as well.7 Many different factors are postulated to maintain adequate CBF, but it is believed that local metabolic factors are of primary importance. Under normal circumstances, in areas of increased cerebral activity, vasoactive substances are released, which alters vascular tone and local perfusion. The compensatory increase in perfusion then creates a local washout effect, which leads to a reduction in perfusion. Key local metabolites include, but are not limited to, carbon dioxide (CO2), potassium, adenosine, nitric oxide, histamine, and prostaglandins.2 Cerebral blood volume (CBV) is determined by CBF and capacitance vessel diameter. CBV thus increases with vasodilation and decreases with vasoconstriction. The relationship © Copyright 2013 Elsevier Inc. All rights reserved.

Section I—Background



3

Table 1.1  Cerebral Blood Flow Thresholds Cerebral Blood Flow (mL/100 g/min)

Threshold

Consequences

40-60

—

Normal

20-30

Neurologic function

Start of neurologic symptoms Altered mental status

16-20

Electrical failure

Isoelectric electroencephalogram Loss of evoked potentials

10-12

Ionic pump failure

Na+ and K+ pump failure Cytotoxic edema

20 mm Hg) is an important secondary insult and associated with mortality after TBI. Patients with an admission Glasgow Coma Scale (GCS) score between 3 and 8 and an abnormal CT scan are most likely to develop intracranial hypertension, and it is recommended that these patients receive an ICP monitor. Knowledge about ICP is necessary to calculate CPP that is a “surrogate” of CBF where direct CBF monitoring is not used. The use of an ICP monitor is described in detail in the Brain Trauma Foundation’s Guidelines for severe TBI. Despite nearly 50 years of use, there is only class II evidence literature that supports a role for ICP monitors,42-45 although metaanalysis of the literature suggests use of an ICP is associated with better outcome after TBI.28 Histopathologic evidence for ischemia is a common finding in autopsy studies in TBI and SAH, and it is likely that inadequate CBF contributes to the occurrence of post-traumatic

Section I—Background

secondary brain insults and increases the probability of a poor outcome. In addition CBF threshold values for infarction and the penumbra (which remains potentially salvageable) have been defined. The tissue with a CBF between these two thresholds will proceed to infarction if CBF is not restored within a limited time window. Therefore CBF monitoring offers a rational approach to detect and prevent secondary insults.46-48 Bedside CBF monitors can be characterized as quantitative or qualitative and use either direct or indirect methods. Jugular oximetry and TCD provide nonquantitative or “adequacy of CBF” data and are the methods used most often in the NCCU. Jugular venous oxygen saturation (SjvO2) provides information about the adequacy of global CBF in relation to metabolic demands. Reduction in SjvO2 to less than 50% after TBI is associated with poor outcome, and there is some evidence to suggest that therapies based on this information may help improve outcomes. However, SjvO2 is limited by its lack of sensitivity to regional changes.49,50 TCD was introduced to clinical practice in 1981 and is based on the Doppler principle. It is noninvasive and can be used repeatedly but its interpretation is operator dependent. TCD measures CBF velocity and not CBF. However, reasonable correlations have been reported between TCD and xenon CT or PET CBF measurements. Invasive techniques to measure CBF continually include such techniques as laser Doppler flowmetry (LDF) and thermal diffusion flowmetry (TDF). Both are available as intraparenchymal probes placed through a small craniotomy or held in place by a skull bolt and offer the advantage of assessing tissue perfusion in the microcirculation rather than the major vessels. LDF measures erythrocyte flux and relative changes in CBF. In TDF the catheter contains a distal thermistor and a second, more proximal located temperature probe. The thermistor is heated to few degrees above tissue temperature, and the temperature probe samples temperature constantly. The temperature difference is thus a reflection of heat transfer and may be translated to a measure of CBF. Initial data suggest that TDF provides a sensitive real-time assessment of intraparenchymal CBF that agrees with the xenon CT CBF measurements.51 Monitors that provide a measure of the adequacy of CBF and insights into metabolism include direct brain oxygen tension measurement and cerebral microdialysis. Brain oxygen monitoring has demonstrated that many of the secondary processes that complicate primary brain injury—hypotension, hypoxia, intracranial hypertension—all can decrease brain oxygen tension.52,53 The result of oxygen deprivation is increased anaerobic metabolism, which in turn can lead to cell death and progressive inflammation.54 Cerebral microdialysis can be used to detect such metabolic changes before irreversible injury and may complement cerebral oximetry or ICP measurements. Severe hypoxia or ischemia is typically associated with marked increases in the lactate/pyruvate ratio that correlates with the PET-measured oxygen extraction fraction. An increase in the lactateto-pyruvate ratio greater than what is considered normal (20 : 25) is associated with a poor outcome in severe TBI. Both brain oxygen monitors and cerebral microdialysis can be used in patients with epilepsy, stroke, SAH, and TBI, where their use often may detect pathology that is not detected by more conventional means.55-61 Seizures are a source of secondary insult to the injured brain. Recent data from continuous electroencephalography (cEEG) studies demonstrate that seizures, mostly not clinically

13

manifest, occur in more than 20% of patients in the NCCU with a variety of pathologies including TBI, SAH, or ICH, among others. In addition EEG can be used to detect ischemia that may be particularly useful in patients with SAH who develop vasospasm. Other applications of cEEG include prognostication of outcome, for example, the use of alpha variability in cEEG recordings may help predict outcome after TBI.62-64

Conclusion Neuromonitoring has evolved and become an integral part of the care of patients with neurocritical care diseases. The primary justification for monitoring is that detection of early neurologic worsening can prevent irreversible brain damage. Neuromonitoring may help to individualize patient care decisions, guide patient management, and monitor the therapeutic response of interventions and so avoid any potential adverse effects. In addition, monitoring may allow physicians and nurses to understand the pathophysiology of complex disorders, to design and implement management protocols based on real-time data, and to improve neurologic outcome and quality of life in survivors of severe brain injury. Traditional monitoring in the NCCU has been largely reactive, but with the introduction of more advanced neuromonitoring the information provided by newer monitoring techniques now allows trends to be defined and for the proactive treatment of patients. The application of clinical informatics and the use of multimodal monitoring are evolving and have become standard in some NCCUs; this is centered on patient-specific physiologic targets. Further evolution of monitoring and its integration is likely in the coming years such that decision support will become commonplace in the NCCU.

References 1. Rosamond W, Flegal K, Furie K, et al. Heart disease and stroke statistics— 2008 Update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation 2008;117: e25–146. 2. Hyder AA, Wunderlich CA, Puvanachandra P, et al. The impact of traumatic brain injuries: a global perspective. NeuroRehabilitation 2007;22: 341–53. 3. Wijdicks EFM, Hijdra A, Young GB, et al. Practice parameter: prediction of outcome in comatose survivors after cardiopulmonary resuscitation (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 2006;67:203–10. 4. Bershad EM, Feen ES, Hernandez OH, et al. Impact of a specialized neurointensive care team on outcomes of critically ill acute ischemic stroke patients. Neurocrit Care 2008;9:287–92. 5. Suárez JI. Critical care neurology and neurosurgery. Totowa, NJ: Humana Press; 2004. 6. Ropper AH, Gress DR, Diringer MN, et al. Neurological and neurosurgical intensive care. 4th ed. Philadelphia: Lippincott Williams & Wilkins; 2003. 7. Mayer SA, Coplin WM, Chang C, et al. Neurocritical Care Society; American Academy of Neurology Section on Critical Care and Emergency Neurology; Society of Neurosurgical Anesthesia and Critical Care. Program requirements for fellowship training in neurological intensive care: United Council for Neurologic Subspecialties guidelines. Neurocrit Care 2006;5(2):166–71. 8. Mayer SA, Coplin WM, Chang C, et al. Neurocritical Care Society; American Academy of Neurology Section on Critical Care and Emergency Neurology; Society of Neurosurgical Anesthesia and Critical care. Core curriculum and competencies for advanced training in neurological intensive care: United Council for Neurologic Subspecialties guidelines. Neurocrit Care 2006;5(2): 159–65.

14

Section I—Background

9. Suarez JI. Outcome in neurocritical care: advances in monitoring and treatment and effect of a specialized neurocritical care team. Crit Care Med 2006;34:S232–8. 10. Varelas PN, Eastwood D, Yun HJ, et al. Impact of a neurointensivist on outcomes in patients with head trauma treated in a neurosciences intensive care unit. J Neurosurg 2006;104:713–19. 11. Varelas PN, Schultz L, Conti M, et al. The impact of a neuro-intensivist on patients with stroke admitted to a neurosciences intensive care unit. Neurocrit Care 2008;9:293–9. 12. Diringer MN, Edwards DF. Admission to a neurologic/neurosurgical intensive care unit is associated with reduced mortality rate after intracerebral hemorrhage. Crit Care Med 2001;29:635–40. 13. Mirski MA, Chang CW, Cowan R. Impact of a neuroscience intensive care unit on neurosurgical patient outcomes and cost of care: evidence-based support for an intensivist-directed specialty ICU model of care. J Neurosurg Anesthesiol 2001;13:83–92. 14. Berman MF, Solomon RA, Mayer SA, et al. Impact of hospital-related factors on outcome after treatment of cerebral aneurysms. Stroke 2003;34:2200–7. 15. Wilby MJ, Sharp M, Whitfield PC, et al. Cost-effective outcome for treating poor-grade subarachnoid hemorrhage. Stroke 2003;34:2508–11. 16. Suarez JI, Zaidat OO, Suri MF, et al. Length of stay and mortality in neurocritically ill patients: impact of a specialized neurocritical care team. Crit Care Med 2004;32:2311–17. 17. Bernard SA, Gray TW, Buist MD, et al. Treatment of comatose survivors of out-of-hospital cardiac arrest with induced hypothermia. N Engl J Med 2002;346:557–63. 18. Hypothermia After Cardiac Arrest Study Group. Mild therapeutic hypothermia to improve the neurologic outcome after cardiac arrest. N Engl J Med 2002;346:549–56. 19. Varelas PN, Spanaki MV, Hacein-Bey L. Documentation in medical records improves after a neurointensivist’s appointment. Neurocrit Care 2005;3:234–6. 20. Helms AK, Torbey MT, Hacein-Bey L, et al. Standardized protocols increase organ and tissue donation rates in the neurocritical care unit. Neurology 2004;63:1955–7. 21. Rosenthal G, Hemphill 3rd JC, Sorani M, et al. Brain tissue oxygen tension is more indicative of oxygen diffusion than oxygen delivery and metabolism in patients with traumatic brain injury. Crit Care Med 2008;36:1917–24. 22. Obrist WD, Langfitt TW, Jaggi JL, et al. Cerebral blood flow and metabolism in comatose patients with acute head injury: relationship to intracranial hypertension. J Neurosurg 1984;61:241–53. 23. Lassen N. Cerebral blood flow and oxygen consumption in man. Physiol Rev 1959;39:183–238. 24. Rosner M, Rosner S, Johnson A. Cerebral perfusion pressure: management protocol and clinical results. J Neurosurg 1995;83:949–62. 25. Sahuquillo J. Does multimodality monitoring make a difference in neurocritical care? Eur J Anaesthesiol Suppl 2008;42:83–6. 26. Varelas PN, Conti MM, Spanaki MV, et al. The impact of a neurointensivistled team on a semiclosed neurosciences intensive care unit. Crit Care Med 2004;32:2191–8. 27. Kurtz P, Fitts V, Sumer Z, et al. How does care differ for neurological patients admitted to a neurocritical care unit versus a general ICU? Neurocrit Care 2011;Apr 26. Epub ahead of print. 28. Stein SC, Georgoff P, Meghan S, et al. Relationship of aggressive monitoring and treatment to improved outcomes in severe traumatic brain injury. J Neurosurg 2010;112(5):1105–12. 29. Spiotta AM, Stiefel MF, Gracias VH, et al. Brain tissue oxygen-directed management and outcome in patients with severe traumatic brain injury. J Neurosurg 2010;113:571–80. 30. Adamides AA, Rosenfeldt FL, Winter CD, et al. Brain tissue lactate elevations predict episodes of intracranial hypertension in patients with traumatic brain injury. J Am Coll Surg 2009;209:531–9.

31. Chesnut RM, Marshall LF, Klauber MR, et al. The role of secondary brain injury in determining outcome from severe head injury. J Trauma 1993;34: 216–22. 32. Oddo M, Schmidt JM, Carrera C, et al. Impact of tight glycemic control on cerebral glucose metabolism after severe brain injury: a microdialysis study. Crit Care Med 2008;36:3233–8. 33. Oddo M, Milby A, Chen I, et al. Hemoglobin concentration and cerebral metabolism in patients with aneurysmal subarachnoid hemorrhage: a microdialysis study. Stroke 2009;40(4):1275–81. 34. Oddo M, Frangos S, Maloney-Wilensky E, et al. Effect of shivering on brain tissue oxygenation during induced normothermia in patients with severe brain injury. Neurocrit Care 2010;12(1):10–6. 35. Robertson CS, Valadka AB, Hannay HJ, et al. Prevention of secondary ischemic insults after severe head injury. Crit Care Med 1999;27:2086–95. 36. Elf K, Nilsson P, Enblad P. Outcome after traumatic brain injury improved by an organized secondary insult program and standardized neurointensive care. Crit Care Med 2002;30:2129–34. 37. Markgraf C, Clifton G, Moody M. Treatment window for hypothermia in brain injury. J Neurosurg 2001;95:979–83. 38. Clifton GL, Choi SC, Miller ER, et al. Intercenter variance in clinical trials of head trauma—experience of the National Acute Brain Injury Study: hypothermia. J Neurosurg 2001;95:751–5. 39. Newberg AB, Alavi A. Neuroimaging in patients with head injury. Semin Nucl Med 2003;33:136–47. 40. Jacobs A, Put E, Ingels M, et al. Prospective evaluation of technetium-99mHMPAO SPECT in mild and moderate traumatic brain injury. J Nucl Med 1994;35:942–47. 41. Wintermark M, Chiolero R, Van Melle G, et al. Cerebral vascular autoregulation assessed by perfusion-CT in severe head trauma patients. J Neuroradiol 2006;33:27–37. 42. The Brain Trauma Foundation. The American Association of Neurological Surgeons. The Joint Section on Neurotrauma and Critical Care. Indications for intracranial pressure monitoring. J Neurotrauma 2000;17:479–91. 43. Becker DP, Miller JD, Ward JD, et al. The outcome from severe head injury with early diagnosis and intensive management. J Neurosurg 1977;47: 491–502. 44. Ghajar JB, Hairiri RJ, Paterson RH, et al. Improved outcome from traumatic coma using only ventricular CSF drainage for ICP control. Adv Neurosurg 1993;21:173–7. 45. Narayan RK, Kishore PR, Becker DP, et al. Intracranial pressure: to monitor or not to monitor? A review of our experience with severe head injury. J Neurosurg 1982;56:650–9. 46. Bouma GJ, Muizelaar JP, Choi SC, et al. Cerebral circulation and metabolism after severe traumatic brain injury: the elusive role of ischemia. J Neurosurg 1991;75:685–93. 47. Robertson CS, Contant CF, Gokaslan ZL, et al. Cerebral blood flow, arteriovenous oxygen difference, and outcome in head injured patients. J Neurol Neurosurg Psychiatry 1992;55:594–603. 48. Symon L, Held K, Dorsch N. A study of regional autoregulation in the cerebral circulation to increased perfusion pressure in normocapnia and hypercapnia. Stroke 1973;4:139–47. 49. Murr R, Schurer L. Correlation of jugular venous oxygen saturation to spontaneous fluctuations of cerebral perfusion pressure in patients with severe head injury. Neurol Res 1995;17:329–33. 50. Robertson CS, Gopinath SP, Goodman JC, et al. SjvO2 monitoring in head-injured patients. J Neurotrauma 1995;12:891–6. A complete list of references for this chapter can be found online at www.expertconsult.com.



References 1. Rosamond W, Flegal K, Furie K, et al. Heart disease and stroke statistics— 2008 Update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation 2008;117: e25–146. 2. Hyder AA, Wunderlich CA, Puvanachandra P, et al. The impact of traumatic brain injuries: a global perspective. NeuroRehabilitation 2007;22:341–53. 3. Wijdicks EFM, Hijdra A, Young GB, et al. Practice parameter: prediction of outcome in comatose survivors after cardiopulmonary resuscitation (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 2006;67:203–10. 4. Bershad EM, Feen ES, Hernandez OH, et al. Impact of a specialized neurointensive care team on outcomes of critically ill acute ischemic stroke patients. Neurocrit Care 2008;9:287–92. 5. Suárez JI. Critical care neurology and neurosurgery. Totowa, NJ: Humana Press; 2004. 6. Ropper AH, Gress DR, Diringer MN, et al. Neurological and neurosurgical intensive care. 4th ed. Philadelphia: Lippincott Williams & Wilkins; 2003. 7. Mayer SA, Coplin WM, Chang C, et al. Neurocritical Care Society; American Academy of Neuorology Section on Critical Care and Emergency Neurology; Society of Neurosurgical Anesthesia and Critical Care. Program requirements for fellowship training in neurological intensive care: United Council for Neurologic Subspecialties guidelines. Neurocrit Care 2006;5(2):166–71. 8. Mayer SA, Coplin WM, Chang C, et al. Neurocritical Care Society; American Academy of Neurology Section on Critical Care and Emergency Neurology; Society of Neurosurgical Anesthesia and Critical care. Core curriculum and competencies for advanced training in neurological intensive care: United Council for Neurologic Subspecialties guidelines. Neurocrit Care 2006;5(2): 159–65. 9. Suarez JI. Outcome in neurocritical care: advances in monitoring and treatment and effect of a specialized neurocritical care team. Crit Care Med 2006;34:S232–8. 10. Varelas PN, Eastwood D, Yun HJ, et al. Impact of a neurointensivist on outcomes in patients with head trauma treated in a neurosciences intensive care unit. J Neurosurg 2006;104:713–19. 11. Varelas PN, Schultz L, Conti M, et al. The impact of a neuro-intensivist on patients with stroke admitted to a neurosciences intensive care unit. Neurocrit Care 2008;9:293–9. 12. Diringer MN, Edwards DF. Admission to a neurologic/neurosurgical intensive care unit is associated with reduced mortality rate after intracerebral hemorrhage. Crit Care Med 2001;29:635–40. 13. Mirski MA, Chang CW, Cowan R. Impact of a neuroscience intensive care unit on neurosurgical patient outcomes and cost of care: evidence-based support for an intensivist-directed specialty ICU model of care. J Neurosurg Anesthesiol 2001;13:83–92. 14. Berman MF, Solomon RA, Mayer SA, et al. Impact of hospital-related factors on outcome after treatment of cerebral aneurysms. Stroke 2003;34: 2200–7. 15. Wilby MJ, Sharp M, Whitfield PC, et al. Cost-effective outcome for treating poor-grade subarachnoid hemorrhage. Stroke 2003;34:2508–11. 16. Suarez JI, Zaidat OO, Suri MF, et al. Length of stay and mortality in neurocritically ill patients: impact of a specialized neurocritical care team. Crit Care Med 2004;32:2311–17. 17. Bernard SA, Gray TW, Buist MD, et al. Treatment of comatose survivors of out-of-hospital cardiac arrest with induced hypothermia. N Engl J Med 2002;346:557–63. 18. Hypothermia After Cardiac Arrest Study Group. Mild therapeutic hypothermia to improve the neurologic outcome after cardiac arrest. N Engl J Med 2002;346:549–56. 19. Varelas PN, Spanaki MV, Hacein-Bey L. Documentation in medical records improves after a neurointensivist’s appointment. Neurocrit Care 2005;3:234–6. 20. Helms AK, Torbey MT, Hacein-Bey L, et al. Standardized protocols increase organ and tissue donation rates in the neurocritical care unit. Neurology 2004;63:1955–7. 21. Rosenthal G, Hemphill 3rd JC, Sorani M, et al. Brain tissue oxygen tension is more indicative of oxygen diffusion than oxygen delivery and metabolism in patients with traumatic brain injury. Crit Care Med 2008;36:1917–24. 22. Obrist WD, Langfitt TW, Jaggi JL, et al. Cerebral blood flow and metabolism in comatose patients with acute head injury: relationship to intracranial hypertension. J Neurosurg 1984;61:241–53. 23. Lassen, N. Cerebral blood flow and oxygen consumption in man. Physiol Rev 1959;39:183–238.

Section I—Background 14.e1 24. Rosner M, Rosner S, Johnson A. Cerebral perfusion pressure: management protocol and clinical results. J Neurosurg 1995;83:949–62. 25. Sahuquillo J. Does multimodality monitoring make a difference in neurocritical care? Eur J Anaesthesiol Suppl 2008;42:83–6. 26. Varelas PN, Conti MM, Spanaki MV, et al. The impact of a neurointensivistled team on a semiclosed neurosciences intensive care unit. Crit Care Med 2004;32:2191–8. 27. Kurtz P, Fitts V, Sumer Z, et al. How does care differ for neurological patients admitted to a neurocritical care unit versus a general ICU? Neurocrit Care 2011;Apr 26. [Epub ahead of print] 28. Stein SC, Georgoff P, Meghan S, et al. Relationship of aggressive monitoring and treatment to improved outcomes in severe traumatic brain injury. J Neurosurg 2010;112(5):1105–12. 29. Spiotta AM, Stiefel MF, Gracias VH, et al. Brain tissue oxygen-directed management and outcome in patients with severe traumatic brain injury. J Neurosurg 2010;113:571–80. 30. Adamides AA, Rosenfeldt FL, Winter CD, et al. Brain tissue lactate elevations predict episodes of intracranial hypertension in patients with traumatic brain injury. J Am Coll Surg 2009;209:531–9. 31. Chesnut RM, Marshall LF, Klauber MR, et al. The role of secondary brain injury in determining outcome from severe head injury. J Trauma 1993;34:216–22. 32. Oddo M, Schmidt JM, Carrera C, et al. Impact of tight glycemic control on cerebral glucose metabolism after severe brain injury: a microdialysis study. Crit Care Med 2008;36:3233–8. 33. Oddo M, Milby A, Chen I, et al. Hemoglobin concentration and cerebral metabolism in patients with aneurysmal subarachnoid hemorrhage: a microdialysis study. Stroke 2009;40(4):1275–81. 34. Oddo M, Frangos S, Maloney-Wilensky E, et al. Effect of shivering on brain tissue oxygenation during induced normothermia in patients with severe brain injury. Neurocrit Care 2010;12(1):10–6. 35. Robertson CS, Valadka AB, Hannay HJ, et al. Prevention of secondary ischemic insults after severe head injury. Crit Care Med 1999;27:2086–95. 36. Elf K, Nilsson P, Enblad P. Outcome after traumatic brain injury improved by an organized secondary insult program and standardized neurointensive care. Crit Care Med 2002;30:2129–34. 37. Markgraf C, Clifton G, Moody M. Treatment window for hypothermia in brain injury. J Neurosurg 2001;95:979–83. 38. Clifton GL, Choi SC, Miller ER, et al. Intercenter variance in clinical trials of head trauma—experience of the National Acute Brain Injury Study: hypothermia. J Neurosurg 2001;95:751–5. 39. Newberg AB, Alavi A. Neuroimaging in patients with head injury. Semin Nucl Med 2003;33:136–47. 40. Jacobs A, Put E, Ingels M, et al. Prospective evaluation of technetium-99mHMPAO SPECT in mild and moderate traumatic brain injury. J Nucl Med 1994;35:942–47. 41. Wintermark M, Chiolero R, Van Melle G, et al. Cerebral vascular autoregulation assessed by perfusion-CT in severe head trauma patients. J Neuroradiol 2006;33:27–37. 42. The Brain Trauma Foundation. The American Association of Neurological Surgeons. The Joint Section on Neurotrauma and Critical Care. Indications for intracranial pressure monitoring. J Neurotrauma 2000;17:479–91. 43. Becker DP, Miller JD, Ward JD, et al. The outcome from severe head injury with early diagnosis and intensive management. J Neurosurg 1977;47:491–502. 44. Ghajar JB, Hairiri RJ, Paterson RH, et al. Improved outcome from traumatic coma using only ventricular CSF drainage for ICP control. Adv Neurosurg 1993;21:173–7. 45. Narayan RK, Kishore PR, Becker DP, et al. Intracranial pressure: to monitor or not to monitor? A review of our experience with severe head injury. J Neurosurg 1982;56:650–9. 46. Bouma GJ, Muizelaar JP, Choi SC, et al. Cerebral circulation and metabolism after severe traumatic brain injury: the elusive role of ischemia. J Neurosurg 1991;75:685–93. 47. Robertson CS, Contant CF, Gokaslan ZL, et al. Cerebral blood flow, arteriovenous oxygen difference, and outcome in head injured patients. J Neurol Neurosurg Psychiatry 1992;55:594–603. 48. Symon L, Held K, Dorsch N. A study of regional autoregulation in the cerebral circulation to increased perfusion pressure in normocapnia and hypercapnia. Stroke 1973;4:139–47. 49. Murr R, Schurer L. Correlation of jugular venous oxygen saturation to spontaneous fluctuations of cerebral perfusion pressure in patients with severe head injury. Neurol Res 1995;17:329–33. 50. Robertson CS, Gopinath SP, Goodman JC, et al. SjvO2 monitoring in head-injured patients. J Neurotrauma 1995;12:891–6.

14.e2 Section I—Background 51. Vajkoczy P, Roth H, Horn P, et al. Continuous monitoring of regional cerebral blood flow: experimental and clinical validation of a novel thermal diffusion microprobe. J Neurosurg 2000;93:265–74. 52. Gopinath SP, Valadka AB, Uzura M, et al. Comparison of jugular venous oxygen saturation and brain tissue Po2 as monitors of cerebral ischemia after head injury. Crit Care Med 1999;27:2337–45. 53. Kiening KL, Härtl R, Unterberg AW, et al. Brain tissue pO2-monitoring in comatose patients: implications for therapy. Neurol Res 1997;19:233–40. 54. Siesjö BK. Pathophysiology and treatment of focal cerebral ischemia. Part II: mechanisms of damage and treatment. J Neurosurg 1992;77:337–54. 55. Clausen T, Alves OL, Reinert M, et al. Association between elevated brain tissue glycerol levels and poor outcome following severe traumatic brain injury. J Neurosurg 2005;103:233–8. 56. Meixensberger J, Kunze E, Barcsay E, et al. Clinical cerebral microdialysis: brain metabolism and brain tissue oxygenation after acute brain injury. Neurol Res 2001;23:801–6. 57. Hutchinson PJ, Gupta AK, Fryer TF, et al. Correlation between cerebral blood flow, substrate delivery, and metabolism in head injury: a combined microdialysis and triple oxygen positron emission tomography study. J Cereb Blood Flow Metab 2002;22:735–45. 58. Vespa P, Martin NA, Nenov V, et al. Delayed increase in extracellular glycerol with post-traumatic electrographic epileptic activity: support for the theory that seizures induce secondary injury. Acta Neurochir 2002;81(Suppl.):355–7.

59. Ståhl N, Mellergård P, Hallström A, et al. Intracerebral microdialysis and bedside biochemical analysis in patients with fatal traumatic brain lesions. Acta Anaesthesiol Scand 2001;45:977–85. 60. Reinstrup P, Ståhl N, Mellergård P, et al. Intracerebral microdialysis in clinical practice: baseline values for chemical markers during wakefulness, anesthesia, and neurosurgery. Neurosurgery 2000;47:701–9. 61. Vespa PM, McArthur D, O’Phelan K, et al. Persistently low extracellular glucose correlates with poor outcome 6 months after human traumatic brain injury despite a lack of increased lactate: a microdialysis study. J Cereb Blood Flow Metab 2003;23:865–77. 62. Scheuer ML. Continuous EEG monitoring in the intensive care unit. Epilepsia 2002;43(Suppl 3):114–27. 63. Vespa PM, Boscardin WJ, Hovda DA, et al. Early and persistent impaired percent alpha variability on continuous electroencephalography monitoring as predictive of poor outcome after traumatic brain injury. J Neurosurg 2002;97:84–92. 64. Vespa PM, Nuwer MR, Nenov V, et al. Increased incidence and impact of nonconvulsive and convulsive seizures after traumatic brain injury as detected by continuous electroencephalographic monitoring. J Neurosurg 1999;91:750–60.

Chapter

3

 

I

Designing the Neurocritical Care Unit for Better Patient Care Mahbub Rashid, Craig Zimring, and Owen B. Samuels

Introduction There is growing evidence that the physical design of clinical spaces affects the quality, efficiency, and experience of care in intensive care units (ICUs) and other settings.1-4 These effects are complex. In some cases the design directly leads to outcomes that might have clinical significance, for example, whether improved air filtering reduces airborne pathogens. In other cases the environment contributes to noise or lighting that can increase or decrease stress for patient, families, or staff. In yet other cases, the environment contributes to staff or patient behavior that may affect care. For instance, if staff see and encounter each other informally over the course of their day, they may better coordinate care,5 or if they see hand hygiene sinks or rubs, they may increase their compliance with handwashing.3 This chapter examines the effects of the ICU design and particularly the design of the neurocritical care unit (NCCU) on patient care. Addressed are the important areas within the ICU, key design considerations, main design guidelines, and emerging evidence on how ICU design influences patient care. The chapter ends with a case study in which the authors were involved, from the perspective of the medical director.

Evidence-Based Intensive Care Unit Design Research in ICU environmental design is an emerging field of study, and therefore high-quality research articles are still limited in number. In addition, many confounding variables can influence the outcome of ICU design research. Therefore along with the findings of ICU design research, the authors also present expert opinions and findings of research studies in other health care settings that may be relevant to ICU design. This section reviews the primary functional and procedural issues associated with ICU design and addresses the key areas of the ICU.

Unit Layout Unit layout defines the size and location of functional areas and their relationships within a unit. Major determinants of © Copyright 2013 Elsevier Inc. All rights reserved.

the layout include: (1) direct monitoring of patients by clinical staff, (2) an outside window for each patient room, and (3) reduction of cross-infection, traffic volume, and noise level, among other factors.

Monitoring In NCCUs, patients need constant visual monitoring because their conditions may change quickly and unpredictably, and these changes need to be recognized early. NCCU patients also require frequent neurologic assessments or bedside procedures that may involve multiple members of a care team. A physical layout that supports effective face-to-face interaction in a patient’s room and within the unit is thus required. In a teaching hospital the rooms or corridors also need to support the large number of participants who make patient rounds.

Windows U.S. law requires that ICU patients must have direct access to natural light. This same requirement also applies in several other countries (e.g., India, Saudi Arabia, and the United Arab Emirates). The number and arrangement of patient rooms consequently depend on the amount of peri­meter wall available in the unit. Therefore a review of best practice examples shows that designers often select compact shapes with high area-to-perimeter ratios to accommodate the maximum number of patient rooms for any given area. They also put most support areas, including nurse work areas, in the core that do not require any outside window to reduce the walking distance between clinical support areas and patient rooms.6

Limiting Infection, Traffic, and Noise Cross-infection, traffic volume, and noise level often may help shape unit configurations, and each of these factors is of greater significance in larger hospital units. Studies suggest that patients in larger units have greater risk of hospitalacquired infection.7,8 Larger units also have more traffic and noise sources. These noise sources commonly include noises of other patients (e.g., snoring, crying), monitor alarms, telephone rings and conversations, conversations among staff, 15

16

Section I—Background

staff entering or leaving, staff wandering, sudden voices, footsteps, falling objects, noises of respirators, doors closing, and visitors talking, among others.9 Breaking a larger unit into smaller units, pods, or clusters may reduce infection and noise. However, pods can break down the visual and social cohesiveness of a unit, and multiple pods may make movement of supplies difficult because they create more service stops. Thus the appropriate configuration for a large ICU remains a matter of striking the right balance among various contradictory factors.

Unit Size According to the Society of Critical Care Medicine’s Guidelines for Intensive Care Unit Design (henceforth, the Guidelines), 8 to 12 beds per unit are considered best from a functional perspective.10-13 In one survey, a group of ICU experts also suggested that the ideal number of patient beds in an ICU should be 9 or 10, and no less than 6.14 An NCCU with fewer than 6 beds may be inefficient to operate and manage. In contrast, in a very large unit without proper unit design and a sufficiently large nursing staff, patient monitoring and care may become difficult. The total gross area of a unit, another indicator for unit size, is somewhat related to the number of beds in the unit— the more beds the greater the ICU gross area per bed.6 The amount of circulation spaces, another determinant of the gross area of a unit, is an important indicator of the square footage efficiency of an ICU. Circulation spaces within an ICU consist of internal hallways, corridors, or aisles used by all ICU users—patients, ICU staff, and visitors. Like any other facility, an ICU may be inefficient with too much or too little circulation space. Circulation spaces are sociologically important because they determine the interconnectedness of people and functions within a facility. A narrow corridor within an ICU can impede transfer of knowledge as much as it can impede the flow of goods and people. Properly designed circulation spaces in ICUs may hold a great potential to enhance the transfer of tacit knowledge through face-to-face interactions.15 In the United States, the National Fire Protection Association’s Life Safety Code also affects ICU size and design. The Life Safety Code limits the size of any suite to 5000 square feet if it does not have intervening smoke partitions and fire-rated doors.16 The area per bed of a unit ranges from 650 to 1200 square feet or more depending on function on the unit, so most units require smoke partitions or “hold open” smoke doors. Hospitals and designers need to ensure that when any one part of an ICU larger than 5000 square feet becomes unavailable in the event of fire or smoke breakout, the other parts of the unit have the required components for patient and staff safety.

Unit Location Important departmental relationships of the unit should be carefully considered during the site selection process. Convenient physical movement across departments may help reduce many safety risks associated with patient transfer. In general, patients are transferred from one place to another as often as three to six times during their hospital stay to receive the care

that matches their level of acuity.17-19 This rate may be higher for NCCU patients. Delays, communication discontinuities, loss of information, and changes in computers and systems during patient transfer can contribute to increased medical errors and loss of staff time and productivity.18,20 Patients can get hurt, and most nurses’ back injuries occur during patient transfer (see the following text). Thus design interventions must include factors that help reduce the time and effort involved in patient transfer.

Patient Room Design A patient’s room is the basic working unit of an ICU, and it affects patient care including safety, privacy, and comfort. For example, nurses can save multiple trips to nursing stations or storage rooms if a patient’s room includes a space for charting or storage space for supplies. A longer distance between the bed and the toilet can increase physical stress for a nurse who needs to help the patient to the toilet. If there is a welldefined area within the room for families, they can be present for patient comfort and help caregivers by providing information and assistance with care. Important design considerations of patient rooms in the NCCU, similar to other ICUs, include to: (1) create well-defined functional zones to eliminate conflicts, (2) provide enough space that is appropriate for patient care, (3) provide necessary life support systems, (4) balance visibility and privacy, (5) provide toilet facilities, (6) reduce hospital-acquired infections and psychosis among patients, and (7) reduce patient and staff injury.

Patient Room Layout The patient room layout defines the size and location of functions and their relationships within the room. It affects how functions are performed and how patients and caregivers interface in the room. Jastremski and Harvey suggest that an ideal room should have three zones: a patient zone, a family zone, and a caregiver zone.21 Hamilton and Shepley22 defined four different zones within a patient’s room: (1) patient, (2) hygiene, (3) staff, and (4) family zones. The patient zone includes the bed, bedside, and overbed tables, and the immediate area occupied by clinicians when they provide care. The hygiene zone includes the patient’s toilet, sink, and activities associated with hygiene. The staff zone includes the area just inside or outside the entry to the patient’s room to support nursing and caregiver functions; this may include a writing surface, provisions for hand hygiene, patient information, medication, and supplies. The family zone may include seating or provisions for overnight stay, storage space, separate lighting, Internet access, and a writing surface, among others. Defining patient room in terms of what is in a patient’s view and what is not can be important. Evidence suggests that patients lying on an ICU bed are stressed when they see medical equipment, accessories, and monitors.23 Therefore it is reasonable to keep these devices away from the patient’s view, and instead put family space within the patient’s view. Architectural treatment of areas within a patient’s view also can be important because it appears that “positive distractions” such as nature can reduce stress and pain3 and that natural light can reduce analgesic use.24 Soothing color and light, natural materials, and paintings of nature may be used

in the area within the patient’s view to make his or her experience more comfortable.

Patient Room Size The need for larger patient rooms is increasing in ICUs. Advocates of infection prevention recommend that each patient room should have dedicated patient care equipment to reduce cross-infection with more resistant microbial strains. Others also recommend that each room should have a dedicated family space, with amenities to improve family integration with patient care. As medical breakthroughs and advancements occur, more technology is brought into patient rooms, and this requires more space. The increasing multidisciplinary nature of patient care in the NCCU also requires patient rooms to accommodate larger medical teams. Additional space also may be needed in patient rooms to support research and the increasing number of procedural interventions that now are performed in ICUs, such as bronchoscopy, echocardiography, and placement of external ventricular drains. The Guidelines stipulate, “Ward-type ICUs should allow at least 225 square feet of clear floor area per bed. ICUs with individual patient modules should allow at least 250 square feet per room [assuming one patient per room]. …”12 In a survey of the best-practice ICUs in the United States built between 1993 and 2003, the average size of a patient room was 250 square feet.6 However, since 2000, many best-practice ICUs have also used more than 250 square feet for patient rooms,25 suggesting that hospitals are aware of trends such as the demand for family spaces in patient rooms.

Privacy and Visibility in a Patient Room Privacy is an important factor associated with individual satisfaction in many environments including hospitals and even in moments of extreme crisis, privacy may be required to preserve individual dignity. Patient and family surveys suggest hospitals with more private rooms tend to have higher patient satisfaction rates (www.pressganey.com). There are several advantages to private rooms. First, they provide dedicated space for individualized care without disturbing other patients and can help reduce noise, improve patient sleep quality, and support staff-patient communication.21,26 Second, hospitalacquired infection rates in ICUs with private rooms are less because of improved airflow, better ventilation, and more accessible handwashing facilities.1,27-30 Finally, the private room design allows for a patient care environment with more control over optimal environmental conditions.31 However, in private rooms patient visibility is often at a stake and patients are afraid of being left alone. From a clinical viewpoint it is easier to make a case for open patient rooms in ICUs; this permits easy visual monitoring of the patient by the clinical staff that can affect patient safety. ICU staff often prefer an open ICU to see everything that happens, to readily seek help from others in a crisis, and to act immediately in groups without the constraints of walls of a private patient room.32 In private patient rooms, where glass often is used for patient visibility, measures to ensure visual and acoustic privacy of patients and their families when needed also are necessary. Hospitals often prefer breakaway glass doors because they can be closed for privacy, noise reduction, and infection control

Section I—Background

17

and still maintain maximum visibility of patients and monitors. Breakaway glass doors also allow maximum clearance to move patients in and out of the room. In an emergency, breakaway glass doors allow the room to become more open than the other doors. However, with breakaway doors closed it may be difficult to hear patient alarms, for example, ventilator alarms.

Life Support Systems in a Patient Room Easy access to the patient’s head and the ability to move a patient bed around during procedures are important in the NCCU. Traditional head wall systems that have been used since the 1970s to provide the life-support systems do not allow easy access to the patient’s head, nor do they allow clinicians to reorient the bed when needed. Headwall systems include power outlets and outlets for medical gases and vacuum on one or both sides of a patient bed. Some installations also include wall-mounted monitors and equipment for a patient’s vitals. Power columns, whether rotating or static, are now used in many ICUs to provide life support systems. Equipped with medical utilities, power outlets, and monitors, these power columns allow easy access to the patient’s head and may allow clinicians to reorient the bed. Two, instead of one, power columns—one on each side of the bed—can be installed to help increase the symmetry of functions around the patient bed. However, it can be difficult to work around power columns during a procedure. Other innovations—the ceilingmounted boom, ceiling columns, or the Draeger Ponta beam—help provide easy access and sufficient flexibility for proper patient care in NCCUs and in particular provide access to the patient’s entire body, especially to the head. These ceiling-mounted systems, however, add cost and often require additional structural support. These systems occasionally can conflict with a patient lift system in an NCCU patient room.

Toilets in a Patient Room ICU patient rooms are not required to have toilets, but there are many good reasons to have a toilet in the room for both the patient and family. Toilets in patient rooms can be used to dump and clean bedpans, which can be a major source of aerosol contaminants and infectious organisms,33 and contained systems often are used to reduce aerosols. The location, use, and design of a toilet or of other devices to eliminate waste have a significant effect on ICU design. A review of current design practice shows that toilets are placed in many different locations in relation to a patient room. Inboard toilets are on the corridor side of patient rooms; outboard are on the window side. A third option is to place the toilets of two adjacent patient rooms next to each other in a wet zone. Each location has advantages and disadvantages.6

Hospital-Acquired Infections In patient room design, air quality, single-bed patient rooms, lighting conditions, noise level, and handwashing sink are important because they can help reduce infections among patients. Most studies show that (1) private patient rooms can

18

Section I—Background

reduce cross-infection among ICU patients; (2) single-bed patient rooms with high-quality high-efficiency particulate air (HEPA) filters and with negative- or positive-pressure ventilation are more effective in preventing airborne pathogens; and (3) multibed rooms are more difficult to decontaminate and have more surfaces that act as a reservoir for pathogens.2,30,34 The 2006 American Institute of Architects Guidelines for Design and Construction of Healthcare Facilities therefore has adopted the single-bed room as the standard for all new construction in the United States.35 Infrequent handwashing by health care staff is associated with hospital-acquired infections.36 Several design factors may discourage handwashing, including: (1) poor sink location, (2) poor visibility, (3) uncomfortable sink height, and a (4) lack of redundancy and wide spatial separation of resources that are used sequentially in handwashing.36-39 There are conflicting results on how physical design influences handwashing compliance.40-43 There is, however, a consensus that a multi-strategy intervention that includes staff education, easy visual and physical access to sinks, standard sink locations in all patient rooms, comfortable sink heights, and alcohol-based dispensers can help increase handwashing compliance.36,37 A review of current design practice shows that handwashing sinks are placed at many different locations in a patient room, including: (1) locations directly outside the room entranceway, (2) immediately after the entranceway either on the footwall or on the head wall, (3) somewhere in the middle of the footwall, and (4) at the far end of the room walls. Designers and hospitals must consider the advantages and disadvantages of each of these locations.6 (For a discussion on this topic, see Rashid.6)

Psychosis Among Intensive Care Unit Patients ICU patients who are confined to bed may suffer from delirium, also known as “ICU psychosis.”44 There is growing evidence from non-ICU settings that both natural light and outdoor views can help patients maintain sensory orientation and circadian rhythm.45-49 This in turn can reduce the likelihood of delirium. Consequently, the Guidelines recommend: “Windows are an important aspect of sensory orientation, and as many rooms as possible should have windows to reinforce day/night orientation. … If windows cannot be provided in each room, an alternate option is to allow a remote view of an outside window or skylight.”12 Artificial lighting conditions that mimic the variations in natural light also can help patients maintain sensory orientation and circadian rhythm. Looking at a ceiling or a wall painted in solid colors for a long period also may contribute to patient delirium. Warm colors and paintings of nature may improve the environment. Sometimes a calendar that shows the date or a digital clock that shows date and time may help patients adjust their internal physiologic rhythm. However, the monotonous clicking sound of an analog clock can cause distress in ICU patients. ICU psychosis also may be associated with a high level of noise.50,51 Noise level in the ICU ranges from 50 to 75 dB, with peaks up to 85 dB.52 This is much higher than World Health Organization recommendations for noise levels in hospital patient rooms and units.53 Common sources of noise in

hospitals include telephones, alarms, trolleys, ice machines, paging systems, nurse shift change, staff caring for other patients, doors, staff conversations, and patients crying out or coughing.54,55 Hospital noise can be improved if proper design and management measures are in place.

Reducing Patient Falls and Fall Severity The physical environment can be a root cause for patient falls.56 Among specific interior design elements, flooring can contribute to the incidence of falls and the severity of injury from a fall.57 Patients may suffer more injuries when they fall on vinyl floors than carpeted floors.58 Subfloors also may influence the injury from falls; the risk of fracture is less for wooden than concrete subfloors.59 Several design factors can help reduce the incidence of falls including decentralized observation units next to patient rooms rather than a centralized nursing station,17 patient lifts and other transfer devices, and innovative acuity adaptable patient rooms.

Other Patient and Staff Injuries Manual lifting of ICU patients poses a high risk of injury for patients, such as dislodgement of invasive tubes and lines, shoulder dislocation, fracture of fragile bones, or being dropped.60 Skin tears and abrasions also may occur when patients are pulled up or across beds, and manual patient handling can contribute to pain in critically ill patients. Pain experienced by these patients during turning or repositioning sometimes is greater than that experienced during tracheal suctioning, tube advancement, and wound dressing changes.60 Staff also are at risk for work-related injuries when moving patients. The use of ceiling lifts can help limit risks associated with manual moving to both patient and staff. If possible, lifts should extend into the toilet room.3 If patient volumes and staffing patterns allow, ICU rooms that can flex in acuity from super-acute to step-down also may reduce patient transfers and discontinuity in care.

Staff Work Areas and Support Spaces ICUs can be stressful workplaces that can endanger the physical and mental health of the clinical staff. In the United States there is a shortage of critical care nursing staff, and the current staff is older and has a high turnover rate. Staff turnover rate in many institutions is greater in ICUs than other wards because of the stressful working conditions. ICU design, however, can help relieve staff stress by reducing unnecessary physical labor, by providing amenities, and by providing positive distractions for staff physical and mental recovery.

Staff Work and Support Area Location and Layout There are three basic nursing unit configurations: (1) centralized nursing station, (2) nursing substation, and (3) nursing observation unit. In older hospital units a centralized nursing station is generally the main component of the staff work area. Along with the patients’ records room, the central monitoring station, and staff workstations for patient charting and medical

recording, it serves as the hub of all unit functions. This type of nursing station usually has a centralized support and service area next to it that accommodates medical and supply storage, pharmacy, conference rooms, administrative offices, and other ancillary functions. In older units a centralized nursing station is where clinical management, staff interaction, mentoring, and socialization occur. However, centralized nursing stations may contribute to errors and inefficiency because of noise, crowding, and considerable walking distance from patient rooms. In hospital units built in the 1990s and 2000s, the centralized nursing station often is replaced with several decentralized observation units with direct observation of one or two rooms and located either just outside or inside the patient room. Typical functions include a work surface for patient charting, a computer to record and access patient information, and telecommunication services. There may or may not be storage spaces for medication and supplies, handwashing facilities, and image retrieval systems. It is suggested that the decentralized observation units increase efficiency, but perhaps at the cost of staff “social life.” Team workstations, sometimes distributed throughout a unit, provide spaces for interdisciplinary teamwork, mentoring, clinical management, and social functions that may not be feasible in the totally decentralized observations units. Hospitals may use different combinations of the basic nursing unit configurations in ICUs.6 The relation of the support or service areas to nursing units differs from unit to unit. In an exploratory study Zborowsky et al.61 investigated how nursing station design (i.e., centralized and decentralized nursing station layouts) affected nurses’ use of space, patient visibility, noise levels, and perceptions of the work environment. They concluded that the “hybrid” nursing design model in which decentralized nursing stations are coupled with centralized meeting rooms for consultation between staff members may strike a balance between the increase in computer duties and the ongoing need for communication and consultation that addresses the conflicting demands of technology and direct patient care. In another recent study, Hendrich et al. examined how nurses adopt distinct movement strategies based on features of unit topology and nurse assignments and observed that the spatial qualities of nurse assignments and unit layout affect nurse strategies for moving through units and affect how frequently nurses enter patient rooms and the nurse station.62 Therefore how various design features of nursing unit and support space configuration affect staff stress and effectiveness, staff communication, and task performance meets the needs of a particular ICU need to be considered.

Staff Stress and Effectiveness The location of supplies and equipment and of electronic charting impact the time spent in patient care by nurses. Nurses spend a lot of time walking, which includes the time to locate and gather supplies and equipment and to find other staff members.63,64 Studies suggest that bringing staff and supplies physically and visually closer to the patient reduces the time nurses spend walking about the unit.65,66 Decentralized nurses’ stations and supplies’ servers next to patient rooms allows nurses to spend more time in direct patient care activities.25-27

Section I—Background

19

Nurses may spend between 15% and 25% of their time in charting.67-69 Computers for charting may be found at the nursing observation units next to the patient room, in the patient room, on mobile carts, and/or at the central nursing stations away from the patient room. When charting is not done at or near the bedside nurses may spend more time away from the bedside to prepare and store charts at other locations or make more mistakes in charting because of memory lapses between the time of information collection at the bedside and putting it on the chart. Several factors contribute to staff stress in the ICU. Among them is noise that can be associated with emotional exhaustion and burnout among ICU nurses.70,71 Excessively high noise levels in healthcare settings and frequent interruptions also can interfere with work.72 For example, in a recent timeand-motion study that included 40 doctors for more than 210 hours, Westbrook et al. observed that interruptions led doctors to spend less time on the tasks they were working on and, in nearly a fifth of cases, to give up on the task.73 Patients in NCCUs often have numerous monitoring and recording devices with alarms that may also contribute to staff stress and fatigue. Nurses may become insensitive to alarms, because every alarm may not need immediate attention. Therefore they can miss that important alarm which requires immediate attention. For example, an investigation by the Boston Globe suggested that 216 deaths from 2005 to 2010 nationwide were associated with monitor alarm problems.74 Device-related incidents may be underreported and it is possible that the number of adverse events associated with alarm problems is higher. According to the Globe’s investigation, the deaths listed in the U. S. Food and Drug Administration (FDA) data were linked to problems with alarms on patient monitors that track heart functions, breathing and other vital signs. The problem typically was not a broken device. Instead, most cases occurred because medical staff did not notice an alarm or react with urgency. This includes not hearing the alarm, ignoring an alarm, mis­programming complicated monitors or forgetting to turn them on. The interface between technology and patients also can challenge NCCU staff and contribute to stress. Often, patient monitor and access lines are built up with multiple ports and, even with proper training and instructions it may difficult to sort out where to put this or that connector. ICU nurses also need to ensure that medications are compatible and so need to know how to control the stopcock. It is expected that technology innovations will help overcome some of the these interface related problems, e.g., each port can be made unique to help eliminate mixing up of lines, devices can be created to help identify incompatible drugs or integrated printers in every patient room for prescriptions may help eliminate medical errors. Together, several simple fail-safe devices may remove some of the cognitive load that contributes to stress among nurses.75 For example, Kobayashi et al. used simple human factors engineering principles to develop an experimental chart binder system with alternating color-based chart groupings, simple and prominent identifiers, and embedded visual cues.76 This was associated with a significant reduction in chart binder location problems, so contributing to safe patient care delivery. Similarly Blomkvist et al.,77 who examined the effects of changing the acoustic conditions (sound-absorbing versus sound-reflecting ceiling tiles) in a coronary ICU, observed that there were positive staff

20

Section I—Background

outcomes, including improved speech intelligibility and reduced perceived work demands, pressure and strain during the periods of improved acoustic conditions.

self-esteem, and (5) enhance positive relationships by offering love and comfort.97 In addition, families can help busy nurses and physicians.98,99

Staff Communication

Location of Family Space

Staff communication is a major variable in health care and ICU safety and several studies demonstrate that a high degree of involvement and interaction among caregivers can influence patient outcomes78 and length of stay.79 For example, Baggs et al.80 examined interdisciplinary collaboration and patient outcomes in a medical ICU and observed that patients had a 5% chance of death or readmission where nurses believed they had worked successfully with medical residents. The risk was tripled when the residents made decisions about patient care without adequate nurse consultation. The value of better communication is strongest in the very sick, complex patients.81 Research in “Magnet” hospitals also indicates that healthy collaborative relationships among caregivers are possible and appear linked to optimal patient outcome.82 A growing body of literature in several environmental design research areas including offices, laboratories, housing complexes, and acute care health facilities show that the physical design of an environment may affect communication, interaction, and/or or collaboration (For a review of the literature, see Ulrich et al.3; Rashid83; Elsbach and Pratt84; Rashid and Zimring.85) When designing staff areas in ICUs, the following should be considered: (1) Physical design can affect the quality and the quantity of interaction.86 (2) Location of people and activity and physical distance among workers may be linked to their informal communication.87 (3) Proximity of workspaces may predispose to the development of an informal group among compatible people as an outgrowth of the informal communication associated with proximity.87 (4) Spatial arrangement including the location of functions, walls, partitions, furnishings, and other barriers may affect cohesiveness and interaction among groups.88 (5) Visibility and accessibility play a powerful role in the way individuals perceive and use workplaces and communicate within.89 (6) Time spent in walking by staff may be related to time spent in patient care activities including nurse-physician interactions.17

The location of family waiting spaces in ICUs has both practical and symbolic importance. Having family members nearby often helps to shift an ICU’s culture and make families a greater part of decision making (though sometimes this also requires clinicians to create structured ways of dealing with stressed family members). Symbolically the presence of family spaces located outside the unit may suggest that families are not integrated with patient care, whereas those provided within the patient room may indicate that families are integrated with patient care. Depending on their accessibility and comfort, family spaces provided within the unit but not in the patient room can suggest the family role is in a state of flux in the unit. These impressions can, at times, be wrong. Some units may still not allow families to play an active role in patient care even with families present in the patient room. Hospitals should consider providing family spaces at several of these locations for different functions and amenities.6 (For a discussion on the possible sociologic implications of different locations of family spaces in ICUs, see Rashid, 2006.6)

Lighting Conditions and Task Performance There are few studies on the effects of lighting conditions on task performance among ICU staff. Studies in other work settings show that staff may make more mistakes in inappropriate lighting conditions, and performance on visual tasks gets better as light levels increase.90 For example, medication dispensing errors among hospital workers are more frequent when daylight hours are fewer91; these errors can be reduced at an illumination level greater than the baseline level of 45 foot candles.92 Studies in offices also indicate the importance of appropriate lighting levels for complex tasks that require excellent vision.93

Spaces for Families Many patients in the NCCU cannot communicate for themselves. Therefore family members have an important role as surrogate decision makers.94-96 Family members can also help patients (1) perform daily functions, (2) understand concerns about health, (3) foster a link to the environment, (4) reinforce

Family Waiting Area Layout Family waiting areas may be broken down into zones with varying degrees of privacy and control similar to a home. The number of ICU patient rooms, the availability of family space in the patient room, the average length of patient stay, and the types of amenities are some of the issues to consider to determine the size of a common waiting space. Waiting areas should be divided into sections to provide more intimate and quieter resting spaces and relatively busy and noisy activity spaces. Solid partitions, dividers, glass walls, or planters can separate each section according to the need of these spaces. Each section should contain comfortable chairs or sofas for the family, and resting and activity spaces should include private spaces or booths for telephone conversations. Activity spaces should include: (1) computers with Internet access that allow families to access these computers to stay up-to-date with patient status and the outside world and (2) study carrels with health care information for families. There should be a media room to separate the television from the rest of the waiting area, so families who wish to have quiet and solitude are not disturbed. Families with children should be given spaces separate from a “quiet zone” for adults only. A play area for children within the direct visual reach of the adult family members should be considered in the area designated for families with children. Some hospitals provide family sleep rooms with private bathrooms, kitchenettes, and laundry in their waiting areas for family members who must stay at the hospital for an extended period.

Family Space in Patient Rooms When possible, each patient room should include a welldefined family area to allow families to be present for shift change report, teaching sessions, care-planning discussions, and daily medical rounds. A family space within a patient’s

room provides families a more comfortable environment for activities, and being able to sleep in the patient’s room provides social support and reassurance for the patient and family members.

Furnishings and Finishes Furnishings in family areas should include comfortable seating for the family and the option of a wall-mounted fold-down bed or foldout chair-bed. Flexible furniture arrangements that allow families to change furniture layout to meet their needs are preferable, because seating arrangements that cannot be changed or chairs that cannot be moved may cause frustration among families. Unnecessary sources of visual stimulation should be minimized and wall furnishings should not be of bold patterns or colors that can be misperceived as threatening objects (e.g., bugs, animals) by patients or their families. Wall coverings and colors should be soothing and relaxing. In general, the attractiveness of the physical environment in waiting areas has been shown to be significantly associated with higher perceived quality of care, less anxiety, and higher reported positive interaction with staff.100

Access to Patients and Caregivers Family spaces should provide easy visual or physical access to patient rooms so family members can see the patient. Families also should have easy access to caregivers when needed and know when caregivers are available in the unit. For patient safety it is better for families to enter the unit through a separate entry other than the one used by service and clinical staff. Designers and hospitals need to ensure that such a system of entrances does not make interfaces among families and caregivers difficult. If the ICU design restricts family-caregiver interfaces, families may gather at places where they are likely to find caregivers.

Staff-Family Communication In ICUs, staff-family communication can provide emotional, informational, and tangible supports to family members, and can facilitate family members’ involvement in patient care. Hospitals should consider the following to help improve family-staff interactions and communication. (1) Central nursing stations and glass partitions around the staff area can limit family access to staff. (2) Decentralized nursing stations may provide more opportunities for a nurse to spend time in patient rooms. These stations also can be used during medical rounds by medical teams to retrieve patients’ records. (3) Private patient rooms and well-designed consultation rooms may provide opportunities for confidential discussions. (4) Within hallways, alcoves can provide private spaces for confidential discussions. (5) Seating that is arranged side-by-side along family space walls can discourage social interaction. (6) Private and peaceful spaces can help improve communication. (7) In dim lighting conditions and in rooms with softer floor materials, people may interact longer.101-107

Noise Reduction in Family Space Carpeting in corridors next to family waiting spaces can reduce the sound of footsteps, rolling carts, staff member conversations, and other common noises in ICUs, and

Section I—Background

21

high-performance sound-absorbing materials can be used to reduce reverberation time, sound propagation, and noise intensity levels. Storage areas, staff lounges, and utility rooms also can be located away from patient rooms and family spaces to reduce noise. Internal corridors between storage and utility rooms can help clinical and support staff members perform necessary tasks without disturbing patients or families.

Music in Family Space Sometimes music can be used to mask distressing environmental noise that cannot otherwise be eliminated. Sounds of nature accompanied by soft music also can be used in family waiting areas to calm anxious families or visitors. However, not all music can produce a desired calming effect. Music often evokes emotions and feelings that are rooted in an individual’s past experiences and personal preferences.108 Thus it is essential to respect music preferences of family members and provide them choices.

Artwork in Family Space Appropriate artwork can help reduce stress among patient families.109 The choice of artwork needs to be sensitive to culture, religion, the specific geographic area, and the interior design scheme. Hospitals should consider developing systems that allow artwork to be changed by the patient family as easily as changing television channels. Because art varies enormously in subject matter and style, not all artwork is suitable for highstress health care spaces.

Lighting in Family Space Appropriate lighting can influence mood or create a relaxed ambience. Therefore attention should be given to make natural light available in all family spaces in the unit. When the family space is within the patient room, it is necessary to make sure that the intensity of natural light is comfortable to patients. The use of slightly tinted or reflective glass can reduce glare and heat production from sunlight. Vertical blinds and other window treatments can be used to adjust light intensity as desired by the patient. For artificial light in family spaces, it is important to consider multiple lighting options that can be controlled by the family when appropriate. Where natural light is not an option (e.g., older ICUs), full-spectrum fluorescent lighting can be used for comparable benefits. A dynamic lighting solution that allows the color and temperature levels to be changed according to the time of day may be suitable for a patient room or family space.

Odors and Aromas Pleasing aromas can help reduce blood pressure, slow the rate of respiration, lower pain perception levels, improve the immune system, and help increase a sense of well-being among family members who are under severe mental and physical stress. In contrast, odors (“negative smells”) may stimulate anxiety, fear, and stress.110 Hospitals, particularly ICUs, are well known for their unpleasant odors or chemical smells. If possible, strong-smelling cleaning agents should be avoided near family areas. Aroma should be used with caution in ICU family areas.

22

Section I—Background

Nature, Spirituality, and Religion Nature can have a positive effect on physical and emotional well-being; hence it is preferable to design family areas with windows to the outside. If possible these spaces need to be close to hospital gardens with plants, water, and other natural objects. When family spaces do not have a view of or access to nature, nature may be brought into the unit (e.g., potted plants, sound of nature, and nature-related artwork). Hospitals also should consider outdoor labyrinths in gardens as a focus for spirituality.111-113 A working knowledge of common cultural and religious needs of patients and families is required to design family spaces. Sometimes a focus group with local spiritual and ethnic leaders before ICU design or redesign may help identify common design concerns of these groups. It may help families to have a community room for tai chi, yoga, and other spiritual modalities and a chapel or a sanctuary close to the ICU where religious services can take place. Sometimes these places are the only quiet refuge for families from the chaos of the hospital. Hospitals should also provide religious books, inspirational texts, and texts on grief and coping written in multiple languages in the chapel or the community room, and consider having space for common religious items used by people of different faiths (e.g., rosaries, crucifixes, and holy water for Catholic users; clean clothing, prayer rugs, and compasses for Muslim users; Sabbath kits for Jewish users) in the chapel or the community room. When building a new unit, a tile marker could be inserted in all family spaces and patient rooms to signify the direction of prayer.

high-quality care. Consequently a larger NCCU was proposed, initially to appeal to the bottom line: if the unit had more beds and could attract more patients, it could generate more revenue and, most important, fulfill staff ’s mission as the hospital of last resort for many of these patients with complex brain injury. In 2007 Emory Medical Center was in the early phase of planning a replacement hospital, and the administration did not want to spend a lot of money on a new ICU that would be demolished in 5 years when the new hospital opened. Early on, the new NCCU was described as the “throwaway” NCCU, and the hospital agreed to meet the state and federal requirements so that it could quickly open to meet the immediate ICU bed shortages. The initial design was for a 24-bed ICU with a “track” around it; visitors would enter the patient rooms from the back so as not to disrupt the central area used by the doctors and nurses. The rooms measured 200 square feet, as required by the state of Georgia, with no dedicated space for family members. This design essentially duplicated the current ICUs at that time. In these units the typical patient room was so crowded with specialized equipment that it was difficult to get to the patient without tripping over cords or knocking out invasive lines Figure 3.1 shows a comparison of the ICU before and after construction. It took time to respond to an emergency and to maintain sterility was near impossible. During patient care rounds there was little room for the ICU team’s numerous members in crowded rooms and hallways. In the central areas, nurses were crowded around desks with charts spread all over tables; this increased the potential for mistakes in documentation, record keeping, and medication administration. Families were limited to dark, common spaces

Case Study: Emory University Hospital Neuroscience Critical Care Unit In 2005 an architecture firm that worked with the Emory Hospital in Atlanta, Georgia, presented a design to replace the NCCU. The unit’s medical director (senior author Owen Samuels, MD) was concerned that the intended design might not address some of the issues described earlier that could affect patient outcomes. Dr. Samuels approached Craig Zimring of Georgia Institute of Technology School of Architecture about published evidence on the effects of ICU design. Dr. Zimring agreed to have his graduate students, under the guidance of Dr. Rashid, search the literature and develop design concepts based on research findings. This exercise ultimately led to an interdisciplinary design charrette with the architectural firm and a revised NCCU design that included the design implications from the literature. This section reviews how the NCCU was designed primarily from the perspective of the medical director.

Evidence for a Better Way Neurocritical care admissions at Emory increased from 587 patients in 1999 to more than 1400 patients in 2007. This rapid growth meant that in 2007 the existing NCCU was out of beds and patients with severe neurologic disorders were cared for in three geographically separated small units (two seven-bed units, and one nine-bed unit). This approach was inefficient and compromised patient safety and delivery of

Fig. 3.1  Top panel, Crowded initial conditions. Bottom panel, Completed project.

Section I—Background

in the outside hall away from patients and were restricted to visiting during morning rounds. Discussions between doctor and families, including those about prognosis, brain death, organ donation, and end-of-life concerns took place either in the cluttered patient rooms or in public hallways with no privacy. The new proposed space promised little more than some new converter chairs. There was concern that the proposed design was not ideal. To convince the administration to pursue a completely new concept, designers focused on key people: the chief nursing officer for neurosciences and the chief executive officer of Emory Healthcare. The design team told them that current ICUs were uncomfortable for families, the space was inherently dangerous with a large potential for avoidable medical mistakes that was largely unrecognized, and staff burnout was common. Doctors and nurses make clinical decisions based in part on evidence from the literature. Shouldn’t such evidence also inform how hospitals and ICUs are designed? Although research in ICU design is an emerging field, there is a large body of scientific evidence on how the physical environment affects patient outcome, staff effectiveness, family well-being, and costs. The team therefore proposed a new design founded on an evidence-based approach for patient and familycentered care supported by a healing environment but flexible enough that it could continue to change in the future. Developers were confident that an improved design could reduce staff stress and enhance performance. As an academic institution, the team also wanted to study the effect of a new type of ICU.

Emphasis About Family Involvement Many factors other than technologic advancement can contribute to patient outcome. When the ICU was designed, the team had several goals or “design drivers” (Table 3.1) in mind, with accompanying measurable outcome variables to be tracked. A primary driver for the new ICU was family support. It was proposed to eliminate signs that restricted family visitation, and the team was tempted to replace the sign “Physician Rounds in Progress” with “Physician Rounds in Progress, Family Presence Encouraged.” The plan included a family zone located within the patient’s room, as the “family studio,” a children’s area located immediately outside the ICU, family lockers and showers, clothing washers and dryers, and a quiet room for families and close friends. Outcome measures to be collected included patient and family satisfaction scores, hospital-acquired infections, nursing retention rates, ICU length of stay, organ donation success, and number of litigation filings. This family-centered approach was to be balanced with the ability to turn the patient ICU room into a “minioperating room” to reduce patient transfers and support more procedures at the bedside. Other important design drivers were reduction of medical errors; increased patient safety, and staff satisfaction. Each goal had measurable outcomes to be tracked.

A Dynamic Design Process To determine factors such as patient room size and configuration and the design of family spaces, the design team analyzed best practices of the prior 10 years’ winners of the ICU Design Citation Award. The Society of Critical Care Medicine, the

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Table 3.1  Project Goals and Metrics for ICUD Design Outcome Measures

Design Drivers

Design Response

Support families

Family zone in patient room Kid’s room Lockers and showers Family quiet room

Greater satisfaction on Press-Ganey and Emory ICU surveys Fewer complaints and litigation

Support more procedures at the bedside

Medical gas booms Larger patient zone Improved ergonomics

Fewer patient transfer complications and lower costs Fewer errors Shorter stays More time spent by the ICU staff in the ICU area

Reduce infection

Numerous rubs and handwashing stations

Improved handwashing compliance Lower MSRA and hospitalacquired infection rates

Reduce medical errors and increase patient safety

Improved ceiling tiles Carpet where appropriate Charting niches Zoned caregiver area

Fewer medical and medication errors Less litigation Reduced self-extubation Decreased falls and injuries related to patients leaving beds

ICU, Intensive care unit; MRSA, methicillin-resistant Staphylococcus aureus.

American Association of Critical Care Nurses, and the American Institute of Architects jointly give this award. Next the team partnered with the division of health care design at Georgia Institute of Technology’s College of Architecture, led by an environmental psychologist who specializes in the use of architectural design as a healing tool. Several charrette sessions were held, which included key stakeholders from Emory, the architects (HKS, Inc.), and Georgia Tech. A mock-up of the proposed ICU that included nurses’ station, patient rooms, wall-to-ceiling booms, and family areas was created. Several procedures, including resuscitation, intubation, intracranial monitor implantation, nursing shiftchange, and interactions between families and staff were enacted through role-playing and recorded by videographers for later analysis. A mock-up of the family studio allowed analysis of functionality and family flow. Family members of patients who had recently been discharged from or were still in the ICU were involved with the unit’s design throughout the process. As developers learned from such experiences, the design of the ICU was altered even as construction was under way. It was originally planned to distribute the nurses’ stations throughout the unit, but later it was decided to keep a communal area as well, because the team realized that nurses and

24

Section I—Background

2.6m (8’7”) 1.5m (4’9”)

8.5m (28’0”) 5.3m (17’3”)

1.5m (4’9”) 1.6m (5’4”)

2.9m (9’5”) Fig. 3.2  Illustration of two adjacent ICU patient rooms (shaded blue). The nurse’s station outside the patient rooms and the adjoining family areas (shaded green) also are visible. Room dimensions are provided.

Fig. 3.3  Patient room, view from above.

doctors at times need to be in the same area to better support one another.

Proposal Becomes Reality The new NCCU opened February 2007. The rooms are between 345 and 450 square feet (Fig. 3.2) whereas the old rooms were 120 to 200 square feet. Pneumatic booms lift equipment off the floor. This limits clutter and allows rapid 360-degree access to the patient’s head in emergency situations. The beds and doors are configured so that patients who are awake have a direct line of sight to the nurses’ station or a bay window. Each room is a suite that consists of the patient room and a family area separated by a curved wall with large glass-block windows that lets in natural light (Fig. 3.3). The

4.5m (15’)

9.1m (30’)

family studio has a table, chairs, comfortable sleeping arrangements, flat-screen television, wireless Internet access, music, and a white-noise system to blunt surrounding noises. The new unit allows staff to do things that could not be done before including hold a private conversation with a family member when visiting a patient. Family members can leave the room for some respite and still be just a stone’s throw away from their loved one. The following case that bridged the transition between the old and new NCCU illustrates some of the advantages of the new family-centered unit. David was a 31-year-old computer programmer, the father of a 3-year-old girl, and about to be married. He was admitted to the NCCU with a grade IV subarachnoid hemorrhage and was in the old ICU for 4 days, and then moved to the new NCCU when it opened. David later developed neurogenic pulmonary edema, severe pneumonia, acute respiratory distress syndrome, and heart failure and required induced coma for intracranial hypertension. He subsequently had an aneurysm rebleed and progressed to brain death and his family decided to donate his organs. His family, parents, and his fiancée kept a rotating vigil 24 hours a day. They always felt they were in the way in the old ICU, whereas they felt welcome in the new facility. The family often stood at David’s bedside as the team explained the purpose of the complex monitors and instruments and did not have to leave the bedside for discussions about brain death or organ donation. The mother said, “This was our home for a month, and it got so that the nurses could tell when we needed a hug.”114 David’s father said, “No one ever misled us or told us anything but the truth … and most importantly, we were there for everything.”115 Hospital staff did everything they could for David, and nothing could change his ultimate outcome. But the way

Section I—Background

someone dies is important. The circumstances of how David was treated probably helped allow the family to donate his organs and better come to terms with his death. They later generously donated their time to help the NCCU develop the family-centered approach by participating in many discussions about their experiences.

Family-Centered Units Pose Challenges The concept of care around the patient and their family makes sense. However, there is resistance to it, even from the most dedicated health care workers. The team at Emory spent about a year and a half preparing for family-centered care; starting the process was the real challenge. In a unit that is designed for both patients and their families, how does one care for patients and their families simultaneously? There are several challenges: Team rounding: Doctors and nurses may be apprehensive about inviting families to rounds. Training doctors and nurses with families present is a real paradigm shift and raises many controversial issues.  Nurses in view: Imagine a nurse operating six or seven intravenous pumps and trying to figure out medications while having a family member—or three or four members—continuously present.  Urgent or frightening treatment: How does staff deal with resuscitation? What if the family is right by the bedside? Should they be asked to leave? What kind of support do they need? 

The authors do not have all the answers to such problems but are currently studying them to figure out best practices.

Outcomes Emory’s NCCU won the 2008 ICU Design Citation Award from the Society of Critical Care Medicine, the American Association of Critical Care Nurses, and the American Institute of Architects Academy on Architecture for Health. The authors have started to look at outcomes associated with the NCCU. Patient and staff satisfaction have increased, according to self-assessments. Most recent Press-Ganey Family Satisfaction scores indicate greater than 85% overall satisfaction. Other variables of quality care benchmarks include significant decrease in pneumonia rates and central venous line bloodstream infections, increased compliance with critical care pathways, increased nursing retention, and a trend toward decreased medical legal litigation.

Conclusion This chapter has briefly discussed environmental design criteria for the ICU, the patient room, staff and support areas, and family areas of ICUs to help improve patient, staff, and family outcomes. These processes can influence patient outcomes and have an effect on how staff monitor individual patients and overall outcomes and quality in the ICU. Although some of these issues will likely persist for the foreseeable future, others are being addressed by technical and process changes. For example, as manufacturers of medical equipment and supplies continue to merge and consolidate and develop

25

standardized protocols for integration of medical equipment and devices, many interface problems related to technology that we see in ICUs today may be eliminated.

References 1. Bartley J, Streifel AJ. Design of the environment of care for safety of patients and personnel: does form follow function or vice versa in the intensive care unit? Crit Care Med 2010;38(Suppl. 8):388–98. 2. Ulrich RS, Zimring C, Joseph A, et al. The role of the physical environment in the hospital of the 21st century: a once-in-a-lifetime opportunity. Concord, CA: The Center for Health Design; 2004. 3. Ulrich RS, Zimring C, Zhu X, et al. A review of the research literature on evidence-based healthcare design. HERD 2008;1(3):61–125. 4. Zimring C, Ulrich RS, Joseph A, et al. The environment’s impact on safety. In: Marberry SO, editor. Improving healthcare with better building design. Chicago: Health Administration Press; 2006. p. 63–81. 5. Cai H, Do EY-L, Zimring CM. Extended linkography and distance graph in design evaluation: an empirical study of the dual effects of inspiration sources in creative design. Design Studies 2010;31(2):146–68. 6. Rashid M. A decade of adult intensive care unit design: a study of the physical design features of the best-practice examples. Crit Care Nurs Quart 2006;29(4):282–311. 7. Kohlenberg A, Schwab F, Behnke M, et al. Screening and control of methicillin-resistant Staphylococcus aureus in 186 intensive care units: different situations and individual solutions. Critical Care 2011;15:R285. 8. Vincent JL, Bihari DJ, Suter PM, et al. The prevalence of nosocomial infection in intensive care units in Europe: results of the European Prevalence of Infection in Intensive Care (EPIC) Study. EPIC International Advisory Committee. JAMA 1995;274(8):639–44. 9. Akansel N, Kaymakçi S. Effects of intensive care unit noise on patients: a study on coronary artery bypass graft surgery patients. J Clin Nurs 2008;17(12):1581−90. 10. Piergeorge AR, Ceserano FL, Casanova DM. Designing the critical care unit: a multidisciplinary approach. Crit Care Med 1983;11(7):541–45. 11. Society of Critical Care Medicine (SCCM). NIH consensus development conference on critical care medicine. Crit Care Med 1983;11:466–9. 12. Society of Critical Care Medicine (SCCM). Guidelines for intensive care unit design. Crit Care Med 1995;23(3):582–8. 13. Stoddard JC. Design, staffing and equipment requirements for an intensive care unit. Int Anesthesiol Clin 1981;19(2):77–95. 14. Hamilton DK, editor. ICU 2010: ICU design for the future, a critical care design symposium. Houston: Center for Innovation in Health Facilities; 2000. 15. Carthey J. Reinterpreting the hospital corridor: “wasted space” or essential for quality multidisciplinary clinical care? HERD 2008;2(1):17–29. 16. National Fire Protection Association. Section 19.2.5.7.2.3. Quincy, MA; 2012. 17. Hendrich A. Case study: the impact of acuity adaptable rooms on future designs, bottlenecks and hospital capacity. Paper presented at the Impact Conference on Optimizing the Physical Space for Improved Outcomes, Satisfaction and the Bottom Line, Atlanta, 2003. 18. Hendrich A, Fay J, Sorrells A. Effects of acuity-adaptable rooms on flow of patients and delivery of care. Am J Crit Care 2004;13(1):35–45. 19. Hendrich A, Lee N. Intra-unit patient transports: time, motion, and cost impact on hospital efficiency. Nurs Econ 2005;23(4):157–64. 20. Cook RI, Render M, Woods DD. Gaps in the continuity of care and progress on patient safety. BMJ 2000;320(7237):791–4. 21. Jastremski CA, Harvey M. Making changes to improve the intensive care unit experience for patients and their families. New Horiz 1998;6(1):99–109. 22. Hamilton DK, Shepley MM. Design for critical care: an evidence based approach. Oxford: Elsevier Ltd; 2010. 23. Tanja-Dijkstra K. The impact of bedside technology on patients’ well being. Health Environments Research & Design Journal 2011;5(1):43−51. 24. Walch JM, Rabin BS, Day R, et al. The effect of sunlight on post-operative analgesic medication usage: a prospective study of spinal surgery patients. Psychosom Med 2005;67(1):156–63. 25. Cadenhead C, Anderson D. Critical care unit design, the winners and future trends: an investigative study. World Health Design Journal 2009;2:72–7. 26. Chaudhury H, Mahmood A, Valente M. Advantages and disadvantages of single-versus multiple-occupancy rooms in acute care environments: a review and analysis of the literature. Enviro Behav 2005;37:760–86. 27. Levin PD, Golovanevski M, Moses AE, et al. Improved ICU design reduces acquisition of antibiotic resistant bacteria: a quasi-experimental observational study. Critical Care 2011;15:R21.

26

Section I—Background

28. Maki DG. Nosocomial infection in the intensive care unit. In: Parillo JE, Bone RC, editors. Critical care medicine-principles of diagnosis and management. St. Louis: Mosby; 1995. p. 893–954. 29. Shirani KZ, McManus AT, Vaughan GM, et al. Effects of environment on infection in burn patients. Arch Surg 1986;121(1):31–6. 30. Teltsch DY, Hanley J, Loo V, et al. Infection acquisition following intensive care unit room privatization. Arch Intern Med 2011;171(1):32–8. 31. Van Enk RA, Steinberg F. Comparison of private room with multiple-bed ward neonatal intensive care unit environments. Health Environments Research & Design Journal 2011;5(1):52–63. 32. France DJ, Throop P, Walczyk B, et al. Does patient-centered design guarantee patient safety? Using human factors engineering to find a balance between provider and patient needs. J Patient Saf 2005;1(3):145–53. 33. Burrington M, Architects WHR. An alternative method for human waste disposal in critical care. In Hamilton DK, editor. ICU 2010: ICU design for the future, a critical care design symposium. Houston: Center for Innovation in Health Facilities; 2000. 34. Mullin B, Rouget C, Clément C, et al. Association of private isolation rooms with ventilator-associated Acinetobacter baumanii pneumonia in a surgical intensive-care unit. Infection Control and Hospital Epidemiology 1997;18(7):499–503. 35. Facilities Guidelines Institute. Guidelines for design and construction of health care facilities. Washington, DC: The American Institute of Architects; 2006. 36. Joseph A. The impact of the environment on infections in healthcare facilities. Concord, CA: The Center for Health Design; 2006. 37. Boyce, J. Antiseptic technology: access, affordability, and acceptance. Emerging Infectious Diseases 2001;7(2):231–3. 38. Lankford MG, Zembower TR, Trick WE, et al. Influence of role models and hospital design on hand hygiene of healthcare workers. Emergency Infectious Diseases 2003;9(2):217–23. 39. Larson E, Albrecht S, O’Keefe M. Hand hygiene behavior in a pediatric emergency department and a pediatric intensive care unit: comparison of use of 2 dispenser systems. American Journal of Critical Care 2005;14(4):304–11.

40. Kaplan LM, McGuckin M. Increasing handwashing compliance with more accessible sinks. Infection Control 1986;7(8):408–10. 41. Vernon MO, Trick WE, Welbel SF, et al. Adherence with hand hygiene: does number of sinks matter? Infection control and hospital epidemiology 2003;24(3):224–5. 42. Vietri NJ, Dooley DP, Davis CE, et al. The effect of moving to a new hospital facility on the prevalence of methicillin-resistant Staphylococcus aureus. American Journal of Infection Control 2004;32(5):262–7. 43. Trick W, Vernon M, Welbe LS, et al. Multicenter intervention program to increase adherence to hand hygiene recommendations and glove use and to reduce the incidence of antimicrobial resistance. Infection Control and Hospital Epidemiology 2007;28(1):42–9. 44. Dyson M. Intensive care unit psychosis, the therapeutic nurse-patient relationship and the influence of the intensive care setting: analyses of interrelating factors. Journal of Clinical Nursing 1999;8:284–90. 45. Beauchemin KM, Hays P. Sunny hospital rooms expedite recovery from severe and refractory depressions. Journal of Affective 1996;40(1-2): 49–51. 46. Benedetti F, Colombo C, Barbini B, et al. Morning sunlight reduces length of hospitalization in bipolar depression. Journal of Affective Disorders 2001;62(3):221–3. 47. Lewy AJ, Bauer VK, Cutler NL, et al. Morning vs. evening light treatment of patients with winter depression. Archives of General Psychiatry 1998;55(10):890–6. 48. Ulrich RS. View through a window may influence recovery from surgery. Science 1984;224(4647):420–1. 49. Ulrich RS. Effects of interior design on wellness: theory and recent scientific research. Journal of Health Care Design 1991;3:97–109. 50. Gelling L. Causes of ICU psychosis: the environmental factors. Nursing in Critical Care 1999;4:22–6. A complete list of references for this chapter can be found online at www.expertconsult.com.

Section I—Background 26.e1



References 1. Bartley J, Streifel AJ. Design of the environment of care for safety of patients and personnel: does form follow function or vice versa in the intensive care unit? Crit Care Med 2010;38(Suppl. 8):388–98. 2. Ulrich RS, Zimring C, Joseph A, et al. The role of the physical environment in the hospital of the 21st century: a once-in-a-lifetime opportunity. Concord, CA: The Center for Health Design; 2004. 3. Ulrich RS, Zimring C, Zhu X, et al. A review of the research literature on evidence-based healthcare design. HERD 2008;1(3):61–125. 4. Zimring C, Ulrich RS, Joseph A, et al. The environment’s impact on safety. In: Marberry SO, editor. Improving healthcare with better building design. Chicago: Health Administration Press; 2006. p. 63–81. 5. Cai H, Do EY-L, Zimring CM. Extended linkography and distance graph in design evaluation: an empirical study of the dual effects of inspiration sources in creative design. Design Studies 2010;31(2):146–68. 6. Rashid M. A decade of adult intensive care unit design: a study of the physical design features of the best-practice examples. Crit Care Nurs Quart 2006;29(4):282–311. 7. Kohlenberg A, Schwab F, Behnke M, et al. Screening and control of methicillin-resistant Staphylococcus aureus in 186 intensive care units: different situations and individual solutions. Critical Care 2011;15:R285. 8. Vincent JL, Bihari DJ, Suter PM, et al. The prevalence of nosocomial infection in intensive care units in Europe: results of the European Prevalence of Infection in Intensive Care (EPIC) Study. EPIC International Advisory Committee. JAMA 1995;274(8):639–44. 9. Akansel N, Kaymakçi S. Effects of intensive care unit noise on patients: a study on coronary artery bypass graft surgery patients. J Clin Nurs 2008;17(12):1581−90. 10. Piergeorge AR, Ceserano FL, Casanova DM. Designing the critical care unit: a multidisciplinary approach. Crit Care Med 1983;11(7):541–45. 11. Society of Critical Care Medicine (SCCM). NIH consensus development conference on critical care medicine. Crit Care Med 1983;11:466–9. 12. Society of Critical Care Medicine (SCCM). Guidelines for intensive care unit design. Crit Care Med 1995;23(3):582–8. 13. Stoddard JC. Design, staffing and equipment requirements for an intensive care unit. Int Anesthesiol Clin 1981;19(2):77–95. 14. Hamilton DK, editor. ICU 2010: ICU design for the future, a critical care design symposium. Houston: Center for Innovation in Health Facilities; 2000. 15. Carthey J. Reinterpreting the hospital corridor: “wasted space” or essential for quality multidisciplinary clinical care? HERD 2008;2(1):17–29. 16. National Fire Protection Association. Section 19.2.5.7.2.3. Quincy, MA; 2012. 17. Hendrich A. Case study: the impact of acuity adaptable rooms on future designs, bottlenecks and hospital capacity. Paper presented at the Impact Conference on Optimizing the Physical Space for Improved Outcomes, Satisfaction and the Bottom Line, Atlanta, 2003. 18. Hendrich A, Fay J, Sorrells A. Effects of acuity-adaptable rooms on flow of patients and delivery of care. Am J Crit Care 2004;13(1):35–45. 19. Hendrich A, Lee N. Intra-unit patient transports: time, motion, and cost impact on hospital efficiency. Nurs Econ 2005;23(4):157–64. 20. Cook RI, Render M, Woods DD. Gaps in the continuity of care and progress on patient safety. BMJ 2000;320(7237):791–4. 21. Jastremski CA, Harvey M. Making changes to improve the intensive care unit experience for patients and their families. New Horiz 1998;6(1): 99–109. 22. Hamilton DK, Shepley MM. Design for critical care: an evidence based approach. Oxford: Elsevier Ltd; 2010. 23. Tanja-Dijkstra K. The impact of bedside technology on patients’ well being. Health Environments Research & Design Journal 2011;5(1):43−51. 24. Walch JM, Rabin BS, Day R, et al. The effect of sunlight on post-operative analgesic medication usage: a prospective study of spinal surgery patients. Psychosom Med 2005;67(1):156–63. 25. Cadenhead C, Anderson D. Critical care unit design, the winners and future trends: an investigative study. World Health Design Journal 2009;2:72–7. 26. Chaudhury H, Mahmood A, Valente M. Advantages and disadvantages of single-versus multiple-occupancy rooms in acute care environments: a review and analysis of the literature. Enviro Behav 2005;37:760–86. 27. Levin PD, Golovanevski M, Moses AE, et al. Improved ICU design reduces acquisition of antibiotic resistant bacteria: a quasi-experimental observational study. Critical Care 2011;15:R21. 28. Maki DG. Nosocomial infection in the intensive care unit. In: Parillo JE, Bone RC, editors. Critical care medicine-principles of diagnosis and management. St. Louis: Mosby; 1995. p. 893–954.

29. Shirani KZ, McManus AT, Vaughan GM, et al. Effects of environment on infection in burn patients. Arch Surg 1986;121(1):31–6. 30. Teltsch DY, Hanley J, Loo V, et al. Infection acquisition following intensive care unit room privatization. Arch Intern Med 2011;171(1):32–8. 31. Van Enk RA, Steinberg F. Comparison of private room with multiple-bed ward neonatal intensive care unit environments. Health Environments Research & Design Journal 2011;5(1):52–63. 32. France DJ, Throop P, Walczyk B, et al. Does patient-centered design guarantee patient safety?: Using human factors engineering to find a balance between provider and patient needs. J Patient Saf 2005;1(3): 145–53. 33. Burrington M, Architects WHR. An alternative method for human waste disposal in critical care. In Hamilton DK, editor. ICU 2010: ICU design for the future, a critical care design symposium. Houston: Center for Innovation in Health Facilities; 2000. 34. Mullin B, Rouget C, Clément C, et al. Association of private isolation rooms with ventilator-associated Acinetobacter baumanii pneumonia in a surgical intensive-care unit. Infection Control and Hospital Epidemiology 1997;18(7):499–503. 35. Facilities Guidelines Institute. Guidelines for design and construction of health care facilities. Washington, DC: The American Institute of Architects; 2006. 36. Joseph A. The impact of the environment on infections in healthcare facilities. Concord, CA: The Center for Health Design; 2006. 37. Boyce, J. Antiseptic technology: access, affordability, and acceptance. Emerging Infectious Diseases 2001;7(2):231–3. 38. Lankford MG, Zembower TR, Trick WE, et al. Influence of role models and hospital design on hand hygiene of healthcare workers. Emergency Infectious Diseases 2003;9(2):217–23. 39. Larson E, Albrecht S, O’Keefe M. Hand hygiene behavior in a pediatric emergency department and a pediatric intensive care unit: comparison of use of 2 dispenser systems. American Journal of Critical Care 2005;14(4):304–11. 40. Kaplan LM, McGuckin M. Increasing handwashing compliance with more accessible sinks. Infection Control 1986;7(8):408–10. 41. Vernon MO, Trick WE, Welbel SF, et al. Adherence with hand hygiene: does number of sinks matter? Infection control and hospital epidemiology 2003;24(3):224–5. 42. Vietri NJ, Dooley DP, Davis CE, et al. The effect of moving to a new hospital facility on the prevalence of methicillin-resistant Staphylococcus aureus. American Journal of Infection Control 2004;32(5):262–7. 43. Trick W, Vernon M, Welbe LS, et al. Multicenter intervention program to increase adherence to hand hygiene recommendations and glove use and to reduce the incidence of antimicrobial resistance. Infection Control and Hospital Epidemiology 2007;28(1):42–9. 44. Dyson M. Intensive care unit psychosis, the therapeutic nurse-patient relationship and the influence of the intensive care setting: analyses of interrelating factors. Journal of Clinical Nursing 1999; 8:284–90. 45. Beauchemin KM, Hays P. Sunny hospital rooms expedite recovery from severe and refractory depressions. Journal of Affective 1996;40(1-2):49–51. 46. Benedetti F, Colombo C, Barbini B, et al. Morning sunlight reduces length of hospitalization in bipolar depression. Journal of Affective Disorders 2001;62(3):221–3. 47. Lewy AJ, Bauer VK, Cutler NL, et al. Morning vs. evening light treatment of patients with winter depression. Archives of General Psychiatry 1998;55(10):890–6. 48. Ulrich RS. View through a window may influence recovery from surgery. Science 1984;224(4647):420–1. 49. Ulrich RS. Effects of interior design on wellness: theory and recent scientific research. Journal of Health Care Design 1991;3:97–109. 50. Gelling L. Causes of ICU psychosis: the environmental factors. Nursing in Critical Care 1999;4:22–6. 51. Hughes J. Hallucinations following cardiac surgery in a pediatric intensive care unit. Intensive and Critical Care Nursing 1994;10:209–11. 52. Gabor J, Cooper A, Crombach S, et al. Contribution of the intensive care unit environment to sleep disruption in mechanically ventilated patients and healthy subjects. American Journal of Respiratory and Critical Care Medicine 2003;167:708–15. 53. Busch-Vishniac I, West J, Barnhill C, et al. Noise levels in Johns Hopkins Hospital. Journal of the Acoustical Society of America 2005;118: 3629–1645. 54. Cropp A, Woods L, Raney D. Name that tone: the proliferation of alarms in the intensive care unit. Chest 1994;105:1217–20. 55. Ulrich RS, Lawson B, Martinez M. Exploring the patient environment: an NHS estates workshop. London: The Stationery Office; 2003.

26.e2 Section I—Background 56. Joint Commission on Accreditation of Healthcare Organizations. Root causes of patient falls. Sentinel event statistics [Graph] 2006 [cited 2007 7/22/07]; Available from: http://www.jointcommission.org/NR/rdonlyres/ FA5A080F-C259-47CC-AAC8-BAC3F5C37D84/0/se_rc_patient_falls.jpg 57. Drahota A, Gal D, Windsor J. Flooring as an intervention to reduce injuries from falls in healthcare settings. Quality in Ageing and Older Adults 2007;8(1):3–9. 58. Healey F. Does flooring type affect risk of injury in older in-patients? Nursing Times 1994;90(27):40–1. 59. Simpson AH, Lamb S, Roberts PJ, et al. Does the type of flooring affect the risk of hip fracture? Age and Ageing 2004;33(3):242–6. 60. Nelson AL, Matz M, Chen F, et al. Development and evaluation of a multifaceted ergonomics program to prevent injuries associated with patient handling tasks. Journal of International Nursing Studies 2006;43: 717–33. 61. Zborowsky T, Bunker-Hellmich L, Morelli A, et al. Centralized vs. decentralized nursing stations: effects on nurses’ functional use of space and work environment. Health Environments Research & Design Journal 2010;3(4):19−42. 62. Hendrich A, Chow MP, Bafna S, et al. Unit-related factors that affect nursing time with patients: spatial analysis of the time and motion study. Health Environments Research & Design Journal 2009;2(2):5–20. 63. Burgio L, Engel B, Hawkins A, et al. A descriptive analysis of nursing staff behaviors in a teaching nursing home: differences among NAs, LPNs and RNs. The Gerontologist 1990;30(1):107–12. 64. Tucker A, Spear S. Operational failures and interruptions in hospital nursing. Health Services Research 2006;41(3):643–62. 65. Shepley MM. Predesign and postoccupancy analysis of staff behavior in a neonatal intensive care unit. Children’s Health Care 2002;31(3):237–53. 66. Shepley MM, Davies K. Nursing unit configuration and its relationship to noise and nurse walking behavior: an AIDS/HIV unit case study. AIA Academy Journal 2003. Available from: http://www.aia.org/aah/journal/ 0401/article0404.asp. 67. Deane D, McElroy MJ, Alden S. Documentation: meeting requirements while maximizing productivity. Nursing Economics 1986;4(4):174–7. 68. Pierpont GL, Thilgen D. Effect of computerized charting on nursing activity in intensive care. Critical Care Medicine 1995;23(6):1067–73. 69. Quist BD. Work sampling nursing units. Nursing Management 1992;23(9): 50–1. 70. Morrison W, Haas E, Shaffner D, et al. Noise stress and annoyance in a pediatric intensive care unit. Critical Care Medicine 2003;31(1):35–7. 71. Topf M, Dillon E. Noise-induced stress as a predictor of burnout in critical care nurses. Heart and Lung 1988;17:247–50. 72. Bayo MV, Garcia AM, Garcia A. Noise levels in an urban hospital and workers’ subjective responses. Archives of Environmental Health 1995; 50(3):247–51. 73. Westbrook JI, Coiera E, Dunsmuir WT, et al. The impact of interruptions on clinical task completion. Qual Saf Health Care 2010;19(4):284−9. 74. Boston Globe. “Patient alarms often unheard, unheeded.” Feb. 11, 2011. Available at: http://www.boston.com/lifestyle/health/articles/2011/02/13/ patient_alarms_often_unheard_unheeded/ (accessed Feb. 29, 2012). 75. Rashid M. Technology and the future of ICU design. Critical Care Nursing Quarterly 2011;34(4):332–60. 76. Kobayashi L, Boss RM , Gibbs FJ, et al. Color-coding and human factors engineering to improve patient safety characteristics of paper-based emergency department clinical documentation. Health Environments Research & Design Journal 2011;4(4):79−88. 77. Blomkvist V, Eriksen C, Theorell T, et al. Acoustics and psychosocial environment in intensive coronary care. Occupational and Environmental Medicine 2005;62(3):1–8. 78. Knaus WA, Draper EA, Wagner DP, et al. An evaluation of outcome from intensive care in major medical centers. Ann Intern Med 1986;104:410–8. 79. Shortell SM, Zimmerman JE, Rousseau DM, et al. The performance of intensive care units: does good management make a difference? Medical Care 1994;32(5):508–25. 80. Baggs JG, Ryan SA, Phelps CE, et al. The association between interdisciplinary collaboration and patient outcomes in a medical/intensive care unit. Heart and Lung 1992;21(1):18–24. 81. Baggs JG, Schmitt M, Mushlin A, et al. Association between nurse-physician collaboration and patient outcomes in three intensive care units. Critical Care Medicine 1999;27(9):1991–8. 82. Kramer M, Schmalenberg C. Securing “good” nurse physician relationship. Nursing Management 2003;34(7):34–8. 83. Rashid M. Hospital design and face-to-face interaction among clinicians: a theoretical model. Health Environments Research & Design Journal 2009;2(4):62−84.

84. Elsbach KD, Pratt MG. The physical environment in organizations. The Academy of Management Annals 2007;1(1):181−224. 85. Rashid M, Zimring C. On psychosocial constructs and office settings: a review of the empirical literature. In Chaudhury H. editor. Proceedings of the Environmental Design Research Association (EDRA) 36 Conference. Vancouver, Canada: EDRA; 2005. p. 107–22. 86. Sundstrom E, Herbert RK, Brown DW. Privacy and communication in an open-plan office: a case study. Environment and Behavior 1982;1:379–92. 87. Allen T. Managing the flow of technology. Cambridge, MA: MIT Press; 1977. 88. Bobele HK, Buchanan PJ. Building a more productive environment. Management World 1979;8(1):8–10. 89. Hillier B, Penn A. Visible colleges: structure and randomness in the place of discovery. Science in Context 1991;4(1):23–49. 90. Boyce P, Hunter C, Howlett O. The benefits of daylight through windows. Troy, New York: Rensselaer Polytechnic Institute; 2003. 91. Roseman C, Booker JM. A seasonal pattern of hospital medication errors in Alaska. Psychiatry Research 1995;57(3):251–7. 92. Buchanan TL, Barker KN, Gibson JT, et al. Illumination and errors in dispensing. American Journal of Hospital Pharmacy 1991;48(10):2137–45. 93. Rashid M, Zimring C. A review of the empirical literature on the relationships between indoor environment and stress in healthcare and office settings: problems and prospects of sharing evidence. Environment and Behavior 2008;40(3):151–90. 94. Bozett FW, Gibbons R. The nursing management of families in the critical care setting. Critical Care Update 1983;10(2):22–7. 95. Byers, JF. Family discussion groups, a way to meet the needs of the ICU patient’s family. Critical Care Nurse 1983;3(1):16–20. 96. Rashid M. Environmental design for patient families in intensive care units. Journal of Healthcare Engineering 2010;1(3):367–97. 97. Simpson T. The family as a source of support for the critically ill adult. AACN Clinical Issues in Critical Nursing 1991;2(2):229–35. 98. Hodovanic BH, Reardon D, Reese W, et al. Family crisis intervention program in the medical intensive care unit. Heart and Lung 1984;13(3):243–9. 99. Molter NC. Needs of relatives of critically ill patients: a descriptive study. Heart and Lung 1979;8(2):332–9. 100. Pati D, Nanda U. Influence of positive distractions on children in two clinic waiting areas. Health Environments Research & Design Journal 2011;4(3):124–40. 101. Gurascio-Howard L, Malloch K. Centralized and decentralized nurse station design: an examination of caregiver communication, work activities, and technology. Health Environments Research and Design Journal 2007;1(1):44–57. 102. Melin L, Gotestam KG. The effects of rearranging ward routines on communication and eating behaviors of psychogeriatric patients. Journal of Applied Behavior Analysis. 198;14(1):47–51. 103. Peterson R, Knapp T, Rosen J. The effects of furniture arrangement on the behavior of geriatric patients. Behavior Therapy 1977;8:464–7. 104. Holahan C. Seating patterns and patient behavior in an experimental dayroom. Journal of Abnormal Psychology 1972;80(2):115–24. 105. Sommer R, Ross H. Social interaction on a geriatrics ward. The International Journal of Social Psychiatry 1958;4(2):128–33. 106. Astedt-Kurki P, Paavilainen E, Tammentie T, et al. Interaction between adult patients’ family members and nursing staff on a hospital ward. Scandinavian Journal of Caring Sciences 2001;15(2):142–50. 107. Miwa Y, Hanyu K. The effects of interior design on communication and impressions of a counselor in a counseling room. Environment and Behavior 2006;38(4):484–502. 108. Daykin N, Bunt L. Music as a Resource for Health and Well-Being. In: Söderback Ingrid, editor. International Handbook of Occupational Therapy Interventions. New York: Springer; 2009. p. 453–46. 109. Ulrich RS, Gilpin L. Healing arts. In: Frampton SB, gilpin L, Charmel P, editors. Putting patients first: Designing and practicing patient-centered care. San Francisco: Jossey-Bass; 2003. p. 117–46. 110. Cooke B, Ernst E. Aromatherapy: A systematic review. British Journal of General Practice 2000;50:493–6. 111. Marcus CC, Barnes M, editors. Healing gardens: Therapeutic benefits and design recommendations. New York: Wiley; 1999. 112. O’Brien ME. Spirituality in Nursing. Sudbury, CT: Jones and Bartlett; 2003. 113. Young C. Spiritually healing environments. In: Spirituality, Health, and Healing. Jones & Bartlett Publishers; 2006. p. 147–68. 114. Landro L. ICUs’ new message: welcome, families. Wall St. J. 2007. (Retrieved from http://oruine.wsj.com/article/SB118419577614963880.html/). 115. Mantone J. Building family-friendly lCUs. Wall St. J. 2007. . (accessed 30.10.2008).

Chapter

4

 

I

Informatics Infrastructure for the Neurocritical Care Unit J. Michael Schmidt, David K. Vawdrey, and Richard S. Moberg

Introduction S.P. is a 60-year-old female with a history of hypertension who presented comatose with a left thalamic intracerebral hemorrhage associated with intraventricular hemorrhage, midline shift, and localized mass effect. Emergently, an external ventricular drain was placed into the left frontal horn, and on day 5 an additional drain was placed into the left temporal horn for persistent left temporal dilation. Invasive multimodality monitoring including intracranial pressure (ICP), and brain tissue oxygen tension (PbtO2), and cerebral microdialysis was placed into the right frontal lobe. She received repeated doses of mannitol and hypertonic saline for persistent elevated ICP. Managing patients with intracranial hypertension, like S.P., is a mainstay in neurocritical care and involves a structured treatment protocol1 to continually assess the effect of each intervention. Tracking and quantifying physiologic measures such as cerebral perfusion pressure (CPP) also is crucial and needs to be put into the context of sedation level, osmotherapies, ventilator settings, and temperature modulation among many other interventions. In a digital world clinical staff should be able to systematically, continually, and rapidly evaluate the effect of various treatments for increased ICP. For instance, when the impact of mannitol and hypertonic saline administration in S.P. is evaluated, the neurocritical care unit (NCCU) staff should have immediate access to basic variables such as osmolality and ICP at the bedside (Fig. 4.1). As fundamental as this is, a plot that contains these core elements is difficult to create in real time and even retrospectively at most institutions. But imagine being able to look at the patient’s display screen in the NCCU and to be able to answer the following questions easily: 1. When mannitol is administered, by how much (mm Hg) is ICP lowered; how quickly is ICP lowered, and how long until ICP again increases to greater than 20 mm Hg? 2. Are repeated administrations of mannitol equally effective or does repeated administration fail to lower ICP as much, as quickly, or as long? 3. Does adding hypertonic saline provide additional ICP reduction? © Copyright 2013 Elsevier Inc. All rights reserved.

4. Do osmolar data suggest that additional osmotic therapy would be dangerous to the patient? Today clinicians generally are required to answer these questions in their heads, approximating when interventions were made by thumbing through the hourly recorded data, estimating each therapy’s impact on ICP, and manually checking laboratory data to estimate the osmolar gap. Ideally other aspects of ICP management protocols also should be evaluated, for example, end-tidal carbon dioxide (CO2) and temperature. Further, analysis tools at the bedside should exist to evaluate the patient’s physiologic status, such as cerebral autoregulation, which would indicate how ICP would respond to changes in blood pressure. This then may reduce the need to discuss how other invasive neuromonitoring data (e.g., cerebral blood flow, PbtO2, cerebral metabolism) may facilitate ICP management. Any attempt to understand these dynamic relationships among ICP, interventions, and other physiology is complicated, and yet this is only one aspect of patient care. The promise of clinical information systems is to improve patient care, reduce medical errors, reduce documentation time, and improve efficiency.2,3 Paper-based hospital medical records are generally inefficient (e.g., illegible handwriting, manual data entry) and have been shown to contribute to medical errors.4,5 Billions of dollars are being devoted to the development and implementation of electronic health records (EHRs)6 and significant progress has been made to bring these data together for documentation purposes.4 Intensive care units (ICUs) have been migrating from paper-based to computerized charting systems for more than a decade.7 In the ICU, however, problems that face clinicians and nurses extend beyond the need for more efficient documentation. During rounds of critically ill patients each morning, a physician may be confronted with more than 200 variables,8,9 and some clinical information systems acquire and store physiologic variables and device parameters online at least every minute.10 People, however, are not able to judge the degree of relatedness between more than two variables.11 The ability to store high-dimensional data far exceeds the intellectual capacity to understand it unassisted12; this greatly contributes to conditions of constant “information overload” that can lead 27

28

Section I—Background Osmolal-Serium

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to preventable medical errors.11,13 A clinical informatics infrastructure in the NCCU that only supports documentation is simply not sufficient. Ideally NCCU staff should be able to use clinical decision support systems to help understand what a patient’s data is trying to tell them.14 Currently there is a paucity of clinical decision support systems in use in the ICU,12 but this is understandable because the data and infrastructure to support their development and use are generally not in place. When patient data is collected in digital form, it usually resides on isolated systems without a way to bring this data together in meaningful ways.4 The objective of this chapter is to provide a blueprint for work with hospital administration, information technology, biomedical engineering, industry vendors, and clinical staff to create an informatics infrastructure that provides decision support. Many hospitals already have data-collection systems in place for electronic documentation, laboratory results, and physician-order systems but need strategies to integrate these data with high-resolution bedside monitor data to support clinical decision support systems. First, clinicians need to be able to articulate a clear message as to why patient data must be stored at a high resolution and be accessible in real time to support clinical decision making.

The Justification: Why Clinical Data Is Needed Data are a commodity that has many purposes but in health care enable hospitals to provide medical care and meet associated legal obligations. Patient data must be maintained securely over a long period of time and done so in a way that maintains patient privacy. Storing data digitally can be more efficient, help reduce medical errors, improve medical device management, and reduce health care costs.3,14,15 It is important for clinicians and nursing staff to voice how patient data can be used to improve patient care. In the absence of that, other more mundane administrative concerns usually take precedence. In the NCCU the clinical need for real-time access to patient data and clinical decision support systems falls into three categories. First, NCCU staff need tools to evaluate the effectiveness of treatment(s) meant to modify physiologic

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endpoints or improve clinical conditions such as cerebral vasospasm or sepsis. Second, patient data should provide under­ standing of the patient’s physiologic status (e.g., dysautonomia, cerebral autoregulation failure), and how such physiology impacts other metrics of brain health (see Chapter 40). Third, complex relationships within patient data should be automatically processed to enable better understanding of prognosis and earlier diagnosis of secondary events before clinical symptoms occur. This automatic processing of data further supports clinical decision making, and can enable computerized implementation of clinical protocols16 (see Chapter 45) or decision making on prognosis or outcome prediction if appropriate models are used.17,18

Clinical Computing Systems The Blueprint The goal is to create the informatics infrastructure necessary to enable health care providers to leverage data from database systems that contain physiologic, laboratory, pharmacy, and other clinical data for the continued development and implementation of better clinical support tools to provide patients the best care possible.3,4 There are many ways to accomplish these goals, but it is essential to work closely with the institution’s information technology (IT) department to devise the right solution for the ICU and institution because it is often difficult to tell what is needed before the project starts. Regardless of the specifics of the solution, each will contain the same basic elements: (1) collection and storage of different kinds of patient data to a database system; (2) creation of a data warehouse whereby patient data are integrated into a single database with copies of all databases to support real-time analytics; and (3) use of software to perform various methods of analysis that together create a clinical decision support system (Fig. 4.2). Chapters 40 and 45 describe some NCCU specific solutions that have been implemented.

Planning Informatics is a rapidly changing in field, and therefore a department should not be locked in any one system at an

Section I—Background



29

Patient room Bedside devices

Monitor network

Patient monitor Patient monitor mainframe

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Fig. 4.2  Theoretical data collection infrastructure for the neurocritical care unit. A, Medical devices that monitor patient physiology can plug into the bedside patient monitor or be transmitted over the network using a serial-to-TCP/IP converter. B, A data server dedicated to collecting and storing physiologic data can receive data from the patient monitor mainframe or directly from a serial-to-TCP/IP converter that is installed on the server as a COM port. C, An IT-managed data warehouse receives all forms of patient data and makes it available for multiple purposes. D, Clinical decision support systems use the data warehouse to facilitate real-time clinical decision making in the intensive care unit. The data warehouse also supports retrospective analysis of a patient for quality assurance, clinical research, and other aspects of knowledge advancement. COM, Communication; EEG, electroencephalogram; EHR, electronic health record; IT, information technology; TCP/IP, transmission control protocol/Internet protocol.

infrastructure level. Data should be stored in an open nonproprietary format such as Structured Query Language (SQL) (Open Database Connectivity [ODBC] compliant) database that will allow any system to access the data. Many ICU directors strive to include an informatics infrastructure when building a new ICU. This is a great time to do this because there will be a capital budget, and essential items such as installing power and internet connectivity in patient rooms will be cheapest during the construction phase. An ICU construction project also will mean that health care providers will have the attention of hospital administrators and information technology personnel. It also is vital to create an operating budget to maintain the infrastructure over time and to upgrade equipment19 and to decide whether remote data viewing is important to put such a system in place. There are commercial products, such as Citrix MetaFrame, that securely enable this functionality and are gaining favor in ICU and

emergency department (ED) settings.20 Decisions also should be made about whether to integrate the NCCU data with other ICUs, both in the same institution and other medical centers. Creation of such integrative databases may help facilitate syndrome surveillance, decision support, comparative effectiveness research, and outcome research.21,22 Data collection systems and the EHR, however, do not replace verbal communication for efficient interdisciplinary exchange of patient information in the NCCU but can be used to supplement this.23

Collecting Bedside Device Data Overview Current EHR systems generally are adequate to store clinical documentation and laboratory, pathology, and radiology

30

Section I—Background

information. However, most EHRs are not designed to capture and store high-frequency physiologic measurements obtained from patient monitoring equipment. In the NCCU, invasive and noninvasive monitoring techniques provide continuous measurement of physiologic parameters, and this highfrequency data can be vital to understand the course of critical illness and optimize treatment. Data documented in an EHR by the NCCU staff, typically on a hourly basis, are not sufficient to fully represent this physiologic data stream, and therefore it is desirable to establish a thoughtful strategy to collect and use data from bedside medical devices such as ventilators, patient monitors, infusion pumps, and other neurospecific monitors. Bedside medical device data are generally the most difficult data to obtain, whereas continuous electroencephalographic and associated patient video data create the greatest demands on network and storage capacity. The informatics infrastructure needed to collect and store continuous electroencephalographic data in the ICU environment is described in detail elsewhere.24

Collecting Bedside Patient Monitor Data Via a Network Portal Many bedside medical devices are plugged into the standard patient monitor, which serves to display all the digital and waveform data on a single bedside display in real time. Most clinical information systems from patient monitor vendors store these data up to 72 hours for clinical review purposes before they are deleted forever. Some may transfer hourly values into an EHR for nurse verification. Networked patient monitors facilitate patient data display in areas other than the patient’s room, such as a central station or the nursing pod area, by allowing other systems to receive that data from a central server. Networked systems represent one potential strategy to collect all data on every bedside patient monitor from a single networked portal at a high temporal resolution. Some medical device manufacturers, including Philips Healthcare (Andover, MA) and GE Healthcare (Chalfont St. Giles, UK), have developed their own proprietary solutions for automated data acquisition through this single portal. Customers rarely use these solutions because they tend to be expensive, do not provide adequate data frequency, and sometimes do not integrate easily with other clinical information systems. These systems do continue to improve, however, and it is sensible to investigate data collection and storage solutions from the institution’s patient monitor vendor. Third-party products such as DataCaptor (Capsule Technologie, Paris, France) are designed to convert the nonstandard output from bedside devices into HL7 format, which can then be sent to EHR systems such as Cerner Millennium (Cerner Corporation, Kansas City, MO) and Eclipsys Sunrise Clinical Manager (Eclipsys Corporation, Atlanta, GA). Open-source efforts to collect bedside device data for both research and clinical care purposes is described elsewhere.25,26 In the Columbia University Medical Center neurological ICU, Bedmaster XA (Excel Medical Electronics, Jupiter, FL) is used to collect all the bedside patient monitor data including parameter data at least every 5 seconds and all visible waveform data at a resolution of 240 Hz. This system works for both the General Electric and Philips patient monitors.

Collecting Data from Individual Bedside Patient Monitors or Devices It may not always be possible to collect bedside device data through a network portal, and many medical devices do not plug into the patient monitor, or if a device does plug into the monitor, not all the data are transferred. Data then need to be collected from the individual medical device or sometimes even each individual patient monitor. Most bedside devices (including the patient monitor) are equipped with RS-232 (digital) and analog (waveform) data output ports for automatic data output capabilities. Specifications for data communication are generally available in the device’s technical manual or can be obtained from the device manufacturer. Medical devices output data usually as a comma-delimited text string (e.g., 21, 15.6, 78.24, 12, 15) every few seconds. This text string must be converted into data that fill specific fields in a database, which requires knowledge about what each number in the text string represents and in what field in the database it should be stored. This translation is referred to as a device interface (a small bit of software that automatically converts data from the device into sensible data for a particular database). Provided it is known what data output is sent from the machine, what each number means, and where it goes in the database, actually writing a device interface is not complicated. One limitation of RS-232 for bedside device communication is that there are many different ways to send data over the serial interface. Several different pin-out and connector styles exist, and there are multiple options for baud rate, parity, stop bits, handshaking, flow control, and signaling.27 For example, many bedside devices output the data string at a set time frequency without prompting, whereas with other devices, such as the patient bedside monitor, the software interface must send a coded request to receive data. Therefore the device interface must be written to accommodate the specifics of each device or patient monitor configuration. Some newer modes to output data from devices include Universal Serial Bus (USB), 802.3 (Ethernet), IEEE 11073, or even wireless (e.g., 802.11 b/g, Bluetooth) data communication capabilities. Because the life span for some medical devices is 10 to 15 years, it is unlikely that RS-232 ports will disappear in the near future. At Columbia University it was decided to use Bedmaster XA to collect bedside data in the NCCU, because the company also wrote device interfaces for devices that did not connect to the bedside monitor, or did so incompletely. For example, it is possible to collect all 22 parameters outputted from the Arctic Sun cooling device (Medivance, Louisville, CO). This allows caregivers to automatically track the device’s water temperature, which decreases when the machine works harder to maintain body temperature (i.e., fever spike), and other parameters such as ICP and PbtO2. There also is a device interface for the Camino ICP monitor (Integra Neuroscience, Paramus, NJ), even though this monitor can plug into the patient bedside monitor. Many brain injury patients may have an external ventricular drain and a parenchymal ICP monitor. It is important to distinguish each ICP from the other. However, there are limited methods to maintain the same data label for each device regardless of where it was plugged in on the patient monitor. Instead the Camino is now to both the patient monitor and the secondary system, where plugged in

the data label can be controlled. It is important to understand how the patient monitor handles different device scenarios when considering how to collect patient data.

Standards in Bedside Device Collection Technical standards developed for medical device communication are available. These standards are supposed to simplify the problem of getting device data into multiple data systems, but often are not adopted by device manufacturers. Efforts to establish a medical device connectivity standard began in the 1980s with the Medical Information Bus (MIB). The MIB was developed by representatives from medical device manufacturers, health care institutions, and academic departments who advocated “plug-and-play” data sharing among bedside devices irrespective of device vendor.28,29 In 1996 the MIB specification was approved by the Institute of Electrical and Electronic Engineers (IEEE) Standards Board under the name “IEEE 1073 Standard for Medical Device Communications.”30-32 The IEEE 1073 standard continued to evolve, and in 2004 the International Organization for Standardization (ISO) formally ratified IEEE 1073 as “ISO 11073 Point-ofCare Medical Device Communication Standard. Despite this, the ISO/IEEE 11073 standard still is not widely used by the medical device industry. Consequently, most hospitals have limited or no integration of bedside device data with their EHR systems and other clinical information systems. Regulatory concerns present another barrier to medical device connectivity at least in the United States. The U.S. Food and Drug Administration (FDA) requires a manufacturer of a data collection device to test the connections to each device from which it receives data rather than just test to ensure proper implementation of a standard (such as ISO/IEEE 11073). This presents an unnecessary burden on the manufacturer, similar to a computer manufacturer’s having to test the connection to every printer rather than just test to the USB standard. The FDA realizes the benefits of medical device connectivity and the regulatory issues are being addressed as part of the mission of the Medical Device Plug and Play (MDPnP) program.33

Transferring Data Over the Network The simplest configuration to transfer data from a medical device to a computer is to plug a RS-232 cable purchased from the local computer store into the RS-232 output of the medical device and then plug the other end into the nine-pin communication (COM) port of a regular personal computer. A serial-to-TCP/IP converter enables one to send data from multiple bedside devices over the hospital or local network to a server located in another room or building. Placed in the patient’s room and “installed” on the server, it creates multiple COM ports that allow many devices to plug into it and transfer its data over the network using standard TCP/IP protocols. These converters are available in many configurations including virtual and wireless. Special care is needed when wireless communication is used to acquire data from bedside medical devices. First, if mobile monitoring solutions rely on battery power, power consumption issues must be considered. Second, wireless communication devices are a cause of radio frequency (RF) electromagnetic interference (EMI) that may cause undesirable effects to

Section I—Background

31

medical equipment. It is recommended that testing be performed for EMI between mobile wireless communication and medical devices.34 Finally, with many devices and multiple wireless technologies competing to use the same frequency spectrum to transmit, crowding can occur that may decrease throughput and affect the reliability of data exchange. Device manufacturers that use RF communication should provide an analysis of data communication requirements, including estimated bandwidth utilization at periods of peak and normal usage. Data overload is one of the greatest informatics challenges in the NCCU for both medical informaticians and intensive care clinicians.35-39 For example, at Columbia University NCCU bedside monitors store approximately 200 megabytes (MB) per day per bed, whereas continuous electroencephalograms (EEGs) can generate approximately 1 gigabyte (GB) per day for EEG alone, and 20  GB per day when there is video recording. When multiple systems in multiple patient rooms record simultaneously, network performance can slow down or data loss is possible. Modern Ethernet networks that use 1  GB per second or greater connections between switches and routers should be used throughout the network to help avoid this problem. It also is important to check for potential bottleneck areas where older systems that use 10 or 100 MB per second connections may exist (e.g., when networks span new and old buildings).24

Linking Patients to Their Data Medical device connectivity is complex, and this extends beyond simply the physical connectors and communication protocols. Perhaps more important is to establish patient context and ensure that device(s) data are reliably associated with the correct patient. A wired infrastructure simplifies patient association because each device can be connected unambiguously to a particular location (i.e., room or bed number). Use of existing electronic admission/discharge/ transfer (ADT) systems to map a specific patient to a location can link device data to a patient. However, mobile devices (e.g., infusion pumps) and wireless data communication introduce additional challenges for patient identification. Some devices allow a patient’s medical record number to be entered into the device interface, or provide bar code scanning capabilities to accomplish the same task. It is essential to consider how data will be linked to a patient before device purchase. There may be an advantage to automatic data documentation directly to an electronic medical record (EMR) from devices such as ventilators and infusion pumps; several studies show this is more accurate and saves nursing time.33,40,41 In some ICUs ventilators are always connected to the bedside monitor and their data automatically transmitted to an EMR for verification. Infusion pumps should have the capability to send streaming data, but not all are able to do this; some that do, send anonymous drug and dose data to a server to help biomedical departments with asset management and device maintenance. Transmission of anonymous data bypasses the Health Insurance Portability and Accountability Act (HIPAA) and privacy concerns. This alleviates potential headaches for biomedical engineering and informatics departments; however, this does not help clinicians manage patients. These various issues need to be addressed

32

Section I—Background

before making purchase decisions. No matter the mechanism used to link device data to patients, local testing and periodic validation should be performed to ensure accuracy.

Time Synchronization It is critical to synchronize data together from multiple devices for accurate bedside device data collection. Each device may maintain its own internal clock, and additional clocks may exist for the data acquisition system and the hospital clinical information system. When data that are used for time-sensitive analyses (e.g., when does an infused medication affects vital signs, when do alarms trigger, and what is the duration?) are recorded, it is important to know exactly the order and delay between events. The Network Time Protocol (NTP) is the most commonly used Internet time protocol and can be used if utilities for time synchronization are otherwise unavailable.

Other Data Collection Considerations It is important to anticipate how the data may be used to prepare an effective strategy for physiologic data acquisition in the NCCU. Is the purpose of data collection to facilitate clinical care, research, or both? If the data are to be used to provide patient care and there is an existing EHR system in use, it is important to decide whether bedside device data will be automatically transferred to the EHR, and if so, how this will be accomplished. Undoubtedly there will be workflow changes for care providers associated with automatic data collection (e.g., documentation and data review processes). To help anticipate some of the sociotechnical challenges that may arise, both technologic and associated with personnel or workflow, the following questions should be addressed: How often will data be transferred to the existing EHR system?  Will manual verification be required before the data are included in the patient’s record?  For each data element that is currently documented in the patient’s record, does that element exist in the bedside device’s output stream?  Will filters be applied to the data to reduce artifact (i.e., “noise” in the signal) or select representative measurements?  Will the same type of measurement be obtained simultaneously from separate devices (e.g., respiratory rate collected from a patient monitor and a mechanical ventilator)? How will these measurements be dealt with?  How will downtime procedures be created and enforced (for the EHR system as well as the data collection system)? 

Some clinical information systems may not be capable of handling second-by-second or even minute-by-minute recording of physiologic variables. If data are to be stored in a secondary or research database instead of or in addition to an EHR system, several other questions should be considered: How will data be stored (e.g., flat files, relational database, XML database)?  How will data backups be performed?  How frequently can or should data be acquired and stored (e.g., 500 Hz, 1 sec, 5 sec, 1 min, 15 min, 1 hr)? 

Data Warehouse Configurations In this chapter the focus has been on how to get high-frequency data (i.e., parameter data every 5 seconds) from the patient monitor and other bedside medical devices to a “server.” Servers are simply a class of computers with large computational and storage capacities that manage, store, and retrieve data for other computers or devices.19 A data warehouse is a collection of decision support technologies to enable better and faster decisions42 that is composed of multiple servers and networked data storage to support clinical decision making and research.3,43 A data warehouse is where laboratory, imaging, intervention, physiologic, and all other patient databases reside. Traditional data warehouses are set up to bring several different kinds of data (e.g., laboratory and physiologic) together into a unified database to be used by clinical support software tools. Software programs translate data output from the device into an intelligent form to allow the data to be added into a database at medical device interfaces. Similarly to transfer data from one database to another database also requires a software interface. Database interfaces rely on standards such as HL7 to streamline the process. An interface engine is software that manages all the standardized “messages” being sent back and forth between databases.44 An alternative and more flexible strategy is to create a real-time replica of each database paired with software that supports real-time and ad hoc queries from decision support software.43 The exact strategy to be used in the NCCU will require discussion with the institutional IT department and vendors. There are several important considerations to link databases. First, performance bottlenecks are not specific to the network and can occur at the server level. There needs to be adequate storage capacity for primary data collection of patient monitors and medical devices, a backup of these data in case of hardware failure, and replicas or integrated databases that will support clinical support applications to prevent bottlenecks. Second, the file server and associated disk systems need to be sufficiently robust to avoid performance slowdowns during data collection, data review, and other maintenance functions. Third, file servers used in critical care should be capable of operating without interruption, despite common, predictable component failures. Strategies such as redundant power supplies and redundant arrays of independent disks (RAIDs) rather than storing data on single hard drives may prevent this. Though there are many variations of a RAID drive, in its basic form data are divided and written across multiple devices simultaneously and redundantly. This can increase performance and provide fault tolerance.19,24

Clinical Decision Support Research still is needed to determine what data should be collected at the bedside, and how information is best summarized and presented to health care providers in the NCCU. Innovative graphic displays show particular promise but have yet to be adopted on a large scale.37,45-49 Display of physiologic trends also is important in critical care, perhaps more so than simple numeric displays or threshold alarms. Adoption of automatic data acquisition from bedside devices will finally enable the research and patient care environment that Peters and Stacy anticipated almost a half-century ago:

Section I—Background

“The ability to combine analogue and digital computation … moves the field of analysis of physiologic data to that point where mathematical postulates can be set up and tested in the real situation. The enhancement of this skill and propensity will permit us to take physiology out of the data-collecting-for-data’s-sake stage to the more imaginative methods now employed in physical sciences. This step will mean as much to the advancement of knowledge in physiology as it has meant in the physical sciences.”50 Chapters 40 and 45 address these issues in further detail. However, how the data will be used needs to be considered to collect it in a manner that enables proper use. Currently there is little regulatory guidance on clinical decision support systems despite reports that have surfaced about their potential for harm.51 Two independent organizations are addressing this52,53 and will hopefully provide some certification guidelines. Thus the regulatory issues ahead are certain to become more stringent, but the actual outcome remains unpredictable.

Conclusion To create the infrastructure necessary for a successful neuromonitoring and clinical informatics program in the NCCU is feasible, and there are enough commercial resources available to help with this process. The key to success is to recognize that there are actually four problems to consider when the infrastructure is developed: data collection, data visualization, data analysis, and decision support. The first and most important step is data collection, because without the data nothing else is possible. It is critical to clearly articulate to hospital administrators and information technologists what data the NCCU needs, how it will be used, and what positive impact it should have on patient care, for example, better outcomes or reduced length of stay. Each hospital constituent group has different needs for the same data, and unless the NCCU needs are understood, the required data may turn out to be unavailable or inaccessible. Therefore NCCU staff should work with the information technology group to make sure that network and storage concerns are addressed up front and that there is an equipment maintenance plan. The data should be stored in a manner such that it can be automatically exported in a standard format to any number of viewing or analysis systems. In addition, communication between different health care providers (e.g., nurses, pharmacists, physicians) is necessary to ensure a synchronized and efficient system.54 These steps will ensure that the infrastructure will withstand the test of time and subsequently enable leverage of whatever technologies emerge in the years to come.

References 1. Mayer S, Chong J. Critical care management of increased intracranial pressure. J Intensive Care Med 2002;17(2):55–67. 2. Payne T. Introduction and overview of clinical computing systems within a medical center. In: Payne T, editor. Practical guide to clinical computing systems: design, operations, and infrastructure. Burlington, MA; Academic Press; 2008. 3. Martich G, Waldmann C, Imhoff M. Clinical informatics in critical care. J Intensive Care Med 2004;19(3):154–163. 4. Varon J, Marik PE. Clinical information systems and the electronic medical record in the intensive care unit. Curr Opin Crit Care 2002;8(6): 616–24.

33

5. Mador R, Shaw N. The impact of a critical care information system (CCIS) on time spent charting and in direct patient care by staff in the ICU: a review of the literature. Int J Med Inform 2009;78(7):435–45. 6. Gill JM. EMRs for improving quality of care: promise and pitfalls. [comment] Fam Med 2009;41(7):513–15. 7. Donati A, Gabbanelli V, Pantanetti S, et al. The impact of a clinical information system in an intensive care unit. J Clin Monit Comput 2008; 22(1):31–6. 8. Morris G, Gardner R. Computer applications. In: Hall, J, Schmidt G, Wood L, editors. Principles of critical care. McGraw-Hill: New York; 1992. p. 500–14. 9. Gather U, Imhoff M, Fried R. Graphical models for multivariate time series from intensive care monitoring. Stat Med 2002;21(18):2685–2701. 10. Imhoff M, Fried R, Gather U, et al. Dimension reduction for physiological variables using graphical modeling. AMIA Annu Symp Proc 2003:313–17. 11. Imhoff M, Fried R, Gather U. Detecting relationships between physiological variables using graphical modeling. Proc AMIA Symp 2002:340–4. 12. De Turck F, Decruyenaere J, Thysebaert P, et al. Design of a flexible platform for execution of medical decision support agents in the intensive care unit. Comput Biol Med 2007;37(1):97–112. 13. Jennings D, Amabile T, Ross L. Informal assessments: data-based versus theory-based judgments. In: Kahnemann D, Slovic P, Tversky A, editors. Judgments under uncertainty: heuristics and biases. Cambridge University Press: New York; 1982. p. 211–30. 14. Adhikari N, Lapinsky S. Medical informatics in the intensive care unit: overview of technology assessment. J Crit Care 2003;18(1):41–7. 15. Clemmer TP. Computers in the ICU: where we started and where we are now. J Crit Care 2004;19(4):201–7. 16. Campion TR Jr, Waitman LR, May AK, et al. Social, organizational, and contextual characteristics of clinical decision support systems for intensive insulin therapy: a literature review and case study. Int J Med Inform 2010; 79(1):31–43. 17. Peelen L, de Keizer NF, Jonge E, et al. Using hierarchical dynamic Bayesian networks to investigate dynamics of organ failure in patients in the intensive care unit. J Biomed Inform 2010;43(2):273–86. 18. Ji SY, Smith R, Huynh T, et al. A comparative analysis of multi-level computer-assisted decision making systems for traumatic injuries. BMC Med Inform Decis Mak 2009;9:2. 19. Chou D, Sengupta S. Infrastructure and security. In: Practical guide to clinical computing systems: design, operations, and infrastructure. Payne T, editor. Burlington, MA: Academic Press; 2008. 20. Payne T. Architecture of clinical computer systems. In Payne T, editor. Practical guide to clinical computing systems: design, operations, and infrastructure. Burlington, MA: Academic Press; 2008. 21. Herasevich V, Pickering BW, Dong Y, et al. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc 2010;85(3):247–54. 22. Platt R, Takvorian SU, Septimus E, et al. Cluster randomized trials in comparative effectiveness research: randomizing hospitals to test methods for prevention of healthcare-associated infections. Med Care 2010;48 (6 Suppl):S52–7. 23. Collins SA, Bakken S, Vawdrey DK, et al. Model development for EHR interdisciplinary information exchange of ICU common goals. Int J Med Inform 2010; Oct 23. Epub ahead of print. 24. Kull L, Emerson R. Continuous EEG monitoring in the intensive care unit: technical and staffing considerations. J Clin Neurophysiol 2005;22(2): 107–18. 25. Kroth PJ, Belsito A, Overhage JM, et al. Bedside vital signs capture for the non-ICU setting—an open source, PC-based solution. Proc AMIA Symp 2001:344–8. 26. Vawdrey DK, Hum RS. OpenMDC: an open-source framework for medical device communication. In: AMIA Annu Symp Proc. Washington, DC; 2008. 27. TAL tech: Instrumental software solutions. [cited 1/2/2010]; Available from: www.taltech.com/resources/intro-sc.html. 28. Gardner RM, Hawley WL, East TD, et al. Real time data acquisition: recommendations for the Medical Information Bus (MIB). Int J Clin Monit Comput 1991;8(4):251–8. 29. Shabot MM. Standardized acquisition of bedside data: the IEEE P1073 medical information bus. Int J Clin Monit Comput 1989;6(4):197–204. 30. Garnsworthy J. Standardizing medical device communications: the Medical Information Bus. Med Device Technol 1998;9(3):18–21. 31. Kennelly RJ. Improving acute care through use of medical device data. Int J Med Inf 1998;48(1-3):145–9. 32. Kennelly RJ, Gardner RM. Perspectives on development of IEEE 1073: the Medical Information Bus (MIB) standard. Int J Clin Monit Comput 1997;14(3):143–9.

34

Section I—Background

33. Dalto JD, Johnson KV, Gardner RM, et al. Medical information bus usage for automated IV pump data acquisition: evaluation of usage patterns. Int J Clin Monit Comput 1997;14(3):151–4. 34. Bruns B, Dimantha S. Evaluating EMI in a multi-hospital facility. Biomed Instrum Technol 2006;Suppl:40–2. 35. Alberdi E, Gilhooly K, Hunter J, et al. Computerisation and decision making in neonatal intensive care: a cognitive engineering investigation. J Clin Monit Comput 2000;16(2):85–94. 36. Calvelo D, Chambrin MC, Pomorski D, et al. Towards symbolization using data-driven extraction of local trends for ICU monitoring. Artif Intel Med 2000;19(3):203–23. 37. Clemmer TP, Gardner RM. Data gathering, analysis, and display in critical care medicine. Respir Care 1985;30(7):586–601. 38. Cole WG, Stewart JG. Human performance evaluation of a metaphor graphic display for respiratory data. Methods Inf Med 1994;33(4):390–6. 39. Sims AJ, Pay, DA, Watson BG. An architecture for the automatic acquisition of vital signs by clinical information systems. IEEE Trans Inf Technol Biomed 2000;4(1):74–5. 40. Sapo M, Wu S, Asgari S, et al. A comparison of vital signs charted by nurses with automated acquired values using waveform quality indices. J Clin Monit Comput 2009;23(5):263–71. 41. Vawdrey D, Gardner RM, Evans RS, et al. Assessing data quality in manual entry of ventilator settings. J Am Med Informat Assoc 2007;14(3): 295–303.

42. Chaudhuri S, Dayal U. An overview of data warehousing and OLAP technology. ACM Sigmod Record 1997;26(1):65–74. 43. Chelico J, Wajngurt D. Architectural design of a data warehouse to support operational and analytical queries across disparate clinical databases. AMIA Annu Symp Proc 2007;11:901. 44. Payne T, Hoath J. Creating and supporting interfaces. In Payne T, editor. Practical guide to clinical computing systems: design, operations, and infrastructure. Burlington, MA: Academic Press; 2008. 45. Cole WG, Stewart JG. Metaphor graphics to support integrated decision making with respiratory data. Int J Clin Monit Comput 1993;10(2):91–100. 46. Horn W, Popow C, Unterasinger L. Support for fast comprehension of ICU data: visualization using metaphor graphics. Methods Inf Med 2001;40(5): 421–4. 47. Syroid ND, Agutter J, Drews FA, et al. Development and evaluation of a graphical anesthesia drug display. Anesthesiology 2002;96(3):565–75. 48. Powsner SM, Tufte ER. Graphical summary of patient status. Lancet 1994; 344(8919):386–9. 49. Drews FA, Westenskow DR. The right picture is worth a thousand numbers: data displays in anesthesia. Hum Factors 2006;48(1):59–71. 50. Peters RM, Stacy RW. Automatized clinical measurement of respiratory parameters. Surgery 1964;56:44–52. A complete list of references for this chapter can be found online at www.expertconsult.com.



References 1. Mayer S, Chong J. Critical care management of increased intracranial pressure. J Intensive Care Med 2002;17(2):55. 2. Payne T. Introduction and overview of clinical computing systems within a medical center. In: Payne T, editor. Practical guide to clinical computing systems: design, operations, and infrastructure. Academic Press: Burlington, MA;2008. 3. Martich G, Waldmann C, Imhoff M. Clinical informatics in critical care. J Intensive Care Med 2004;19(3):154. 4. Varon J, Marik PE. Clinical information systems and the electronic medical record in the intensive care unit. Curr Opin Crit Care 2002;8(6):616–24. 5. Mador R, Shaw N. The impact of a critical care information system (CCIS) on time spent charting and in direct patient care by staff in the ICU: a review of the literature. Int J Med Inform 2009;78(7):435–45. 6. Gill JM. EMRs for improving quality of care: promise and pitfalls. [comment] Fam Med 2009;41(7):513–15. 7. Donati A, Gabbanelli V, Pantanetti S, et al. The impact of a clinical information system in an intensive care unit. J Clin Monit Comput 2008;22(1):31–6. 8. Morris G, Gardner R. Computer applications. In: Hall, J, Schmidt G, Wood L, editors. Principles of critical care. McGraw-Hill: New York; 1992. p. 500–14. 9. Gather U, Imhoff M, Fried R. Graphical models for multivariate time series from intensive care monitoring. Stat Med 2002;21(18):2685–2701. 10. Imhoff M, Fried R, Gather U, et al. Dimension reduction for physiological variables using graphical modeling. AMIA Annu Symp Proc 2003:313–17. 11. Imhoff M, Fried R, Gather U. Detecting relationships between physiological variables using graphical modeling. Proc AMIA Symp 2002:340–4. 12. De Turck F, Decruyenaere J, Thysebaert P, et al. Design of a flexible platform for execution of medical decision support agents in the intensive care unit. Comput Biol Med 2007;37(1):97–112. 13. Jennings D, Amabile T, Ross L. Informal assessments: data-based versus theory-based judgments. In: Kahnemann D, Slovic P, Tversky A, editors. Judgments under uncertainty: heuristics and biases. Cambridge University Press: New York; 1982. p. 211–30. 14. Adhikari N, Lapinsky S. Medical informatics in the intensive care unit: overview of technology assessment. J Crit Care 2003;18(1):41–7. 15. Clemmer TP. Computers in the ICU: where we started and where we are now. J Crit Care 2004;19(4):201–7. 16. Campion Jr TR, Waitman LR, May AK, et al. Social, organizational, and contextual characteristics of clinical decision support systems for intensive insulin therapy: a literature review and case study. Int J Med Inform 2010;79(1):31–43. 17. Peelen L, de Keizer NF, Jonge E, et al. Using hierarchical dynamic Bayesian networks to investigate dynamics of organ failure in patients in the intensive care unit. J Biomed Inform 2010;43(2):273–86. 18. Ji SY, Smith R, Huynh T, et al. A comparative analysis of multi-level computer-assisted decision making systems for traumatic injuries. BMC Med Inform Decis Mak 2009;9:S6. 19. Chou D, Sengupta S. Infrastructure and security. In: Practical guide to clinical computing systems: design, operations, and infrastructure. Payne T, editor. Burlington, MA: Academic Press; 2008. 20. Payne T. Architecture of clinical computer systems. In: Payne T, editor. Practical guide to clinical computing systems: design, operations, and infrastructure. Burlington, MA: Academic Press; 2008. 21. Herasevich V, Pickering BW, Dong Y, et al. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc 2010;85(3):247–54. 22. Platt R, Takvorian SU, Septimus E, et al. Cluster randomized trials in comparative effectiveness research: randomizing hospitals to test methods for prevention of healthcare-associated infections. Med Care 2010;48 (6 Suppl):S52–7. 23. Collins SA, Bakken S, Vawdrey DK, et al. Model development for EHR interdisciplinary information exchange of ICU common goals. Int J Med Inform 2010; Oct 23. [Epub ahead of print] 24. Kull L, Emerson R. Continuous EEG monitoring in the intensive care unit: technical and staffing considerations. J Clin Neurophysiol 2005;22(2):107–18. 25. Kroth PJ, Belsito A, Overhage JM, et al. Bedside vital signs capture for the non-ICU setting—an open source, PC-based solution. Proc AMIA Symp 2001:344–8.

Section—Background 34.e1 26. Vawdrey DK, Hum RS. OpenMDC: an open-source framework for medical device communication. In: AMIA Annu Symp Proc. Washington, DC; 2008. 27. TAL tech: Instrumental software solutions. [cited 1/2/2010]; Available from: www.taltech.com/resources/intro-sc.html. 28. Gardner RM, Hawley WL, East TD, et al. Real time data acquisition: recommendations for the Medical Information Bus (MIB). Int J Clin Monit Comput 1991;8(4):251–8. 29. Shabot MM. Standardized acquisition of bedside data: the IEEE P1073 medical information bus. Int J Clin Monit Comput 1989;6(4):197–204. 30. Garnsworthy J. Standardizing medical device communications: the Medical Information Bus. Med Device Technol 1998;9(3):18–21. 31. Kennelly RJ. Improving acute care through use of medical device data. Int J Med Inf 1998;48(1-3):145–9. 32. Kennelly RJ, Gardner RM. Perspectives on development of IEEE 1073: the Medical Information Bus (MIB) standard. Int J Clin Monit Comput 1997;14(3):143–9. 33. Dalto JD, Johnson KV, Gardner RM, et al. Medical information bus usage for automated IV pump data acquisition: evaluation of usage patterns. Int J Clin Monit Comput 1997;14(3):151–4. 34. Bruns B, Dimantha S. Evaluating EMI in a multi-hospital facility. Biomed Instrum Technol 2006;Suppl:40–2. 35. Alberdi E, Gilhooly K, Hunter J, et al. Computerisation and decision making in neonatal intensive care: a cognitive engineering investigation. J Clin Monit Comput 2000;16(2):85–94. 36. Calvelo D, Chambrin MC, Pomorski D, et al. Towards symbolization using data-driven extraction of local trends for ICU monitoring. Artif Intel Med 2000;19(3):203–23. 37. Clemmer TP, Gardner RM. Data gathering, analysis, and display in critical care medicine. Respir Care 1985;30(7):586–601. 38. Cole WG, Stewart JG. Human performance evaluation of a metaphor graphic display for respiratory data. Methods Inf Med 1994;33(4):390–6. 39. Sims AJ, Pay, DA, Watson BG. An architecture for the automatic acquisition of vital signs by clinical information systems. IEEE Trans Inf Technol Biomed 2000;4(1):74–5. 40. Sapo M, Wu S, Asgari S, et al. A comparison of vital signs charted by nurses with automated acquired values using waveform quality indices. J Clin Monit Comput 2009;23(5):263–71. 41. Vawdrey D, Gardner RM, Evans RS, et al. Assessing data quality in manual entry of ventilator settings. J Am Med Informat Assoc 2007;14(3):295–303. 42. Chaudhuri S, Dayal U. An overview of data warehousing and OLAP technology. ACM Sigmod Record 1997;26(1):65–74. 43. Chelico J, Wajngurt D. Architectural design of a data warehouse to support operational and analytical queries across disparate clinical databases. AMIA Annu Symp Proc 2007;11:901. 44. Payne T, Hoath J. Creating and supporting interfaces. In: Payne T, editor. Practical guide to clinical computing systems: design, operations, and infrastructure. Burlington, MA; Academic Press; 2008. 45. Cole WG, Stewart JG. Metaphor graphics to support integrated decision making with respiratory data. Int J Clin Monit Comput 1993;10(2):91–100. 46. Horn W, Popow C, Unterasinger L. Support for fast comprehension of ICU data: visualization using metaphor graphics. Methods Inf Med 2001;40(5):421–4. 47. Syroid ND, Agutter J, Drews FA, et al. Development and evaluation of a graphical anesthesia drug display. Anesthesiology 2002;96(3):565–75. 48. Powsner SM, Tufte ER. Graphical summary of patient status. Lancet 1994;344(8919):386–9. 49. Drews FA, Westenskow DR. The right picture is worth a thousand numbers: data displays in anesthesia. Hum Factors 2006;48(1):59–71. 50. Peters RM, Stacy RW. Automatized clinical measurement of respiratory parameters. Surgery 1964;56:44–52. 51. Tsai TL, Fridsma DB, Gatti G. Computer decision support as a source of interpretation error: the case of electrocardiograms. J Am Med Inform Assoc 2003;10:478–83. 52. Healthcare Information Technology Standards Panel (HITSP), New York: American National Standards Institute. 53. Certification Commisssion for Health Information Technology (CCHIT), Chicago, IL. 54. Pingenot AA, Shanteau J, Sengstacke LT. Description of inpatient medication management using cognitive work analysis. Comput Inform Nurs 2009;27(6):379–92.

Chapter

5

 

I

Nursing and Education DaiWai M. Olson

Almost a century ago George Santayana1 wrote, “Those who cannot remember the past are condemned to repeat it.” The history of nursing parallels the development of patient monitoring and equally affords an insight to predict some of the future directions in patient monitoring. Today nurses view the terms multitasking and multimodal monitoring not as new terms, but as evolving paradigms.2 In this chapter the historical influence of medicine on the current role of the nurse serves as a mechanism to understand how nursing can optimally contribute to emerging trends in neurologic monitoring.

profession. Wreszinski4 translated the Ebbers papyrus such that future English versions report “wet nurse” as the figure who provides milk to a child. Historians find no female versions of a nurse’s role as an attendant or assistant to the physician. The nosocomii were men who were educated by physicians and taught how to run a hospital; the role of the nosocomii (from which we derive nosocomial) is not fully described but is thought to be the first ancestor of modern nursing. More modern times provide a few clues to the emerging role of nursing. The physician’s role evolved over time and was symbolized through Asclepius, the god of medicine and healing. The rod of Asclepius often is shown with a coiled snake. Of the five daughters of Asclepius, it is Hygeia, goddess of health, from whom many believe the modern nurse descends (Fig. 5.1). Drawings and sculptures of Hygeia often depict her holding a snake, cup, or both. Further symbolism of the rod of Asclepius is the caduceus. This symbol, which has come to represent medicine, shows twin snakes (or a two-headed snake) coiled about the rod of Asclepius. The caduceus was adopted in the early 1900s to represent medicine and often is confused with the twin snakes and winged staff of Hermes (a symbol of commerce). Controversy exists whether the snake represents the twin battles of life and death, or more directly the practice of removing worms from open wounds by winding them about a small staff.

Ancient Past

Immediate Past

In ancient times nursing and medicine were intertwined, and there were healers who brewed medicinal teas and tended to injuries with a combination of mysticism, herbalism, and remedies handed down through oral history.3 After each cup of “medicine” and after each broken bone was set, the healers monitored their patients and observed their successes and failures that they shared with other healers. When human societies settled down and towns were established, medical care was regimented and evolved into a discipline. As the base of medical knowledge expanded, humankind began to document the effect of various treatments. Oral history or direct observation no longer could adequately transfer medical knowledge that now was shared across time and distance in written form. Although physical evidence exists to support splinting of bones, herbal remedies, and even trepanation, much of known early medical history is attributed to Egyptian papyrus writings.3 Several key writings provide clues to the role of nursing in emerging societies. Except for midwifery, nursing was predominantly a male

During the middle ages the role of God in health care expanded and in times of plague, men and women devoted to God began to house and care for the sick. Most historical scholars believe that the nun’s habit of the 15th and 16th centuries is the forerunner to the nurses’ cap of the mid-20th century. Nursing care was a separated workforce, both by sex and time. Male nurses associated with religious brotherhoods and female nurses associated with sisterhoods often were separated by distances that were not easily crossed.5 The end of the Middle Ages marked the onset of modern history and a further evolution in the healing arts. In particular global commerce, increasing life span, growing population centers, and war created new opportunities and challenges for the medical team. During this time it was realized that a physician alone could not attend to the sick and wounded. Instead, nurses around the world took on this role. Florence Nightingale provides one of the earliest and most resilient personifications of the nursing profession and the role of nursing care in patient outcome. She had been educated in mathematics and

Introduction Nurses and physicians come from two distinctly different programs. In the neurocritical care unit (NCCU) they work side by side but may not have been provided with the opportunity to understand each other’s roles. The purpose of this chapter is to provide a common ground of understanding for nurses and physicians to help improve multimodal monitoring systems by exploring the role of nursing in patient monitoring and how nursing education influences that role.

Historical Perspective of Nursing and Monitoring

© Copyright 2013 Elsevier Inc. All rights reserved.

35

36

Section I—Background

Fig. 5.1  Asclepius and Hygeia.

through careful observation was able to demonstrate a significant change in outcomes by modifying the postoperative care and environment of soldiers during the Crimean War. By war’s end she had penned texts on care and conduct in both military and civilian hospitals and helped to establish a center for nursing training. After the war she wrote Notes on Nursing, which provided details on how nurses should care for and monitor patients in their wards.6 In this book her words provide a glimpse of the future: “What you want are facts, not opinion—for what can have any opinion of any value as to whether the patient is better or worse, excepting the constant medical attendant, or the really observing nurse?” F. Nightingale (1860)

This insight forecasts two needs in the establishment of fact and a foundation of monitoring in neurocritical care. First, the phrase “constant medical attendant” implies a need to obtain data without gaps across time. Second is the use of the word “observing” as a method to obtain facts about the patient rather than provide opinions.

Recent History In the last century nursing and medicine have witnessed an astounding evolution in the ability to acquire and store data. Although nothing has replaced the utility of direct observation, new tools have been developed to enhance observational skills and provide for continuous assessment. Feeling for the threadiness of a pulse was replaced with blood pressure auscultation, then noninvasive blood pressure cuffs and subsequently with continuous intra-arterial blood pressure monitoring and now an effort to use noninvasive blood flow monitoring. Just as the tools to find facts have evolved, so have the methods to communicate and record these facts. Oral

histories and verbal reports of facts were replaced with short notes. Notes become cumbersome and were placed in charts, which became disorganized and were replaced with tabseparated sections. Physicians wrote orders for nurses to follow (being careful to press down hard enough to ensure that their notes filtered through multiple layers of carboncopy paper. Electronic medical records (EMRs) now dominate the field and provide the opportunity to think of data acquisition beyond traditional boundaries. Changes in how we observe and record data have paralleled the changes in who records and observes data. After the U.S. Civil War, nursing became a primarily female occupation. The “Angels of the Battlefield” became famous leaders. Dorothea Dix became the first female superintendent of the Union Army, Mary Todd Lincoln advocated for nursing before and after her husband’s assassination, and Clara Barton became the founder of the American Red Cross. With each new war the face of nursing changed again. By the end of World War II, nearly 60,000 women joined the military nurse corps. With the advantage of rapid transport, medical evacuation, and mobile army surgical hospital (MASH) technology, men became trained as corpsmen in subsequent wars. Many of those corpsmen turned to nursing as a postwar profession.7 Education of nurses has evolved quickly to meet the growing demand for what Nightingale predicted: “a really observing nurse.” In 1873 Linda Richards became the first nurse to graduate as a Nurse with a Diploma in the United States. Thirty years later, North Carolina became the first state to require nursing licensure. By 1956 Columbia University became the first school to award a master’s degree in nursing, and in 1965, the University of Colorado established the first nurse practitioner position. Although nurse educators and nurse scientists began entering academia with doctoral degrees in affiliated areas (e.g., biology, education, psychology), the first PhD programs specifically in nursing were established in 1954.7 Currently nurses have a wide range of programs and career paths that include certification and specialization that range from the licensed practical nurse (LPN) to the doctorally prepared nurse. Table 5.1 provides a list of titles and descriptions for professional nurses with advanced education to give a general understanding of the primary role designated to each discipline.

Nursing Theory—Practice and Process The discipline of nursing is a unique blend of art and science that evolved over many years even before nursing education became compulsory.8,9 The various views on epistemology in nursing are summarized by Walker and Avant.10 Empirical knowing is guided by practice and observation. In the empirical realm, knowledge is created from an extension of the senses; it arises from experiment.11 The need for nursing knowledge as a separate discipline was a major catalyst in the evolutionary process of nursing.12 As nurses became educated they contributed to the fundamental knowledge base of nursing; nursing theory emerged as the driving force to test and explain nursing practice.13 The advantages to this approach are well described.14,15 Nursing science provides the best evidence for nursing care of

Entry to practice as a nursing professional

Basic nursing care

Nursing assessment, nutrition, pharmacology, human growth and development, psychology, maternal/child, microbiology, communication, anatomy and physiology, and mental health nursing

No

High school diploma

2-4 years

Degree objectives

Curriculum focus

Core courses†

Prescriptive authority

Point of entry

Program length§

2-3 years

2-3 years

BSN

Yes

No‡ BSN

Applied statistics. Graduate-level pharmacology, assessment, and pathophysiology, and courses in an elected specialty (e.g., management of critically ill patients, for the acute care NP, versus child health in family care, for the family NP)

Direct care provider with prescriptive authority

An advanced-practice nurse who diagnoses and manages common acute and stable chronic health problems. NPs perform comprehensive physical exams, order and interpret diagnostic tests, obtain specialty consults, and perform and prescribe therapeutic measures, including most classes of medications. NPs, individually accountable for their practice and decisions, collaborate closely with physicians.

Midlevel provider of direct care, master’s degree

Nurse Practitioner (NP)*

Applied statistics, research design and methodology. Graduate-level pharmacology, assessment, and pathophysiology. CNS students are required to take specialty focus courses and advanced health assessment.

Improve outcomes for patients by influencing systems level, team, and patient change

A CNS is an advancedpractice nurse familiar with the theory and research related to a nursing specialty area, such as critical care. Traditionally, a CNS influences patient outcomes through direct clinical practice, collaboration, education, research, consultation and system leadership. CNSs are uniquely prepared, by experience and education, to manage the complexities of negotiating complex health care delivery systems.

Expert in clinical nursing, master’s degree

Clinical Nurse Specialist (CNS)*

2-3 years

BSN

Yes

Neurobiology, spinal and epidural anesthesia, and advanced airway management. Graduate-level pharmacology. CRNAs are required to achieve a number of clinical internship hours (varies by state).

Direct care provider with prescriptive authority

Advanced-practice nursing. CRNAs provide anesthetics to patients in every practice setting, and for every type of surgery or procedure. They are the sole anesthesia providers in two thirds of all rural hospitals, and the main provider of anesthesia to expectant mothers and to men and women serving in the U.S. Armed Forces.

Midlevel provider of anesthesia care, master’s degree

Certified Registered Nurse Anesthetist (CRNA)

2-3 years

BSN or MSN

No‡

Evidence-based practice, applied statistics data driven health care improvement, financial management and budget planning, effective leadership, health systems transformation

Translation of evidence to practice at the systems level

Nursing leaders in interdisciplinary health care teams. Using the tools and skills specific to translating evidence gained through nursing research into practice, they improve systems of care, and measure outcomes of patient groups, populations, and communities.

Leadership roles as an advancedpractice nurse

Doctorate in Nursing Practice (DNP)

4-7 years

BSN or MSN

No

Philosophy of science and theory development, advanced research design, statistics and data analysis longitudinal and qualitative research methods. PhD students are required to take courses related to their intended area of research.

Independent researcher

To prepare nurse scientists to develop new knowledge for the science and practice of nursing. Graduates will lead interdisciplinary research teams, design, and conduct research studies, and disseminate knowledge for nursing and related disciplines, particularly addressing trajectories of chronic illness and care systems.

Nursing research

Doctor of Philosophy (PhD)

Section I—Background

*There are a variety of subspecialties (i.e., family practice, acute care). † Course requirements vary by state and university. The core requirements are provided here only as a sample of general requirements. ‡ May have prescriptive authority. § Full-time student.

Diploma, associate or baccalaureate degree in nursing

Career focus

Registered Nurse (RN)

Table 5.1.  A Short Description of Common Nursing Titles

37

38

Section I—Background

patients.16 Caring, although not solely in the domain of nursing, requires a theoretical basis, just as curing, not solely in the domain of medicine, requires a theoretical basis.17,18 Theory provides a foundation of knowledge about a problem or situation; what is known, what are the components, mediators, moderators, and co-variables. Importantly, theory provides the platform from which new hypotheses may be generated and tested. Nursing knowledge is not limited to academic research or rigid theories. Theories that are not supported by scientific testing give way to those that hold up to such scrutiny. Nurses at all levels are responsible for generating and testing theories, and for participating in research. Most recently, the push for evidence-based practice (EBP) has emerged as a dominant paradigm in nursing care. Understanding the role of nursing theory in nursing education and bedside care provides insight for members of other disciplines that interact with nurses. One of the most widely explored theories in critical care setting is Benner’s Novice to Expert Theory.19

The Novice to Expert Theory Benner’s Novice to Expert theory of nursing care is often cited in the critical care setting19 and describes five stages of professional development: (1) novice, (2) advanced beginner, (3) competent, (4) proficient, and (5) expert. At first appearance the NCCU is a chaotic environment filled with sights, sounds, and even smells that rarely are encountered in daily life. In the midst of this chaos, nurses are focused on the task of patient care. When nurses first come to the intensive care unit (ICU) they enter at the novice level.19 When novices, nurses often may be unsuccessful in recognizing and interpreting key data. The focus is on task completion, and novices are governed by rules (medical orders) such as “record B/P q1h, notify medical doctor if SBP1 Mac Nitrous oxide

The relative influence of anesthetics on brainstem auditory evoked potentials (BAEP) and somatosensory evoked potentials (SSEP) is depicted. Halogenated volatile agents referenced include desflurane, sevoflurane, and isoflurane. ↔, No change; ↑, clinically insignificant increase; ↓, clinically insignificant decrease; , clinically significant increase; , clinically significant decrease; ?, no information.

agents are used, the dose should be kept below 1 MAC to maintain SSEP signal quality. This may be facilitated by the coadministration of potent opiates, which do not affect signal quality. The addition of N2O typically is avoided, because this further degrades the signal.71 In addition, the anesthetic concentration should be kept constant during critical periods to reduce anesthetic influence on the interpretation of changes. The use of intravenous anesthetics, such as propofol, thiopental, or midazolam infusion, often results in better signal quality than with use of volatile agents. Ketamine and etomidate, in particular, have been reported to increase the amplitude of SSEPs, although the effect that this has on sensitivity and utility remains a matter of speculation. Regardless of the anesthetic regimen, it is important to avoid bolus doses or rapid changes in anesthetic depth during key portions of an intervention, such as vessel occlusion or manipulation of the spine, to avoid confounding influences on signal integrity at a critical time when the monitoring modality is most useful. Other factors, such as blood pressure, temperature, and patient position, may influence evoked potential monitoring. Nerve injury associated with patient position, such as crush injury at pressure points, or traction injury must be considered. A decrease in blood pressure may also alter SSEPs and even mild hypothermia can increase latency and decrease the amplitude of evoked potentials because thermoregulatory behaviors and physiologic responses are blunted in the anesthetized patient.

Brainstem Auditory Evoked Potential Monitoring Brainstem auditory evoked potentials (BAEPs) are resistant to anesthetic effects and can be recorded with virtually any

anesthetic technique. Inhalation agents can increase the latency but do not abolish BAEPs.72 The effects of anesthetic agents on BAEP and SSEP are summarized in Table 9.2.

Motor Evoked Potentials MEPs are electrical potentials monitored along the motor pathway after stimulation of the motor cortex or spinal cord. MEPs are elicited by direct or transcranial stimulation with either electrical (TcEMEP) or magnetic (TcMMEP) techniques. Responses can be recorded over the spinal cord from electrodes placed in the epidural space (spinal D waves or epidural MEP), along peripheral motor nerves (neurogenic MEP), or as compound muscle action potentials (CMAPs) over muscle (myogenic MEP). Myogenic MEPs are large amplitude biphasic potentials in response to motor unit depolarization, and so, unlike SSEPs, signal averaging is not required. This allows for near instant motor pathway feedback. TcMMEPs are exquisitely sensitive to anesthetic agents and so are unsuitable for intraoperative monitoring. The entire motor pathway from cerebral motor cortex through brainstem, corticospinal tracks, anterior horn, peripheral nerve, and neuromuscular junction to skeletal muscle can be assessed using transcranial stimulation with myogenic MEP monitoring. Motor pathway injury can result from ischemia, or disruption, retraction, compression, or distraction of neural tissue. Each of these insults can cause functional alterations that may be neurophysiologically evident.73 MEPs therefore are an appealing intraoperative monitor and are applicable to any surgical procedure which places the motor pathway at risk for injury: craniotomy, spinal surgery, or thoracoabdominal aortic aneurysm repair. Intraoperatively, MEPs are usually monitored with SSEPs.

76

Section I—Background 1 stimulus

3 stimuli

5 stimuli

Isoflurane 0%

0.2%

0.4% Fig. 9.1  Graphs that illustrate augmentation of motor evoked potentials (MEP) responses when using multipulse stimuli with increasing isoflurane doses. (Ubags LH, Kalkman CJ, Been HD. Influence of isoflurane on myogenic motor evoked potentials to single and multiple transcranial stimuli during nitrous oxide/opioid anesthesia. Neurosurgery. 1998;43(1): 90–4.)

0.5 mV 0.6%

0

MEPs are useful to monitor for ischemia, particularly of the anterior horn cells (alpha motor neurons), which are thought to be most sensitive to ischemic insults.73 Many publications describe the use of MEP for intraoperative monitoring, although there are no clearly defined thresholds for latency or amplitude changes that correlate with risk of motor pathway injury. In general, latency is robust to anesthetic or surgical insults; therefore amplitude changes are assessed more commonly. The threshold considered concerning for injury is the complete loss of signal rather than a fixed percentage decrease in amplitude (e.g., 50%). Other authors consider the increase in stimulation energy required to reproduce baseline signals as the marker for injury.74 The safety of MEPs is well known.75 However, induction of seizures is a potential risk with TcEMEPs.

Anesthetic Effects MEPs are sensitive to anesthetics; therefore a tailored approach is required to select the most appropriate anesthetic regimen.76 Transcranial magnetic stimulation–generated MEPs are more sensitive to anesthetics than transcranial electrical (TcE) stimulation, and usually are abolished with induction, regardless of the agents used. TcE stimulation therefore is the technique used exclusively during intraoperative monitoring. Transcranial magnetic stimulation currently has a very limited role in the operating room. Early work with TcEMEPs showed that single-pulse signals were extremely sensitive to volatile agents even at subclinical doses.77,78 Subsequently, multipulse stimulation techniques have been shown to improve both lowamplitude baseline signals and MEP signals depressed by anesthesia (Fig. 9.1). Table 9.3 summarizes how different anesthetic agents affect multipulse TcEMEPs, which is the current standard during intraoperative monitoring. “Anesthetic fade,” a time-dependent decrease in MEP signal amplitude proportionate to the length of surgery regardless of the anesthetic regimen can occur.79 Increasing the stimulation

100 Time (msec)

0

100 Time (msec)

0

100 Time (msec)

energy may attenuate anesthetic fade, but increases the risk for potential false-positive signal changes. Volatile anesthetics are used commonly to maintain anesthesia. All currently used halogenated anesthetics cause significant dose-dependent depression of myogenic MEP signals.80-85 This depression is believed to result from volatile anestheticinduced inhibition of pyramidal activation of spinal motor neurons.86 At full anesthetic concentrations of 1 MAC, multipulse TcEMEPs with isoflurane are only recordable in 8% of subjects.82 TcEMEP in response to paired TcE stimulation during sevoflurane anesthesia at 1 MAC is unrecordable,84 whereas with a four-pulse TcE stimulation this result improves to more than 80%.85 However, this is still inadequate for clinical use. With desflurane or sevoflurane at 0.5 MAC with either N2O or a narcotic infusion, MEPs are recordable in 100% of patients,81,83 and with isoflurane MEP monitoring is possible in 90%.78 Total intravenous anesthetic regimens therefore seem preferable and only one study to date has shown adequate clinical recording conditions with a volatile anesthetic compared to total IV technique.81 N2O is used frequently as an anesthetic adjuvant. When 50% N2O is used with intravenous infusion of narcotic with or without propofol, multipulse TcEMEP amplitudes are reduced by about half, but can be consistently recorded.87,88 With concentrations ranging from 20% to 60%, N2O is associated with a dose-dependent decrease in MEP amplitude, yet signals remain recordable in 100% of subjects.89 Given these findings, N2O is an acceptable anesthetic adjuvant during MEP monitoring when administered with other agents that have limited depressive effects. Propofol is currently the most popular anesthetic agent to maintain anesthesia during MEP monitoring in that it is easily titratable and has a favorable pharmacokinetic profile. Titrating propofol infusion rate intraoperatively to achieve clinically relevant concentrations does not affect MEP responses in a clinically significant fashion.90 However, dose-dependent depression of myogenic MEPs can be demonstrated at higher

Section I—Background



77

Table 9.3  Anesthetic Effects on Transcranial Electrical Stimulation on Motor Evoked Potential Responses TcE Pulses

Change in Amplitude from Baseline

% of Subjects with Response

Isoflurane (0.17 MAC)

5

References

↓↓

100%

81

Isoflurane (0.33 MAC) Isoflurane (0.5 MAC)

5

↓↓

100%

81

5

↓↓↓

90%

81

Isoflurane (0.75 MAC)

4

NA

61%

82

Isoflurane (1 MAC)

5

NA

8%

83

Desflurane (0.5 MAC)

5

NA

100%

84

Sevoflurane (0.25 %)

2

↓↓↓

85%

85

Sevoflurane (0.5 MAC)

2/4

ø/NA

55%/100%

85, 86

Sevoflurane (0.75 MAC)

2/4

ø/NA

10%/90%–100%

85, 86

Sevoflurane (1 MAC)

Anesthetic Agent

2/4

ø/NA

0%/80%–90%

85, 86

N2O (50%)

2

↔

100%

88, 89

N2O (20%, 40%, 60%)

6

90

1



100%

Midazolam (0.05 mg/kg bolus)

↓↓↓

100%

92 101

5



NA

Propofol (67 µg/kg/min)

NA

100%

95

Propofol (>100 µg/kg/min)

4

97%

82

Etomidate (0.1 mg/kg bolus)

3

100%

94

Etomidate (5-10 µg/kg/min)

1

100%

96

Ketamine (0.5 mg/kg bolus)

3

↔

100%

94

Ketamine (1 mg/kg/hr)

5

NA

100%

96

↔

100%

97

Thiopental

Dexmedetomidine (1 µg/kg bolus)

↓

Dexmedetomidine (0.15 µg/kg/hr)

7

↔

100%

98

Dexmedetomidine (~0.3 µg/kg/hr)

7

↔

100%

98

Fentanyl (3 µg/kg bolus)

1

↔

100%

92



100%

101

100%

81

↔

100%

102

↓↓↓

100%

102

Remifentanil (9 ng/mL) Sufentanil (0.5 µg/kg/hr)

3

Neuromascular blockade T1 45%–55% of baseline

6

T1 5%–15% of baseline

6

 /ø

↔, Minimal/no change; ↓, decrease 5% to 30% ; ↓↓, decrease 30% to -60%; ↓↓↓, decrease greater than 60%; ø, absent or less than 10%; , dose-dependent decrease; MAC, minimum alveolar concentration; blank indicates no reliable data.

doses.76 Bolus administration of propofol can lead to MEP signal loss. However, since propofol has rapid redistribution and metabolism, signals return within minutes91 (Fig. 9.2). Therefore during intraoperative MEP monitoring propofol is preferable to many of the other intravenous agents because of its desirable neurophysiologic effects and pharmacokinetic profile. Midazolam boluses of 50 µg/kg cause significant depression of single-pulse TcEMEP signals; the signals, however, are still recordable in all patients.91 Infusions of 0.1 mg/kg/hr of midazolam do not depress TcMMEP signals.76 Studies have not been done in humans with multipulse TcE, but one would expect signals to be better than those described for TcM or single pulse TcE. Other benzodiazepines have similar effects as midazolam.

Ketamine can be used in boluses (0.5 mg/kg) or as continuous infusions (1 mg/kg/hr) without altering MEP responses.92-94 Excellent recording conditions are achieved in all cases. However, ketamine has dissociative anesthetic side effects and potentially undesirable or controversial neurophysiologic effects. These factors need to be balanced with the desire for reliable intraoperative MEP signals. Etomidate has appealing hemodynamic stability for anesthesia induction. It also can be used as a continuous infusion to maintain sedation. However, it may contribute to adrenal insufficiency and propylene glycol toxicity. Nevertheless, etomidate allows for excellent recording conditions for MEPs, with only a short duration of suppression following bolus administration and stable recording conditions when given as an infusion.91,93,95

78

Section I—Background Propofol

Midazolam

Etomidate

Fentanyl

+ 2 mV Control

–

2 min 5 min 10 min Fig. 9.2  The effect of intravenous boluses of anesthetic agents on motor evoked potentials (MEPs). (Kalkman CJ, Drummond JC, Ribberink AA, et al. Effects of propofol, etomidate, midazolam, and fentanyl on motor evoked responses to transcranial electrical or magnetic stimulation in humans. Anesthesiology. 1992;76(4):502–9.)

30 min

0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

Dexmedetomidine is a relatively new sedative and anesthetic agent. The effects of dexmedetomidine on MEP amplitudes have been studied in patients undergoing spine surgery.96-98 Earlier studies showed that a standard infusion rate of dexmedetomidine has little effect on MEP amplitude and signals are recordable in 100% of subjects.96,97 However, a more recent study suggests that dexmedetomidine may cause a clinically significant dose-related decrease in MEP amplitude98 and loss of signals has been described in pediatric spine surgery.99 Dexmedetomidine has propofol-sparing effects; therefore a low dose infusion may be a useful adjunct during propofol anesthesia when MEPs are monitored, but the effects of changing infusion rate/plasma concentration must be taken into account. Opioids are administered commonly with other anesthetic agents. Opioids frequently are used when MEP monitoring is required because they have minimal effects. A single bolus of fentanyl at 3 µg/kg does not decrease MEP amplitude.91 Sufentanil at an infusion rate of 0.5 µg/kg/hr allows reliable recordings in 100% of patients.80 Other investigations have shown that opioids decrease myogenic MEPs in a dosedependent manner; however, at target-controlled plasma concentrations remifentanil has the least effect.100 Neuromuscular blockade generally is used to facilitate tracheal intubation or provide an immobile patient optimal surgical exposure. However, boluses of muscle relaxants inevitably abolish MEPs, in that they block signal transduction at the neuromuscular junction. Careful infusions of neuromuscular blockers to achieve 20% to 50% maintenance of single twitch height have been shown to be compatible with reliable MEP recordings when used with a minimally suppressant anesthetic and multipulse TcE. However, deeper blockade leads to unsatisfactory signals.101 To improve MEP amplitude, a posttetanic stimulation can be used.102,103 Caution is necessary in patients with preoperative neurologic deficits because they appear to be more sensitive to the depressant effects of neuromuscular blocking drugs.95 It generally is acceptable and reasonable to use a single dose of a short-acting neuromuscular blocking agent at the time of induction because its effects should wear off by the time intraoperative MEP recording begins. The exception is when a baseline recording is desired. However, maintenance of

Time (msec)

neuromuscular blockade or rebolusing can limit interpretation of MEPs and should be avoided.

Cerebral Metabolism Two modalities can be used intraoperatively to estimate cerebral oxygen metabolism: jugular venous oximetry (see also Chapter 32) and transcranial NIRS (see also Chapter 33). Both modalities provide information on the balance between flow and metabolism rather than on cerebral oxygen metabolism itself. Jugular venous oximetry is discussed in the section on CBF in this chapter.

Near Infrared Spectroscopy NIRS is a noninvasive technique that can measure cerebral oxygen saturation, cerebral blood volume, and even mitochondrial redox states using differential absorption of near infrared light (700 to 1000 nm).104 It is an evolving technology that is starting to be adopted for intraoperative neurophysiologic monitoring, and so its role and utility is only beginning to be elucidated. NIRS is used most commonly in cardiac surgery during cardiopulmonary bypass and during carotid endarterectomy. In carotid endarterectomy it is used as an ischemia monitor during carotid cross clamping and appears to be effective and comparable to other commonly used monitors. However, relative and absolute thresholds for changes in regional cerebral oxygen saturation remain to be defined.105 NIRS also has been used during neuroendovascular procedures for cerebral aneurysm embolization106 and preoperatively to assess patients with skull base tumors and giant aneurysms to determine cerebral oxygen reserve during vessel test occlusion.107 NIRS has several theoretical advantages that make it an appealing intraoperative monitor: (1) it is noninvasive, (2) it allows for continuous assessment, (3) NIRS machines are portable, and (4) spectroscopy is unaffected by anesthetics. However, there also are several disadvantages: (1) it can only be applied to the forehead, (2) the signal is contaminated by extracranial absorption and scattering, and (3) the signals can be affected by ambient light. NIRS is a promising technology, but further research is required to demonstrate its clinical efficacy and justify its routine use during anesthesia.108

Section I—Background



79

Anesthetic Effects

Volatile Anesthetics

Measurement of oxyhemoglobin and deoxyhemoglobin by spectroscopy is unaffected by anesthetics. However, anesthetics can affect cerebral metabolism and CBF. Therefore indirect changes can be observed in NIRS monitoring that result from the pharmacodynamic and consequent physiologic effects of each anesthetic agent. Because NIRS is a relatively new and evolving monitoring modality, there is limited evidence about observed NIRS changes that occur with different anesthetic agents. The known effects are summarized in Table 9.4. Intraoperative use of intravenous dyes such as indigo carmine109 and indocyanine green110,111 can cause low regional cerebral oxygen saturation (rSO2), similar to that observed with pulse oximetry.

The observed NIRS changes seen with the halogenated inhalational agents support findings associated with the neurophysiologic effects of these agents. Desflurane, sevoflurane, and isoflurane have all been examined at clinically relevant concentrations and at 1 MAC do not affect rSO2112-114 despite decreases in blood pressure and cardiac output. These results demonstrate that cerebral autoregulation is maintained at these concentrations. Both desflurane and sevoflurane can result in a dose-dependent increase in rSO2113 suggesting either a shift in the flow-metabolism coupling or cerebrovasodilation at higher concentrations. Sevoflurane, at inhalational induction concentrations of 8%, has been shown to result in cerebral hyperemia, although these results are confounded by the use of N2O.115 The effects of N2O on NIRS have not been specifically studied; however, N2O has been used as an anesthetic adjuvant in many of the studies published on NIRS and may be a confounding factor.

Table 9.4  Observed Changes in Regional Cerebral Oxygen Saturation Under Various Anesthetics References

Intravenous Anesthetics

↔

114

↔

113

Desflurane (>IMAC)



113

Sevoflurane (~IMAC)

↔

112

Sevoflurane (>IMAC)



113,115

Midazolam (0.05 mg/kg bolus)

↔

114

Thiopental (6 mg/kg bolus)

↑

116

Propofol (3 mg/kg bolus)

↑

116

Etomidate (0.3 mg/kg bolus)

↓

116

Because of the ability to rapidly and fairly predictably achieve a state of unconsciousness, bolus administration of intravenous anesthetic commonly facilitates induction of anesthesia. However, limited information is available on the effect of different intravenous agents on rSO2. There is some evidence that sedative doses of midazolam (0.05 mg/kg), do not change rSO2 .113 One study examined the induction effects of etomidate, propofol, and thiopental on cerebral oxygenation and found that propofol and thiopental slightly increased rSO2 while etomidate caused a small decrease in cerebral oxygenation116 (Fig. 9.3). These differences were explained by varying flow-metabolism coupling and cerebral autoregulation properties of the agents. Surprisingly, induction with etomidate resulted in decreased cerebral oxygenation. This observation supports animal work that shows etomidate decreases CBF despite maintenance of mean blood pressure before its

Anesthetic Agent

Change in rSO2

Isoflurane (~IMAC) Isoflurane (~IMAC)

↔, Equivocal/no change; ↑, increase;  ,dose-dependent increase; ↓, decrease; MAC, minimum alveolar concentration.

20

∆[HbO2] (µMolar)

Thiopental

10 Propofol

0

Etomidate –10 –2

–1

0

1 Time (min)

2

3

Fig. 9.3  Line graphs that illustrate relative changes in oxyhemoglobin (HbO2) measured using near infrared spectroscopy (NIRS) after induction of anesthesia with three intravenous anesthetic agents. (Lovell AT, Owen-Reece H, Elwell CE, et al. Continuous measurement of cerebral oxygenation by near infrared spectroscopy during induction of anesthesia. Anesth Analg 1999;88(3): 554–8.)

80

Section I—Background

sedative effects can decrease metabolism. How maintenance or steady-state effects of intravenous anesthetic agents affect NIRS is not clear.

Extracranial Monitors Extracranial monitors commonly used in the operating room include the ECG, noninvasive and invasive blood pressure, central venous pressure, pulse oximetry, and EtCO2. Anesthetic agents do not have any direct influence on the function of these monitors. However, the various anesthetic agents may affect the physiologic variables recorded by these monitors by virtue of their effects on the cardiovascular and respiratory system. The systemic effects of anesthetic agents on these variables are reviewed in standard anesthesia texts (e.g., Miller’s Anesthesia, 7th edition, 2010, Elsevier, or Clinical Anesthesia, 6th edition, 2009, Lippincott Williams & Wilkins).

Conclusion Advanced neuromonitoring frequently is used during neurosurgical procedures to guide surgical decisions and help improve patient safety. The successful deployment of these techniques requires a team approach that involves the neurosurgeon, the anesthesiologist, and the neurophysiologist. The rational use of these monitoring modalities and how the information is interpreted depends on use of an optimal anesthetic regimen. This is only possible with a full understanding of how anesthetic agents influence these various monitors. This chapter provides the basic information and the framework to understand how anesthetic agents affect monitors both directly or indirectly because of physiologic effects. This knowledge is valuable in both the operating room and neurocritical care unit.

References 1. Fukui K, Morioka T, Hashiguchi K, et al. Relationship between regional cerebral blood flow and electrocorticographic activities under sevoflurane and isoflurane anesthesia. J Clin Neurophysiol 2010;27(2):110–5. 2. Mielck F, Brauer A, Radke O, et al. Changes of jugular venous blood temperature associated with measurements of cerebral blood flow using the transcerebral double-indicator dilution technique. Eur J Anaesthesiol 2004:289–95. 3. Yoshitani K, Kawaguchi M, Iwata M, et al. Comparison of changes in jugular venous bulb oxygen saturation and cerebral oxygen saturation during variations of haemoglobin concentration under propofol and sevoflurane anaesthesia. Br J Anaesth 2005;94(3):341–6. 4. Matta BF, Lam AM, Mayberg TS, et al. A critique of the intraoperative use of jugular venous bulb catheters during neurosurgical procedures. Anesth Analg 1994;79(4):745–50. 5. Czosnyka M, Smielewski P, Kirkpatrick P, et al. Continuous assessment of the cerebral vasomotor reactivity in head injury. Neurosurgery 1997;41:11–7. 6. Lam AM, Newell DW. Intraoperative use of transcranial Doppler ultrasonography. Neurosurg Clin N Am 1996;7:709–22. 7. Kincaid MS. Transcranial Doppler ultrasonography: a diagnostic tool of increasing utility. Curr Opin Anaesthesiol 2008;21(5):552–9. 8. Schatlo B, Pluta RM. Clinical applications of transcranial Doppler sonography. Rev Rec Clin Trials 2007;2(1):49–57. 9. Ogasawara K, Suga Y, Sasaki M, et al. Intraoperative microemboli and low middle cerebral artery blood flow velocity are additive in predicting development of cerebral ischemic events after carotid endarterectomy. Stroke 2008;39:3088–91. 10. Ackerstaff RG, Moons KG, van de Vlasakker CJ, et al. Association of intraoperative transcranial Doppler monitoring variables with stroke from carotid endarterectomy. Stroke 2000;31(8):1817–23.

11. Halsey JH. Risks and benefits of shunting in carotid endarterectomy. The International Transcranial Doppler Collaborators. Stroke 1992;23(11): 1583–7. 12. Moritz S, Kasprzak P, Arlt M, et al. Accuracy of cerebral monitoring in detecting cerebral ischemia during carotid endarterectomy: a comparison of transcranial Doppler sonography, near-infrared spectroscopy, stump pressure, and somatosensory evoked potentials. Anesthesiology 2007;107(4):563–9. 13. Ackerstaff RGA. Cerebral circulation monitoring in carotid endarterectomy and carotid artery stenting. Front Neurol Neurosci 2006; 21229–38. 14. Gossetti B, Gattuso R, Irace L, et al. Embolism to the brain during carotid stenting and surgery. Acta Chir Belg 2007;107(2):151–4. 15. Telman G, Kouperberg E, Eran A, et al. Microemboli in MCA ipsilateral to occluded common carotid artery: an observation and short review of the literature. Neurol Res 2008;30(7):684–6. 16. Imray CHE, Pattinson KTS. Potential role for TCD-directed antiplatelet agents in symptomatic carotid artery dissection. Stroke 2006;37(3):767. 17. Zuromskis T, Wetterholm R, Lindqvist JF, et al. Prevalence of micro-emboli in symptomatic high grade carotid artery disease: a transcranial Doppler study. Eur J Vasc Endovasc Surg 2008;35(5):534–40. 18. Alexandrov AV, Babikian VL, Adams RJ, et al. The evolving role of transcranial Doppler in stroke prevention and treatment. J Stroke Cerebrovasc Dis 1998;7(2):101–4. 19. Roy J, Akhtar N, Watson T, et al. Transcranial Doppler microembolic signal monitoring is useful in diagnosis and treatment of carotid artery dissection: two case reports. J Neuroimaging 2007;17(4):350–2. 20. Sfyroeras GS, Karkos CD, Arsos G, et al. Cerebral hyperperfusion after carotid stenting: a transcranial doppler and spect study. Vasc Endovascular Surg 2009;43:150–6. 21. Adhiyaman V, Alexander S. Cerebral hyperperfusion syndrome following carotid endarterectomy. Q J Med 2007;100(4):239–44. 22. Ogasawara K, Sakai N, Kuroiwa T, et al. Intracranial hemorrhage associated with cerebral hyperperfusion syndrome following carotid endarterectomy and carotid artery stenting: retrospective review of 4494 patients. J Neurosurg 2007;107(6):1130–6. 23. Jansen C, Sprengers AM, Moll FL, et al. Prediction of intracerebral haemorrhage after carotid endarterectomy by clinical criteria and intraoperative transcranial Doppler monitoring. Eur J Vasc Surg 1994;8(3): 303–8. 24. Jansen C, Sprengers AM, Moll FL, et al. Prediction of intracerebral haemorrhage after carotid endarterectomy by clinical criteria and intraoperative transcranial Doppler monitoring: results of 233 operations. Eur J Vasc Surg 1994;8(2):220–5. 25. Magee TR, Davies AH, Horrocks M. Transcranial Doppler evaluation of cerebral hyperperfusion syndrome after carotid endarterectomy. Eur J Vasc Surg 1994;8(1):104–6. 26. Riles TS, Imparato AM, Jacobowitz GR, et al. The cause of perioperative stroke after carotid endarterectomy. J Vasc Surg 1994;19(2):206–16. 27. Spencer MP. Transcranial Doppler monitoring and causes of stroke from carotid endarterectomy. Stroke 1997;28(4):685–91. 28. Fodale V, Schifilliti D, Conti A, et al. Transcranial Doppler and anesthetics. Acta Anaesthesiol Scand 2007;51(7):839–47. 29. Lam AM, Matta BF, Mayberg TS, et al. Change in cerebral blood flow velocity with onset of EEG silence during inhalation anesthesia in humans: evidence of flow-metabolism coupling? J Cereb Blood Flow Metab 1995;15(4):714–7. 30. Matta BF, Mayberg TS, Lam AM. Direct cerebrovasodilatory effects of halothane, isoflurane, and desflurane during propofol-induced isoelectric electroencephalogram in humans. Anesthesiology 1995;83(5):980–5. 31. Molnár C, Settakis G, Sárkány P, et al. Effect of sevoflurane on cerebral blood flow and cerebrovascular resistance at surgical level of anaesthesia: a transcranial Doppler study. Eur J Anaesthesiol 2006;24(02):179–84. 32. Matta BF, Heath KJ, Tipping K, et al. Direct cerebral vasodilatory effects of sevoflurane and isoflurane. Anesthesiology 1999;91(3):677–80. 33. Bundgaard H, von Oettingen G, Larsen KM, et al. Effects of sevoflurane on intracranial pressure, cerebral blood flow and cerebral metabolism: a dose-response study in patients subjected to craniotomy for cerebral tumours. Acta Anaesthesiol Scand 1998;42(6):621–7. 34. Wong GT, Luginbuehl I, Karsli C, et al. The effect of sevoflurane on cerebral autoregulation in young children as assessed by the transient hyperemic response. Anesth Analg 2006;102(4):1051–5. 35. Nishiyama T, Matsukawa T, Yokoyama T, et al. Cerebrovascular carbon dioxide reactivity during general anesthesia: a comparison between sevoflurane and isoflurane. Anesth Analg 1999;89(6):1437–41.

36. Bedforth NM, Hardman JG, Nathanson MH. Cerebral hemodynamic response to the introduction of desflurane: a comparison with sevoflurane. Anesth Analg 2000;91(1):152–5. 37. Bedforth NM, Girling KJ, Skinner HJ, et al. Effects of desflurane on cerebral autoregulation. Br J Anaesth 2001;87(2):193–7. 38. Brenet O, Granry JC, Poirier N, et al. The effect of desflurane on cerebral blood flow velocity and cerebrovascular reactivity to CO2 in children. Ann Fr Anesth Reanim 1998;17(3):227–33. 39. Summors AC, Gupta AK, Matta BF. Dynamic cerebral autoregulation during sevoflurane anesthesia: a comparison with isoflurane. Anesth Analg 1999;88(2):341–5. 40. McCulloch TJ, Boesel TW, Lam AM. The effect of hypocapnia on the autoregulation of cerebral blood flow during administration of isoflurane. Anesth Analg 2005;100(5):1463–7. 41. Leon JE, Bissonnette B. Cerebrovascular responses to carbon dioxide in children anaesthetized with halothane and isoflurane. Can J Anaesth 1991;38(7):817–25. 42. Lam AM, Mayberg TS, Eng CC, et al. Nitrous oxide-isoflurane anesthesia causes more cerebral vasodilation than an equipotent dose of isoflurane in humans. Anesth Analg 1994;78(3):462–8. 43. Matta BF, Lam AM. Nitrous oxide increases cerebral blood flow velocity during pharmacologically induced EEG silence in humans. J Neurosurg Anesthesiol 1995;7(2):89–93. 44. Iacopino DG, Conti A, Battaglia C, et al. Transcranial Doppler ultrasound study of the effects of nitrous oxide on cerebral autoregulation during neurosurgical anesthesia: a randomized controlled trial. J Neurosurg 2003;99(1):58–64.

Section I—Background

81

45. Aono M, Sato J, Nishino T. Nitrous oxide increases normocapnic cerebral blood flow velocity but does not affect the dynamic cerebrovascular response to step changes in end-tidal P(CO2) in humans. Anesth Analg 1999;89(3):684–9. 46. Conti A, Iacopino DG, Fodale V, et al. Cerebral haemodynamic changes during propofol-remifentanil or sevoflurane anaesthesia: transcranial Doppler study under bispectral index monitoring. Br J Anaesth 2006;97(3):333–9. 47. Strebel S, Lam AM, Matta B, et al. Dynamic and static cerebral autoregulation during isoflurane, desflurane, and propofol anesthesia. Anesthesiology 1995;83(1):66–76. 48. Matta BF, Lam AM, Strebel S, et al. Cerebral pressure autoregulation and carbon dioxide reactivity during propofol-induced EEG suppression. Br J Anaesth 1995;74(2):159–63. 49. Thiel A, Zickmann B, Roth H, et al. Effects of intravenous anesthetic agents on middle cerebral artery blood flow velocity during induction of general anesthesia. J Clin Monit 1995;11(2):92–8. 50. Kochs E, Werner C, Hoffman WE, et al. Concurrent increases in brain electrical activity and intracranial blood flow velocity during low-dose ketamine anaesthesia. Can J Anaesth 1991;38(7):826–30. A complete list of references for this chapter can be found online at www.expertconsult.com.

Section I—Background 81.e1



References 1. Fukui K, Morioka T, Hashiguchi K, et al. Relationship between regional cerebral blood flow and electrocorticographic activities under sevoflurane and isoflurane anesthesia. J Clin Neurophysiol 2010;27(2):110–5. 2. Mielck F, Brauer A, Radke O, et al. Changes of jugular venous blood temperature associated with measurements of cerebral blood flow using the transcerebral double-indicator dilution technique. Eur J Anaesthesiol 2004:289–95. 3. Yoshitani K, Kawaguchi M, Iwata M, et al. Comparison of changes in jugular venous bulb oxygen saturation and cerebral oxygen saturation during variations of haemoglobin concentration under propofol and sevoflurane anaesthesia. Br J Anaesth 2005;94(3):341–6. 4. Matta BF, Lam AM, Mayberg TS, et al. A critique of the intraoperative use of jugular venous bulb catheters during neurosurgical procedures. Anesth Analg 1994;79(4):745–50. 5. Czosnyka M, Smielewski P, Kirkpatrick P, et al. Continuous assessment of the cerebral vasomotor reactivity in head injury. Neurosurgery 1997; 41:11–7. 6. Lam AM, Newell DW. Intraoperative use of transcranial Doppler ultrasonography. Neurosurg Clin N Am 1996;7:709–22. 7. Kincaid MS. Transcranial Doppler ultrasonography: a diagnostic tool of increasing utility. Curr Opin Anaesthesiol 2008;21(5):552–9. 8. Schatlo B, Pluta RM. Clinical applications of transcranial Doppler sonography. Rev Rec Clin Trials 2007;2(1):49–57. 9. Ogasawara K, Suga Y, Sasaki M, et al. Intraoperative microemboli and low middle cerebral artery blood flow velocity are additive in predicting development of cerebral ischemic events after carotid endarterectomy. Stroke 2008;39:3088–91. 10. Ackerstaff RG, Moons KG, van de Vlasakker CJ, et al. Association of intraoperative transcranial Doppler monitoring variables with stroke from carotid endarterectomy. Stroke 2000;31(8):1817–23. 11. Halsey JH. Risks and benefits of shunting in carotid endarterectomy. The International Transcranial Doppler Collaborators. Stroke 1992;23(11):1583–7. 12. Moritz S, Kasprzak P, Arlt M, et al. Accuracy of cerebral monitoring in detecting cerebral ischemia during carotid endarterectomy: a comparison of transcranial Doppler sonography, near-infrared spectroscopy, stump pressure, and somatosensory evoked potentials. Anesthesiology 2007; 107(4):563–9. 13. Ackerstaff RGA. Cerebral circulation monitoring in carotid endarterectomy and carotid artery stenting. Front Neurol Neurosci 2006;21229–38. 14. Gossetti B, Gattuso R, Irace L, et al. Embolism to the brain during carotid stenting and surgery. Acta Chir Belg 2007;107(2):151–4. 15. Telman G, Kouperberg E, Eran A, et al. Microemboli in MCA ipsilateral to occluded common carotid artery: an observation and short review of the literature. Neurol Res 2008;30(7):684–6. 16. Imray CHE, Pattinson KTS. Potential role for TCD-directed antiplatelet agents in symptomatic carotid artery dissection. Stroke 2006;37(3):767. 17. Zuromskis T, Wetterholm R, Lindqvist JF, et al. Prevalence of micro-emboli in symptomatic high grade carotid artery disease: a transcranial Doppler study. Eur J Vasc Endovasc Surg 2008;35(5):534–40. 18. Alexandrov AV, Babikian VL, Adams RJ, et al. The evolving role of transcranial Doppler in stroke prevention and treatment. J Stroke Cerebrovasc Dis 1998;7(2):101–4. 19. Roy J, Akhtar N, Watson T, et al. Transcranial Doppler microembolic signal monitoring is useful in diagnosis and treatment of carotid artery dissection: two case reports. J Neuroimaging 2007;17(4):350–2. 20. Sfyroeras GS, Karkos CD, Arsos G, et al. Cerebral hyperperfusion after carotid stenting: a transcranial doppler and spect study. Vasc Endovascular Surg 2009;43:150–6. 21. Adhiyaman V, Alexander S. Cerebral hyperperfusion syndrome following carotid endarterectomy. Q J Med 2007;100(4):239–44. 22. Ogasawara K, Sakai N, Kuroiwa T, et al. Intracranial hemorrhage associated with cerebral hyperperfusion syndrome following carotid endarterectomy and carotid artery stenting: retrospective review of 4494 patients. J Neurosurg 2007;107(6):1130–6. 23. Jansen C, Sprengers AM, Moll FL, et al. Prediction of intracerebral haemorrhage after carotid endarterectomy by clinical criteria and intraoperative transcranial Doppler monitoring. Eur J Vasc Surg 1994;8(3):303–8. 24. Jansen C, Sprengers AM, Moll FL, et al. Prediction of intracerebral haemorrhage after carotid endarterectomy by clinical criteria and intraoperative transcranial Doppler monitoring: results of 233 operations. Eur J Vasc Surg 1994;8(2):220–5.

25. Magee TR, Davies AH, Horrocks M. Transcranial Doppler evaluation of cerebral hyperperfusion syndrome after carotid endarterectomy. Eur J Vasc Surg 1994;8(1):104–6. 26. Riles TS, Imparato AM, Jacobowitz GR, et al. The cause of perioperative stroke after carotid endarterectomy. J Vasc Surg 1994;19(2):206–16. 27. Spencer MP. Transcranial Doppler monitoring and causes of stroke from carotid endarterectomy. Stroke 1997;28(4):685–91. 28. Fodale V, Schifilliti D, Conti A, et al. Transcranial Doppler and anesthetics. Acta Anaesthesiol Scand 2007;51(7):839–47. 29. Lam AM, Matta BF, Mayberg TS, et al. Change in cerebral blood flow velocity with onset of EEG silence during inhalation anesthesia in humans: evidence of flow-metabolism coupling? J Cereb Blood Flow Metab 1995;15(4):714–7. 30. Matta BF, Mayberg TS, Lam AM. Direct cerebrovasodilatory effects of halothane, isoflurane, and desflurane during propofol-induced isoelectric electroencephalogram in humans. Anesthesiology 1995;83(5):980–5. 31. Molnár C, Settakis G, Sárkány P, et al. Effect of sevoflurane on cerebral blood flow and cerebrovascular resistance at surgical level of anaesthesia: a transcranial Doppler study. Eur J Anaesthesiol 2006;24(02):179–84. 32. Matta BF, Heath KJ, Tipping K, et al. Direct cerebral vasodilatory effects of sevoflurane and isoflurane. Anesthesiology 1999;91(3):677–80. 33. Bundgaard H, von Oettingen G, Larsen KM, et al. Effects of sevoflurane on intracranial pressure, cerebral blood flow and cerebral metabolism: a dose-response study in patients subjected to craniotomy for cerebral tumours. Acta Anaesthesiol Scand 1998;42(6):621–7. 34. Wong GT, Luginbuehl I, Karsli C, et al. The effect of sevoflurane on cerebral autoregulation in young children as assessed by the transient hyperemic response. Anesth Analg 2006;102(4):1051–5. 35. Nishiyama T, Matsukawa T, Yokoyama T, et al. Cerebrovascular carbon dioxide reactivity during general anesthesia: a comparison between sevoflurane and isoflurane. Anesth Analg 1999;89(6):1437–41. 36. Bedforth NM, Hardman JG, Nathanson MH. Cerebral hemodynamic response to the introduction of desflurane: a comparison with sevoflurane. Anesth Analg 2000;91(1):152–5. 37. Bedforth NM, Girling KJ, Skinner HJ, et al. Effects of desflurane on cerebral autoregulation. Br J Anaesth 2001;87(2):193–7. 38. Brenet O, Granry JC, Poirier N, et al. The effect of desflurane on cerebral blood flow velocity and cerebrovascular reactivity to CO2 in children. Ann Fr Anesth Reanim 1998;17(3):227–33. 39. Summors AC, Gupta AK, Matta BF. Dynamic cerebral autoregulation during sevoflurane anesthesia: a comparison with isoflurane. Anesth Analg 1999;88(2):341–5. 40. McCulloch TJ, Boesel TW, Lam AM. The effect of hypocapnia on the autoregulation of cerebral blood flow during administration of isoflurane. Anesth Analg 2005;100(5):1463–7. 41. Leon JE, Bissonnette B. Cerebrovascular responses to carbon dioxide in children anaesthetized with halothane and isoflurane. Can J Anaesth 1991;38(7):817–25. 42. Lam AM, Mayberg TS, Eng CC, et al. Nitrous oxide-isoflurane anesthesia causes more cerebral vasodilation than an equipotent dose of isoflurane in humans. Anesth Analg 1994;78(3):462–8. 43. Matta BF, Lam AM. Nitrous oxide increases cerebral blood flow velocity during pharmacologically induced EEG silence in humans. J Neurosurg Anesthesiol 1995;7(2):89–93. 44. Iacopino DG, Conti A, Battaglia C, et al. Transcranial Doppler ultrasound study of the effects of nitrous oxide on cerebral autoregulation during neurosurgical anesthesia: a randomized controlled trial. J Neurosurg 2003;99(1):58–64. 45. Aono M, Sato J, Nishino T. Nitrous oxide increases normocapnic cerebral blood flow velocity but does not affect the dynamic cerebrovascular response to step changes in end-tidal P(CO2) in humans. Anesth Analg 1999;89(3):684–9. 46. Conti A, Iacopino DG, Fodale V, et al. Cerebral haemodynamic changes during propofol-remifentanil or sevoflurane anaesthesia: transcranial Doppler study under bispectral index monitoring. Br J Anaesth 2006;97(3):333–9. 47. Strebel S, Lam AM, Matta B, et al. Dynamic and static cerebral autoregulation during isoflurane, desflurane, and propofol anesthesia. Anesthesiology 1995;83(1):66–76. 48. Matta BF, Lam AM, Strebel S, et al. Cerebral pressure autoregulation and carbon dioxide reactivity during propofol-induced EEG suppression. Br J Anaesth 1995;74(2):159–63. 49. Thiel A, Zickmann B, Roth H, et al. Effects of intravenous anesthetic agents on middle cerebral artery blood flow velocity during induction of general anesthesia. J Clin Monit 1995;11(2):92–8.

81.e2 Section I—Background 50. Kochs E, Werner C, Hoffman WE, et al. Concurrent increases in brain electrical activity and intracranial blood flow velocity during low-dose ketamine anaesthesia. Can J Anaesth 1991;38(7):826–30. 51. Mayberg TS, Lam AM, Matta BF, et al. Ketamine does not increase cerebral blood flow velocity or intracranial pressure during isoflurane/nitrous oxide anesthesia in patients undergoing craniotomy. Anesth Analg 1995;81(1):84–9. 52. Engelhard K, Werner C, Möllenberg O, et al. S(+)-ketamine/propofol maintain dynamic cerebrovascular autoregulation in humans. Can J Anaesth 2001;48(10):1034–9. 53. Ogawa Y, Iwasaki K, Aoki K, et al. Dexmedetomidine weakens dynamic cerebral autoregulation as assessed by transfer function analysis and the thigh cuff method. Anesthesiology 2008;109(4):642–50. 54. Drummond JC, Dao AV, Roth DM, et al. Effect of dexmedetomidine on cerebral blood flow velocity, cerebral metabolic rate, and carbon dioxide response in normal humans. Anesthesiology 2008;108(2):225–32. 55. Kofke WA, Dong ML, Bloom M, et al. Transcranial Doppler ultrasonography with induction of anesthesia for neurosurgery. J Neurosurg Anesthesiol 1994;6(2):89–97. 56. Thiel A, Zickmann B, Roth H, et al. Effects of intravenous anesthetic agents on middle cerebral artery blood flow velocity during induction of general anesthesia. J Clin Monit 1995;11(2):92–8. 57. Cold GE, Eskesen V, Eriksen H, et al. CBF and CMRO2 during continuous etomidate infusion supplemented with N2O and fentanyl in patients with supratentorial cerebral tumour: a dose-response study. Acta Anaesthesiol Scand 1985;29(5):490–4. 58. Cheng MA, Hoffman WE, Baughman VL, et al. The effects of midazolam and sufentanil sedation on middle cerebral artery blood flow velocity in awake patients. J Neurosurg Anesthesiol 1993;5(4):232–6. 59. Hänel F, Werner C, von Knobelsdorff G, et al. The effects of fentanyl and sufentanil on cerebral hemodynamics. J Neurosurg Anesthesiol 1997;9(3):223–7. 60. Fodale V, Schifilliti D, Praticò C, et al. Remifentanil and the brain. Acta Anaesthesiol Scand 2008;52(3):319–26. 61. Frost EA. Inhalation anaesthetic agents in neurosurgery. Br J Anaesth 1984;56(Suppl 1):47S-56S. 62. Kennedy RR, Minto C, Seethepalli A. Effect-site half-time for burst suppression is longer than for hypnosis during anaesthesia with sevoflurane. Br J Anaesth 2008;100(1):72–7. 63. Schwartz AE, Tuttle RH, Poppers PJ. Electroencephalographic burst suppression in elderly and young patients anesthetized with isoflurane. Anesth Analg 1989;68(1):9–12. 64. Voss LJ, Seleigh JW, Barnard JPM, et al. The howling cortex: seizures and general anesthetic drugs. Anesth Analg 2008;107:1689–703. 65. Kofke WA. Anesthetic management of the patient with epilepsy or prior seizures. Curr Opin Anaesthesiol 2010;23:391–9. 66. Mäkelä JP, Iivanainen M, Pieninkeroinen IP, et al. Seizures associated with propofol anesthesia. Epilepsia 1993;34(5):832–5. 67. Jääskeläinen SK, Kaisti K, Suni L, et al. Sevoflurane is epileptogenic in healthy subjects at surgical levels of anesthesia. Neurology 2003; 61(8):1073–8. 68. Mustola ST, Baer GA, Toivonen JK, et al. Electroencephalographic burst suppression versus loss of reflexes anesthesia with propofol or thiopental: differences of variance in the catecholamine and cardiovascular response to tracheal intubation. Anesth Analg 2003;97(4):1040–5. 69. Souter MJ, Rozet I, Ojemann JG, et al. Dexmedetomidine sedation during awake craniotomy for seizure resection: effects on electrocorticography. J Neurosurg Anesthesiol 2007;19(1):38–44. 70. Rozet I, Muangman S, Vavilala MS, et al. Clinical experience with dexmedetomidine for implantation of deep brain stimulators in Parkinson’s disease. Anesth Analg 2006;103:1244–8. 71. Lam AM, Sharar SR, Mayberg TS, et al. Isoflurane compared with nitrous oxide anaesthesia for intraoperative monitoring of somatosensory-evoked potentials. Can J Anaesth 1994;41(4):295–300. 72. Manninen PH, Lam AM, Nicholas JF. The effects of isoflurane and isoflurane-nitrous oxide anesthesia on brainstem auditory evoked potentials in humans. Anesth Analg 1985;64(1):43–7. 73. de Haan P, Kalkman CJ. Spinal cord monitoring: somatosensory- and motor-evoked potentials. Anesthesiol Clin N Am 2001;19(4):923–45. 74. Calancie B, Harris W, Brindle GF, et al. Threshold-level repetitive transcranial electrical stimulation for intraoperative monitoring of central motor conduction. J Neurosurg 2001;95(2 Suppl):161–8. 75. MacDonald DB. Safety of intraoperative transcranial electrical stimulation motor evoked potential monitoring. J Clin Neurophysiol 2002;19(5): 416–29.

76. Lotto ML, Banoub M, Schubert A. Effects of anesthetic agents and physiologic changes on intraoperative motor evoked potentials. J Neurosurg Anesthesiol 2004;16(1):32–42. 77. Zentner J, Albrecht T, Heuser D. Influence of halothane, enflurane, and isoflurane on motor evoked potentials. Neurosurgery 1992;31(2):298–305. 78. Haghighi SS, Green KD, Oro JJ, et al. Depressive effect of isoflurane anesthesia on motor evoked potentials. Neurosurgery 1990;26(6):993–7. 79. Lyon R, Feiner J, Lieberman JA. Progressive suppression of motor evoked potentials during general anesthesia: the phenomenon of “anesthetic fade.” J Neurosurg Anesthesiol 2005;17(1):13–19. 80. Ubags LH, Kalkman CJ, Been HD. Influence of isoflurane on myogenic motor evoked potentials to single and multiple transcranial stimuli during nitrous oxide/opioid anesthesia. Neurosurgery 1998;43(1):90–4. 81. Pelosi L, Stevenson M, Hobbs GJ, et al. Intraoperative motor evoked potentials to transcranial electrical stimulation during two anaesthetic regimens. Clin Neurophysiol 2001;112(6):1076–87. 82. Pechstein U, Nadstawek J, Zentner J, et al. Isoflurane plus nitrous oxide versus propofol for recording of motor evoked potentials after high frequency repetitive electrical stimulation. Electroencephalogr Clin Neurophysiol 1998;108(2):175–81. 83. Lo Y, Dan Y, Tan YE, et al. Intraoperative motor-evoked potential monitoring in scoliosis surgery: comparison of desflurane/nitrous oxide with propofol total intravenous anesthetic regimens. J Neurosurg Anesthesiol 2006;18(3):211–4. 84. Kawaguchi M, Inoue S, Kakimoto M, et al. The effect of sevoflurane on myogenic motor-evoked potentials induced by single and paired transcranial electrical stimulation of the motor cortex during nitrous oxide/ ketamine/fentanyl anesthesia. J Neurosurg Anesthesiol 1998;10(3):131–6. 85. Reinacher PC, Priebe H, Blumrich W, et al. The effects of stimulation pattern and sevoflurane concentration on intraoperative motor-evoked potentials. Anesth Analg 2006;102(3):888–95. 86. Rampil IJ, King BS. Volatile anesthetics depress spinal motor neurons. Anesthesiology 1996;85(1):129–34. 87. Ubags LH, Kalkman CJ, Been HD, et al. Differential effects of nitrous oxide and propofol on myogenic transcranial motor evoked responses during sufentanil anaesthesia. Br J Anaesth 1997;79(5):590–4. 88. van Dongen EP, ter Beek HT, Schepens MA, et al. The influence of nitrous oxide to supplement fentanyl/low-dose propofol anesthesia on transcranial myogenic motor-evoked potentials during thoracic aortic surgery. J Cardiothorac Vasc Anesth 1999;13(1):30–4. 89. van Dongen EP, ter Beek HT, Schepens MA, et al. Effect of nitrous oxide on myogenic motor potentials evoked by a six pulse train of transcranial electrical stimuli: a possible monitor for aortic surgery. Br J Anaesth 1999;82(3):323–8. 90. Scheufler KM, Reinacher PC, Blumrich W, et al. The modifying effects of stimulation pattern and propofol plasma concentration on motor-evoked potentials. Anesth Analg 2005;100(2):440–7. 91. Kalkman CJ, Drummond JC, Ribberink AA, et al. Effects of propofol, etomidate, midazolam, and fentanyl on motor evoked responses to transcranial electrical or magnetic stimulation in humans. Anesthesiology 1992;76(4):502–9. 92. Inoue S, Kawaguchi M, Kakimoto M, et al. Amplitudes and intrapatient variability of myogenic motor evoked potentials to transcranial electrical stimulation during ketamine/N2O- and propofol/N2O-based anesthesia. J Neurosurg Anesthesiol 2002;14(3):213–7. 93. Ubags LH, Kalkman CJ, Been HD, et al. The use of ketamine or etomidate to supplement sufentanil/N2O anesthesia does not disrupt monitoring of myogenic transcranial motor evoked responses. J Neurosurg Anesthesiol 1997;9(3):228–33. 94. Zaarour C, Engelhardt T, Strantzas S, et al. Effect of low-dose ketamine on voltage requirement for transcranial electrical motor evoked potentials in children. Spine 2007;32(22):E627–30. 95. Lang EW, Beutler AS, Chesnut RM, et al. Myogenic motor-evoked potential monitoring using partial neuromuscular blockade in surgery of the spine. Spine 1996;21(14):1676–86. 96. Tobias JD, Goble TJ, Bates G, et al. Effects of dexmedetomidine on intraoperative motor and somatosensory evoked potential monitoring during spinal surgery in adolescents. Paediatr Anaesth 2008;18:1082–8. 97. Bala E, Sessler DI, Nair DR, et al. Motor and somatosensory evoked potentials are well maintained in patients given dexmedetomidine during spine surgery. Anesthesiology 2008;109(3):417–25. 98. Mahmoud M, Sadhasivam S, Salisbury S, et al. Susceptibility of transcranial electric motor-evoked potentials to varying targeted blood levels of dexmedetomidine during spine surgery. Anesthesiology 2010; 112(6):1364–73.

99. Mahmoud M, Sadhasivam S, Sestokas AK, et al. Loss of transcranial electric motor evoked potentials during pediatric spine surgery with dexmedetomidine. Anesthesiology 2007;106(2):393–6. 100. Scheufler K, Zentner J. Total intravenous anesthesia for intraoperative monitoring of the motor pathways: an integral view combining clinical and experimental data. J Neurosurg 2002;96(3):571–9. 101. van Dongen EP, ter Beek HT, Schepens MA, et al.Within-patient variability of myogenic motor-evoked potentials to multipulse transcranial electrical stimulation during two levels of partial neuromuscular blockade in aortic surgery. Anesth Analg 1999;88(1):22–7. 102. Hayashi H, Kawaguchi M, Yamamoto Y, et al. The application of tetanic stimulation of the unilateral tibial nerve before transcranial stimulation can augment the amplitudes of myogenic motor-evoked potentials from the muscles in the bilateral upper and lower limbs. Anesth Analg 2008; 107(1):215–20. 103. Yamamoto Y, Kawaguchi M, Hayashi H, et al. The effects of the neuromuscular blockade levels on amplitudes of posttetanic motor-evoked potentials and movement in response to transcranial stimulation in patients receiving propofol and fentanyl anesthesia. Anesth Analg 2008;106(3):930–4. 104. Smith M. Perioperative uses of transcranial perfusion monitoring. Anesthesiol Clin 2007;25(3):557–77. 105. Duffy CM, Manninen PH, Chan A, et al. Comparison of cerebral oximeter and evoked potential monitoring in carotid endarterectomy. Can J Anaesth 1997;44(10):1077–81. 106. Bhatia R, Hampton T, Malde S, et al. The application of near-infrared oximetry to cerebral monitoring during aneurysm embolization: a comparison with intraprocedural angiography. J Neurosurg Anesthesiol 2007;19(2):97–104.

Section I—Background 81.e3 107. Dujovny M, Slavin KV, Hernandez G, et al. Use of cerebral oximetry to monitor brain oxygenation reserves for skull base surgery. Skull Base Surg 1994;4(3):117–21. 108. Kakihana Y, Matsunaga A, Yasuda T, et al. Brain oxymetry in the operating room: current status and future directions with particular regard to cytochrome oxidase. J Biomed Opt 2008;13(3):033001. 109. McDonagh DL, McDaniel MR, Monk TG. The effect of intravenous indigo carmine on near-infrared cerebral oximetry. Anesth Analg 2007;105(3): 704–6. 110. Patel J, Marks K, Roberts I, et al. Measurement of cerebral blood flow in newborn infants using near infrared spectroscopy with indocyanine green. Pediatr Res 1998;43(1):34–9. 111. McCormick PW, Stewart M, Lewis G, et al. Intracerebral penetration of infrared light. Technical note. J Neurosurg 1992;76(2):315–8. 112. Nishikawa K, Kanemaru Y, Hagiwara R, et al. The influence of sevoflurane on the bispectral index, regional cerebral oxygen saturation, and propofol concentration during propofol/N2O anesthesia. J Clin Monit Comput 2006;20(6):415–20. 113. Fassoulaki A, Kaliontzi H, Petropoulos G, et al. The effect of desflurane and sevoflurane on cerebral oximetry under steady-state conditions. Anesth Analg 2006;102(6):1830–5. 114. Kanemaru Y, Nishikawa K, Goto F. Bispectral index and regional cerebral oxygen saturation during propofol/N2O anesthesia. Can J Anaesth. 2006;53(4):363–9. 115. Iwasaki K, Nomoto Y, Ishiwata M, et al. Vital capacity induction with 8% sevoflurane and N2O causes cerebral hyperemia. J Anesth 2003;17(1):3–7. 116. Lovell AT, Owen-Reece H, Elwell CE, et al. Continuous measurement of cerebral oxygenation by near infrared spectroscopy during induction of anesthesia. Anesth Analg 1999;88(3):554–8.

II

Chapter

10

 

Clinical Assessment in the Neurocritical Care Unit Ramani Balu, John A. Detre, and Joshua M. Levine

Introduction Many patients in the neurocritical care unit (NCCU) are in coma, have altered consciousness, or have a disease process that may lead to altered consciousness. Coma and other disorders of consciousness are common clinical problems that indicate a severe disturbance of brain function. Monitoring and management of patients with disturbed consciousness depend in large part on the underlying etiology. The principal means of monitoring the comatose patient are clinical neurologic examinations, the use of rating scales, neuroimaging, and electrophysiologic tests. In addition, a variety of invasive and noninvasive monitors of brain function is available and discussed in other chapters of this book. Goals of monitoring include establishing an etiologic diagnosis and excluding coma mimics, determining the location and severity of injury, assessing response to therapy, and determining prognosis. This chapter provides an overview of the anatomy of consciousness, the general clinical approach to the coma patient, and neurologic assessment, with a focus on the clinical examination, quantitative coma scales, and electrophysiologic and imaging studies that may provide insight into the prognosis of coma. In addition, other critical care scores that provide insight into extracerebral pathophysiology are briefly discussed.

Anatomy of Brain Circuits Involved in Arousal, Alertness, and Conscious Behavior Level of arousal (alertness) depends on the coordinated activity of multiple brainstem nuclei that send projections to diencephalic targets in the thalamus and hypothalamus and diffusely to the cerebral cortex. Areas of the thalamus that receive information from arousal centers in the brainstem in turn send widespread projections to both cerebral hemispheres. Thus isolated brainstem lesions, bilateral thalamic damage, or diffuse bilateral cerebral injury can cause global impairments of consciousness and coma. An important corollary to this general rule is that unilateral lesions should not cause global reductions in consciousness unless they are large enough to produce significant mass effect on the contralateral hemisphere or there is a preexisting contralateral lesion. 84

Because brainstem arousal centers are close to other important nuclei and tracts that control eye movements and breathing, the location of lesions causing global impairments in consciousness often can be readily determined by careful physical examination. In the early 20th century Baron Constantin von Economo first proposed the concept that specific brainstem nuclei control arousal and alertness after his detailed clinicopathologic study of patients with encephalitis lethargica.1 The vast majority of these patients had profound somnolence along with parkinsonism and focal oculomotor abnormalities, and spent only a few hours awake each day. Postmortem analysis of these patients demonstrated damage to the paramedian reticular formation near the junction between the midbrain and the diencephalon. A small subset of patients who suffered from debilitating insomnia in contrast had damage to the anterior hypothalamus. Based on these results, von Economo proposed that a specific arousal-promoting center exists in the midbrain, and a separate sleep-promoting center is in the hypothalamus. Studies by Morruzi and Magoun in the 1940s2 showed that selective lesions of the midbrain paramedian reticular formation in cats caused electroencephalographic slowing and behavioral unresponsiveness similar to sleep. Lesions in the midbrain that contained ascending sensory pathways caused defects in somatosensory and auditory-evoked responses but had no effect on the normal desynchronized electroencephalographic pattern seen in awake animals. These investigators coined the term ascending reticular activating system (ARAS) to describe the critical function of the paramedian reticular formation in alertness. Subsequent lesion studies in humans have confirmed the importance of the upper brainstem to promote and maintain behavioral arousal. Specifically, injury to either the paramedian midbrain or bilateral dorsolateral pontine tegmentum causes coma.3 Lesions of other parts of the brainstem outside of this ascending arousal system, although often debilitating, do not cause global impairments of consciousness.3,4 Multiple brainstem nuclei that form distinct cholinergic and monoaminergic projection systems are now known to constitute the ascending arousal system.4,5 Although these nuclei are not all located within the paramedian midbrain reticular formation, their output fibers in general course through this structure on their way to targets in the diencephalon and cerebral cortex. © Copyright 2013 Elsevier Inc. All rights reserved.



Cholinergic Projection Systems The main source of arousal promoting inputs to the thalamus is from the pedunculopontine and laterodorsal tegmental nuclei in the pons.5-8 These areas send cholinergic projections through the midbrain reticular formation mainly to the intralaminar thalamic nuclei and the thalamic reticular nucleus, although they also project to the thalamic relay nuclei. The intralaminar nuclei are excited by their ascending cholinergic input and send widespread diffuse excitatory projections to the cortex. The thalamic reticular nucleus, by contrast, sends local inhibitory projections to thalamocortical relay nuclei, and its principal neurons are inhibited by acetylcholine. Thus activity in the pedunculopontine and laterodorsal tegmental nuclei—which is greatest during awakening and decreases during sleep—both activate diffuse excitatory projections from the intralaminar nuclei and disinhibit excitatory thalamocortical relay neurons by inhibiting the reticular nucleus. A second source of cholinergic inputs arises from the basal forebrain. These neurons receive inputs from brainstem monoaminergic projection systems (discussed following) and neighboring excitatory brainstem nuclei and send widespread projections throughout the cerebral cortex.5,9 Interestingly, single axons from the basal forebrain have patchy, spatially defined projection patterns to defined subsets of cortical neurons.10 Thus regulated activity of different parts of the basal forebrain can have spatially restricted effects on different cortical areas.

Monoaminergic Projection Systems Multiple monoaminergic projection systems also provide telencephalic input from the brainstem and diencephalon that influence alertness and conscious behavior. Activity of these monoaminergic projections has complex effects on cortical activity and often decreases background activity but increases the responsiveness of a cortical neuron to its best stimulus, thereby increasing signal to noise ratio.11-15 These systems therefore have critical functions in regulating attention, memory, and other higher order cognitive processes in addition to providing a more general arousal-promoting stimulus. Dopaminergic neurons are found in the midbrain in both the substantia nigra and in the ventral tegmental area.5 Projections from the substantia nigra terminate in the basal ganglia and are crucial for motor control and modulation. The ventral tegmental projections course through the midbrain reticular formation and provide a mesolimbic projection to the nucleus accumbens, basal forebrain, cingulate cortex, hippocampus, and amygdala and a mesocortical projection to the prefrontal cortex.5 Mesolimbic dopaminergic pathways are involved in reward-mediated behavior,16,17 and overactivity of these projections is thought to be central in the pathogenesis of thought disorders such as schizophrenia.18 Mesocortical projections likely are involved in attention and working memory.19 Noradrenergic projections to the cerebral hemispheres arise mainly from the locus ceruleus, located in the upper pons near the fourth ventricle. Locus ceruleus activity increases with awakening, and this area likely is important in behavioral state switching (i.e., from sleep to wakefulness).7,8 These noradrenergic systems, like serotonergic systems (see following text), also are pharmaceutical targets in mood disorders.20,21

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Multiple midline brainstem areas throughout the midbrain, pons, and medulla that comprise the raphe nuclei provide serotonergic input to the brain.5 Of these, the rostral raphe nuclei in the midbrain and pons project diffusely throughout the cortex, thalamus, and basal ganglia. Serotonin effects on these areas are complex and can be either excitatory or inhibitory. These pathways also are thought to play a major role in psychiatric diseases such as depression, anxiety, and obsessivecompulsive disorder.20,21 A widespread histaminergic pathway arises from the tuberomamillary nucleus in the posterior hypothalamus.5 Histaminergic neurons are important in sleep and arousal regulation, and activity of tuberomamillary nucleus neurons is greatest during waking and rapid eye movement (REM) sleep.4,7 Histamine receptor blockers that can cross the bloodbrain barrier, such as diphenhydramine, can exert a powerful sleep-promoting effect.4

Interactions Between Arousal-Promoting Brain Centers The anatomy of the pathways described previously and their aggregate importance in arousal have been recognized for decades. However, the specific ways in which these pathways interact to promote conscious behavior, attention, or memory and regulate the transitions between multiple behavioral states is only beginning to be elucidated. Other inputs, including the galanin and gamma aminobutyric acid–secreting (GABAergic) inputs from the ventrolateral preoptic (VLPO) area of the hypothalamus,7,8 orexin-containing neurons from the lateral hypothalamus, and descending cortical inputs provide modulatory control over the ARAS.8,22,23 Nevertheless, the concept of an ascending brainstem arousal system whose activity promotes alertness and conscious behavior remains invaluable clinically when evaluating patients with disorders of impaired consciousness.

Coma Etiology Causes of altered mental status and coma are protean, and can be divided into primary brain disorders and systemic derangements that secondarily affect brain function (Table 10.1). Primary brain disorders can be caused by structural abnormalities (e.g., cerebral infarction, tumors, subdural hematomas, intraparenchymal hemorrhages, and abscesses among others) that either directly distort the circuitry of the ascending arousal system or globally increase intracranial pressure (ICP), or by diffuse nonstructural disturbances such as seizures. Often both structural and nonstructural abnormalities may exist together in the same patient, for example, a patient with a cerebral abscess who develops seizures. Systemic disturbances cause encephalopathy through diffuse bilateral cerebral dysfunction and can include metabolic derangements, exposure to toxins, systemic infections, or diffuse encephalitis caused by primary central nervous system (CNS) infections, autoimmune processes, or paraneoplastic syndromes. The most common causes of coma are traumatic brain injury (TBI), hypoxic-ischemic encephalopathy (HIE), drug overdose, ischemic and hemorrhagic strokes, CNS infections, and brain herniation from space-occupying lesions. A detailed discussion of these conditions is beyond the scope of this

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Table 10.1  A Partial List of the Etiologies of Coma and Altered Mental Status PRIMARY BRAIN DISORDERS

Structural Lesions 1. Traumatic brain injury a. Diffuse axonal injury b. Contusions c. Subdural hematomas d. Epidural hematomas 2. Cerebrovascular disorders a. Ischemic strokes b. Spontaneous intracerebral hemorrhage c. Subarachnoid hemorrhage d. Hypoxic-ischemic encephalopathy e. Cerebral venous sinus thrombosis 3. Malignant disease a. Brain tumors 4. Infectious diseases a. Brain abscesses 5. Demyelinating disease a. Acute disseminated encephalomyelitis b. Central pontine myelinolysis 6. Hydrocephalus Nonstructural Disorders 1. Infectious diseases a. Bacterial meningoencephalitis b. Viral encephalitis 2. Malignant disease a. Carcinomatous or lymphomatous meningitis 3. Generalized seizures, status epilepticus 4. Basilar migraines SYSTEMIC DISORDERS

Toxic Encephalopathies 1. Medication overdose a. Opioids, benzodiazepines, barbiturates, tricyclics, etc. 2. Illicit drug exposure a. Opioids, alcohols, amphetamines, etc. 3. Environmental toxin exposure a. Carbon monoxide b. Heavy metals c. Pesticides Metabolic Encephalopathies 1. Hypoglycemia, hyperglycemia 2. Hyponatremia, hypernatremia 3. Hypercalcemia 4. Hepatic encephalopathy 5. Uremia 6. Vitamin deficiencies (thiamine, niacin) 7. Hypothermia, severe hyperthermia 8. Hypothyroidism, hyperthyroidism 9. Urea cycle disorders Infections 1. Urinary tract infections 2. Pneumonia 3. Sepsis Adapted from Stevens RD, Bhardwaj A. Approach to the comatose patient. Crit Care Med 2006;34(1):31–41.

chapter; however, a few warrant special mention because rapid diagnosis and urgent treatment are essential to limit brain injury. These include seizures, infections, acute hydrocephalus, herniation, ischemic and hemorrhagic strokes, subarachnoid hemorrhage (SAH), cerebral venous sinus thrombosis, hypertensive encephalopathy, and TBI.4

Differential Diagnosis (Mimics) of Coma and the Vegetative State Patients may become unresponsive from conditions that mimic coma or a vegetative state. Care must be taken not to consider these patients as comatose because they have no impairments of conscious behavior and often can communicate with clinical staff and other individuals if an appropriate communication system is devised.24 In the locked-in syndrome, destruction of the ventral pons leaves the patient quadriplegic and mute.4 Patients often are aware of their surroundings and may communicate only through vertical eye movements and blinking, which are spared. With more rostral pontine lesions, vertical eye movements and blinking are lost. In this state that can be likened to receiving a neuromuscular blocking agent without a sedative, the patient has no means of communication. Severe Guillain-Barré syndrome, botulism, and critical-illness neuropathy may similarly result in complete de-efferentation. Catatonia is a manifestation of severe psychiatric illness in which patients open their eyes, do not speak or follow commands, and may exhibit waxy flexibility.4,25 The remainder of the neurologic exam and the electroencephalogram (EEG) are normal. Akinetic mutism that results from bilateral medial frontal lobe injury is a profound form of abulia (lack of motivation) in which patients are unable to speak or to move, but open their eyes, occasionally track visual stimuli, and sometimes respond when prompted.26,27

Neurologic Examination of the Comatose Patient The initial neurologic examination of a patient with altered consciousness allows the lesion to be localized: this helps to narrow the list of etiologic possibilities. For example, integrity of brainstem function and absence of focal signs suggests a toxic or metabolic disorder. In contrast, asymmetric findings and brainstem dysfunction are more consistent with a structural etiology. The exam also is used to exclude conditions that may mimic coma. Serial examinations of the comatose patient over time are essential and provide information about treatment efficacy, progression of the primary process, and prognosis. The clinical examination of the comatose patient is discussed first, followed by some of the standardized scales that have been developed to evaluate coma (Fig. 10.1). The coma examination is focused on four elements: (1) determination of the patient’s level of arousal (wake­ fulness), (2) eye examination, (3) motor responses and presence of abnormal reflexes, and (4) observation of breathing patterns.

Level of Consciousness Patients who exhibit spontaneous eyes opening, verbalization attempts, moaning, tossing, reaching, leg crossing, yawning, coughing, or swallowing have a higher level of consciousness than those who do not. The examiner should next assess the patient’s response to a series of stimuli that escalate in intensity. The patient’s name should be called loudly. If there is no response, the examiner may stimulate the patient by gently shaking him or her. If this produces no response, the examiner should use a noxious stimulus, such as pressure

Section II—Clinical and Laboratory Assessment

Initial resuscitation Airway Breathing Circulation Cervical spine stabilization

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Full Outline of UnResponsiveness [FOUR] score, Reaction Level Scale 85 [RLS85], and Innsbruck Coma Score are discussed later in this chapter.

The Eye Examination Laboratory evaluation Serum glucose, electrolytes, blood gas, osmolality, liver and thyroid function tests, ammonia, complete blood count, toxicology screen

Coma examination

Initial/empiric treatment Hyperventilation, mannitol 0.75-1.25 g/kg if evidence of intercranial hypertension, herniation Thiamine (100 mg IV) then glucose (50 cc of 50% solution) Naloxone (0.4-2 mg IV q 3 minutes) Flumazenil (0.2 mg/min to maximum dose of 1 mg IV) if benzodiazepine overdose suspected Gastric lavage with activated charcoal if other drug intoxication suspected Antibiotic administration if meningoencephalitis suspected Induced hypothermia if comatose after VT/VF Cardiac arrest per ILCOR guidelines

Head CT if etiology unknown or structural lesion suspected

Detailed history and physical examination

Lumbar puncture, EEG, MRI as indicated Fig. 10.1  Algorithm for initial approach to the comatose patient. CT, Computed tomography; EEG, electroencephalogram; MRI, magnetic resonance imaging; ILCOR, International Liaison Committee on Resuscitation; IV, intravenous; VT/VF, Ventricular Tachycardia/Ventricular Fibrillation.

to the supraorbital ridge, nailbeds, or sternum, or nasal tickle with a cotton wisp. Responses such as grimacing, eye opening, grunting, or verbalization should be documented. Motor responses provide information not only about sensation and limb strength but also level of consciousness. The examiner should note whether stimuli produce “purposeful,” nonstereotyped limb movements, for example, reaching toward the site of stimulation (“localization”). This implies a degree of intact cortical function. Stereotyped limb movements generally are mediated by brain and spinal reflexes and do not require cortical input. Examples include extension and internal rotation of the limbs (decerebrate posturing), upper extremity flexion (decorticate posturing), and flexion at the ankle, knee, and hip (“triple-flexion”). Several scales designed to quantitate level of consciousness are available to help reduce inter- and intraobserver variability and to facilitate accurate follow-up. These scales (Glasgow Coma Scale [GCS],

In coma, the neuro-ophthalmologic examination should focus on: (1) the pupils, (2) resting eye position and eye movements, (3) retinal appearance, and (4) the corneal reflex.

Pupillary Examination Pupillary examination is perhaps the most important part of the coma examination, because it can help localize and differentiate between structural lesions and diffuse metabolic encephalopathies that cause bilateral cerebral hemispheric dysfunction. Pupillary constriction is mediated by cholinergic parasympathetic efferents that arise from the EdingerWestphal nucleus in the midbrain and travel within the oculomotor nerve. Pupillary dilation, in contrast, is mediated by sympathetic efferents originating in the hypothalamus that travel through the brainstem and cervical spinal cord and then synapse onto postganglionic neurons in the superior cervical ganglion. These noradrenergic neurons then course along the carotid artery into the cavernous sinus and through the superior orbital fissure before reaching the iris. Pupillary size, shape, and reactivity to light should be assessed. In general, abnormalities of the pupillary light reflex suggest a structural abnormality. However, certain drugs also may affect the pupillary light reflex. These agents can cause pupillary abnormalities that are mistakenly attributed to structural brain lesions (Table 10.2). Metabolic causes of coma typically do not affect the pupils. Normal pupils are round, have equal diameters, and briskly constrict when illuminated. When unequal pupils (anisocoria) are observed, it is important to establish whether it is the larger or the smaller pupil that is abnormal. This is accomplished by examining the eyes both in the light and in the dark. When the lights are extinguished, an abnormally small pupil will fail to dilate fully and the degree of anisocoria will increase. In contrast, when the abnormal pupil is the larger one, the degree of anisocoria will be maximal under full illumination when the larger pupil fails to constrict fully. In the NCCU, the most important causes of a unilaterally dilated pupil are compressive lesions of the oculomotor nerve complex (e.g., uncal herniation or a posterior communicating artery aneurysm). A complete third nerve palsy results in ipsilateral mydriasis, inferolateral deviation of the eye, and ipsilateral ptosis. As a rule a third nerve palsy with pupil involvement means a surgical lesion (i.e., compressive), whereas when the pupil is spared the cause is medical (e.g., diabetes, meningovascular syphilis). Patients with myasthenia gravis may present with ptosis and ophthalmoparesis secondary to neuromuscular weakness that is often unilateral. Therefore, this condition also should be considered in patients who present with what appears to be a pupil-sparing third nerve palsy. The most important cause of a unilateral small pupil is Horner syndrome, which is caused by damage to sympathetic efferents to the eye and consists of miosis and mild ipsilateral ptosis. Horner syndrome can be seen from multiple areas of brain damage, including (1) hypothalamic injury, (2) brainstem damage to descending inputs that synapse onto cervical

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Table 10.2  Drugs That Affect Pupillary Responses Drug Class

Examples

Effect on Pupils

Comments

Muscarinic antagonists

Atropine, scopolamine, ipratropium, tiotropium, tropicamide

Dilate pupils by blocking action of acetylcholine

Ipratropium and tiotropium can cause inadvertent pupillary dilation if accidentally gets into eye during respiratory treatment. Tropicamide eyedrops commonly used to dilate pupils for ophthalmologic evaluation.

Beta agonists

Epinephrine, isoproterenol, salmeterol, formoterol, albuterol

Dilate pupils by activating beta-adrenergic receptors

Albuterol, salmeterol, and formoterol can cause inadvertent pupillary dilation if accidentally gets into eye during respiratory treatment.

Cholinesterase inhibitors

Physostigmine, edrophonium, pyridostigmine, rivastigmine, donepezil, organophosphates

Constrict pupils by increasing acetylcholine concentration at synaptic cleft

Rivastigmine and donepezil used for treatment of dementia. Pyridostigmine used for treatment of myasthenia gravis.

Muscarinic agonists

Pilocarpine

Constrict pupils by activating muscarinic acetylcholine receptors

Pilocarpine eyedrops are used to distinguish pharmacologic pupil dilation from oculomotor nerve injury.

Serotonin-2A (5HT-2A) receptor agonists

Lysergic acid diethylamide (LSD)

Dilate pupils through unclear mechanism

Commonly used recreational hallucinogen.

Monoamine reuptake inhibitors

Cocaine, hydroxyamphetamine

Dilate pupils by blocking reuptake of norepinephrine at synaptic cleft

Hydroxyamphetamine eyedrops can help distinguish if constricted pupil is from preganglionic or postganglionic injury.

Norepinephrine release potentiators

Hydroxyamphetamine

Dilate pupils by increasing norepinephrine concentration at synaptic cleft

See above.

Opiate receptor agonists

Morphine, fentanyl, hydromorphone

Constrict pupils

Commonly used analgesics in hospitalized and critically ill patients

sympathetic preganglionic neurons, (3) cervical spine injury, (4) injury to sympathetic paravertebral ganglia (e.g., with an apical lung mass), or (5) damage to sympathetic postganglionic fibers because they course along the internal carotid artery (e.g., carotid artery dissection). Depending on the lesion location, ipsilateral facial anhidrosis and other focal neurologic signs also may be present. The presence of Horner syndrome unequivocally places the lesion ipsilateral to the pupillary abnormality. Bilaterally fixed and dilated pupils are seen in the terminal stages of brain death but also with anticholinergic medications, such as atropine. Hyperadrenergic states (e.g., pain, anxiety, cocaine intoxication) produce bilaterally large and reactive pupils. Reactive pinpoint (1 year to 18 years old interval is optional, usually 6 hr

Brainstem Reflexes The following tests are performed to evaluate brainstem function. Pupillary response: The pupils may be round, oval, or irregularly shaped. They are usually midsize (4 to 6 mm) but may be dilated. Drugs and preexisting anatomic ocular abnormalities may be a confounding factor.19 The pupillary light reflex (testing the second and third cranial nerves) must be absent. Pilocarpine supersensitivity due to denervation following instillation of 0.06% of the drug also may be seen. In some instances spontaneous asynchronous pupillary constriction and dilation may occur, which should not be a confounding factor for brain death diagnosis.20,21 Ocular movements: Both oculocephalic (doll’s eye response) and vestibulo-ocular (caloric test) reflexes must be absent in brain death patients. The oculocephalic reflex is elicited by rapidly and vigorously turning the head to 90 degrees laterally on both sides. A normal response is deviation of the eyes to

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the opposite side of the head turning; in brain death, there is no deviation of eyes. This test should not be done if there is a suspected fracture or instability of the spine. The vestibuloocular reflex is elicited by raising the head to 30 degrees and irrigating both tympanic membranes with 50 mL of iced saline or water. In brain death patients, there is no eye deviation. The patient should be observed for up to 1 minute following irrigation, with a 5-minute wait between testing for each ear. Contraindications to the test include rupture of the tympanic membrane. Drugs including sedatives, aminoglycoside antibiotics, tricyclic antidepressants, and some antiseizure agents can diminish the oculocephalic and vestibulo-ocular reflexes. Facial trauma involving auditory canal and petrous bone also can inhibit these reflexes. Corneal and facial motor responses: Both corneal and facial reflexes are absent in brain death patients. The corneal reflex is elicited by touching the cornea of the patient with a cotton swab; the normal response is a blink, which is absent in brain death. The facial motor response is elicited by applying pressure to the temporomandibular joint, supraorbital ridge, or nail bed. A normal response is facial grimacing, which is not seen in patients with brain death. Interpretation of these maneuvers can be difficult in patients with facial trauma. Pharyngeal and tracheal reflexes: Both of these reflexes are absent in brain death patients. The pharyngeal reflex is elicited by touching the posterior pharyngeal wall with a tongue blade that normally results in a gag. The cough reflex is elicited by using bronchial suctioning. These reflexes may be difficult to evaluate in orally intubated patients but may be feasible with deep suctioning in the orally intubated patient.22-24 Apnea testing: The medulla controls the central breathing center via chemoreceptors. These receptors sense changes in PaCO2. During apnea testing, target PaCO2 levels are up to 60 mm Hg. To do this test, the patient is removed from the ventilator; 100% oxygen may be administered via the endotracheal tube. In case of chronic hypercarbia (e.g., a patient with chronic obstructive pulmonary disease), higher target values of PaCO2 are required. Cardiac dysrhythmias and hypotension are complications associated with apnea testing and can be reduced by taking precautionary measures, such as preoxygenation and adequate maintenance of the baseline systolic blood pressure up to 120 mm Hg with pressors. Both hypocarbia and hypercarbia diminish viability of the organs for organ donation; one suggestion is to administer CO2 exogenously after preoxygenation to shorten the interval for hypercarbia.25,26 Many patients who undergo apnea testing are on vasopressors, and an apnea test is not possible in between 5% and 10% of patients because of hemodynamic instability or inadequate lung function.27 In hemodynamically stable patients, it is rare that apnea testing is aborted (30 min) partial pressure of brain tissue oxygen of zero is consistent with brain death. This measurement may be helpful in pharmacologically depressed patients, including children, to suggest when formal brain death assessment should be performed.55-57 However, brain oxygen levels have yet to be incorporated into definitions of brain death. Newer diagnostic tests, such as bispectral index, magnetic resonance imaging, computed tomography angiography (CTA), and computed tomography perfusion (CTP), have been suggested as useful,58-60 but there is insufficient evidence to determine whether newer ancillary tests can confirm the cessation of brain function.8

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Electrodiagnostic Testing EEG. An EEG is usually performed for 30 minutes before concluding brain death because of electrocerebral silence. It is recommended that a minimum of eight scalp electrodes be used with a distance between electrodes of at least 10 cm. However, the EEG is not entirely reliable as a confirmatory test to document brain death in that minimal electrical activity may be seen in some patients who otherwise fulfill brain death criteria, and the EEG may appear flat in cases of comatose patients with intact brainstem functioning. According to the American Encephalographic Society guidelines, electrocerebral silence is confirmed when there is absence of cortical activity greater than 2 µV for 30 minutes. EEG results may be contaminated by electromyographic artifacts from scalp motor units.61,62 Somatosensory and brainstem auditory evoked potentials. The somatosensory evoked potential (SSEP) is a bedside test done with a portable instrument via stimulation of the median nerve. When SSEP is used for brain death determination, it presupposes that there is absent pathology in the intervening structures between the peripheral nerve and the cortex (e.g., cervical spine injury). Patients with brainstem death have no response. These tests are useful in patients in whom misleading factors such as depressant drugs, hypothermia, and metabolic disturbances are present. These tests are less sensitive and not recommended for children younger than 6 months of age.63-65

Controversies in Brain Death There remain several important philosophical and practical issues in brain death despite its increasing acceptance worldwide (see also Chapter 8). Some suggest that the definition of brain death should be broadened further, and others suggest it already is too broad. The central issue for both groups is the concept of irreversible coma and particularly loss of respiratory drive. A patient who is unresponsive and who has no corneal reflexes but who has spontaneous respiration is not brain dead by present criteria. Although recent changes may allow such patients to have support stopped, this is different from declaring them dead by brain criteria. A similar issue arises in anencephalic infants, in whom there is no cortex but some of the brainstem is functioning including spontaneous breathing. Even though the child can never gain consciousness, he or she is not brain dead.10-12 Some authors have suggested that irreversible prolonged loss of consciousness is adequate to establish brain death. Proponents of this position suggest that: 1. Some clinically dead patients maintain residual vegetative functions that are mediated by the brain or brainstem (e.g., hypothalamic function when they do not manifest diabetes insipidus). 2. Some patients may retain slight cerebral electrical activity on EEG despite having no brainstem reflexes. 3. Some patients have stereotyped movements in the form of complex spinal reflexes that are difficult to tell from purposeful movements. 4. Confirmatory tests are necessarily positive predictors or may have ambiguity in their interpretation to reliably establish death.

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Proponents of this view postulate that brain death criteria should be based on the diagnosis of permanent loss of consciousness rather than loss of total brain function.66-73 Their new formulation has three components: definition, criteria, and diagnosis: Definition: Irreversible loss of consciousness, which is the most integrating function of the organism Criteria: Loss of cortical-subcortical connections to generate both components of consciousness (capacity and cognition) Diagnostic tests: No waking response to stimuli (capacity), no cognitive or affective functions (content)74 A second idea is to turn time back to 1968 and reform the concept of “irreversible coma” to “irreversible apneic coma” and so abandon the idea of whole brain death but accept instead lack of brainstem function as a sufficient criterion. This was the principle behind British guidelines. These ideas have also generated discussion about organ procurement and the dead donor rule that currently states that organ donors must be dead before donation. Donors when declared brain dead are dead by neurologic criteria. Consequently there is debate whether patients who have suffered severe and irreversible brain damage can become organ donors, even though they are not yet dead and organ removal then becomes the proximal cause of death.75 For the moment, none of these points of view have enough proponents to make a decisive change in the criteria already presented. Since the ad hoc Harvard report was issued, the medical and legal definitions of death have evolved and concepts such as loss of integration of the whole organism, loss of autonomy, and loss of personhood have generated discussion. Functional neuroimaging studies also have provided new insights into patients with severe brain injury and coma.76 In addition, some scholars advocate return to the traditional circulatory and respiratory criteria to diagnose death since brain dead patients may manifest a large variety of biologic function when mechanically ventilated.77 Recently the Institute of Medicine, the Joint Commission on the Accreditation of Healthcare Organizations, and the United Network for Organ Sharing have proposed organ donation after cessation of circulation and respiration as a way to increase organ procurement. In ICU care, this concept of “timed death” and subsequent organ donation (i.e., controlled organ donation after cardiac death) has generated controversy about the limits of treatment that aid organ transplant but that may hasten death, and the period of cardiac arrest needed to declare death and commence organ procurement.78 A critical factor to understand the meaning of death using circulatory-respiratory tests is the distinction between the “permanent” (will not reverse) and “irreversible” (cannot reverse) cessation of circulation, not heartbeat.79,80 Legal statutes specify irreversible cessation of circulatory and respiratory functions. However, the accepted medical standard is permanent cessation because physicians recognize that irreversible cessation inevitably and swiftly follows once circulation no longer restores itself spontaneously and cannot be restored medically (i.e., permanent is a surrogate for irreversibility). The revised Uniform Anatomical Gift Act of 2006 provides protection to those involved in organ procurement. However, the courts have not provided an opinion on whether health care providers may be held

liable for injuries that arise from the determination of death.81 Interdisciplinary teamwork that includes nurses and other clinicians in the ICU, palliative care, and the local organ procurement organization, among others, is necessary for organ donation in non–heart-beating donation and donation after cardiac death. Debate or controversy about death criteria can be healthy in a purely philosophical sense but in health care can be harmful, for example, creating distress for donor families and health care staff, and so institutional standards are necessary to ensure separation of death criteria and organ donation.82

Family Discussions The family should be told clearly that the patient is dead by brain criteria when these rules are followed; subsequent removal of the ventilator is not “termination of life support” but rather recognizing that death has occurred. In general, dead patients are not ventilated. How families respond to brain death or organ donation is beyond the scope of this chapter, and the reader is referred to other narratives.83

Brain Death and Organ Donation One of the most important aspects to establishing clear criteria for brain death is organ donation, although the number of organ donors varies greatly across nations. In many U.S. states, it is mandatory to raise the possibility of organ donation with the family of a patient who may be imminently brain dead. Transplant coordinators help with the subsequent steps, and this along with an institutional multidisciplinary organ donation approach or even countrywide efforts can help increase organ procurement.84-86 Current belief is that it is better for the treating intensivist, neurosurgeon, or neurologist not to be involved directly in the solicitation of organs. Their role is simply to establish that brain death is imminent. Uniform criteria that define imminent brain death and hence potential organ donation are not defined in detail but in general will include a mechanically ventilated deeply comatose patient, with irreversible catastrophic brain injury with a clear etiology of known origin, a Glasgow Coma Score of 3, and the progressive absence of at least three out of six brainstem reflexes or a FOUR score of zero.87 There remains a chronic shortage of organ donors. Family consent represents one limiting factor for successful donation; less than two thirds of families agree to organ donation. Associated factors in the United States include family members of minority populations, older potential donors, medical brain deaths, and a longer duration between brain death declaration and discussion about organ donation.88 In other countries, family refusal for organ donation or low number of organ donations may include denial and rejection of brain death, religious beliefs or fear about organ trade,89 and small hospital size.90 General public awareness is required to support organ and tissue transplantation.74 In addition, structured education and instruction on definitions of brain and cardiac death and organ donation policies are necessary in medical and nursing schools and even in subsequent training.91-93 The care of the brain dead individual between declaration of death and organ procurement and of donation after cardiac death is beyond the scope of this chapter. There are however

many factors that become important to organ procurement and subsequent recipient survival.94-99 The transplant team rather then the neurointensivist is better equipped to address this period of care, but the neurointensivist should be aware of issues such as ventilatory status, inflammation, hemodynamic instability, endocrine and metabolic disturbances, and altered internal homeostasis that may jeopardize organs that could be donated. Finally, there are rare circumstances that lead to maternal brain death during pregnancy. Management in this circumstance requires a multidisciplinary approach that follows current guidelines and recommendations for the fetus and for organ preservation of the potential donor.100

Withdrawal of Life Support Although a separate issue, withdrawal of life-sustaining measures in the individual with catastrophic neurologic injury is in part interwoven with the concept of brain death because this decision incorporates “irreversibility” and “permanence.” In addition, some of these patients may be suitable for organ donation after cardiac death protocols. When care is withdrawn in ventilated and comatose patients, up to half will die within 60 minutes, usually from cardiac arrest. Factors such as absent corneal and cough reflexes, extensor or absent motor response, and poor oxygenation are associated with earlier death.101 This information can be used to guide family and health care provider expectations. In these patients, the presence and severity of pain cannot be assessed and so palliative analgesia and sedation are necessary. Palliative sedation can be complex and requires consideration about whether the medication contributes to covert euthanasia or acceleration of death.

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49. Kuo JR, Chen CF, Chico CC, et al. Time dependant validity in the diagnosis of brain death using transcranial Doppler sonography. J Neurolsurg Psychiatry 2006;77(5):646–9. 50. Calleja S,Tembl JI, Sequra T. Sociedad Espanola Neurosonologia. Recommendations of the use of transcranial Doppler to determine the existence of cerebral circulatory arrest as diagnostic support of brain death. Neurolgia 2007;22(7):441–7. A complete list of references for this chapter can be found online at www.expertconsult.com.

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References 1. Manninen BA. Defining human death: an intersection of bioethics and metaphysics. Rev Neurosci 2009;20(3-4):283–92. 2. Ball CG, Navsaria P, Kirkpatrick AW, et al. The impact of country and culture on end-of-life care for injured patients: results from an international survey. J Trauma 2010;69(6):1323–34. 3. Practice parameters for determining brain death in adults: summary statement. Report of the quality Standards Subcommittee of the American Academy of Neurology. In: Practice handbook: American Academy of Neurology. St Paul, Minn: American Academy of Neurology; 1994. 4. A definition of irreversible coma: report of the Ad Hoc Committee of the Harvard Medical School to Examine the Definition of the brain death. JAMA 1968;205:337–40. 5. Burkle CM, Schipper AM, Wijdicks EF. Brain death and the courts. Neurology 2011;76(9):837–41. 6. Guidelines for the determination of death: report of the medical consultation on the diagnosis of death to the President’s Commission for the Study of Ethical Problems in Medicine and Biomedical and Behavioral Research. JAMA 1981;246:2184–6. 7. The Quality Standards Subcommittee of the American Academy of Neurology. Practice parameters for determining brain death in adults (summary statement). Neurology 1995;45:1012–4. 8. Wijdicks EF, Varelas PN, Gronseth GS, et al. American Academy of Neurology. Evidence-based guideline update: determining brain death in adults: report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 2010;74(23):1911–18. 9. Busl KM, Greer DM. Pitfalls in the diagnosis of brain death. Neurocrit Care 2009;11(2):276–87. 10. John J, Gane BD, Plakkal N, et al. Snake bite mimicking brain death. Case J 2008;1(1):16. 11. Miller RK. Fisher syndrome, a brainstem encephalitis, mimics brain death. Clin Pediatr (Phila) 1993;32(11):685–7. 12. Singounas EG. Glasgow coma scale and brain death: a proposal. Acta Neurochir (Wein) 1995;133(1-2):60. 13. Wijdicks EF, Bamlet WR, Maramattom BV, et al. Validation of a new coma scale: the FOUR score. Ann Neurol 2005;58(4):585–93. 14. Jain S, DeGeorgia M. Brain death associated reflexes and automatism. Neurocrit Care 2005;3(2):122–6. 15. Han SG, Kim GM, Lee KH, et al. Reflex movements in patients with brain death: a prospective study in tertiary medical center. J Korean Med Sci 2006;21(3):588–90. 16. Saposnik G, Maurino J, Saizar R. Facial myokymia in brain death. Eur J Neurol 2001;8(3):227–30. 17. Saposnik G, Maurino J, Saizar R, et al. Undulating toe movements in brain death. Eur J Neurol 2004;11(11):723–7. 18. Van den bent MJ, Ronday M, Oosterlee A. Unexpected movements in a brain dead patient. Ned Tijdschr Geneeskd 1993;137(51):2653–5. 19. Ishiguro T, Tamagawa S, Ogawa H. Changes of pupil size in brain death patient. Seishin Shinkeigaku Zasshi 1992;94(9):864–73. 20. Ishikawa S. Pupil recent development of investigation. Rinsho Shinkeigaku 1990;30(12):1329–33. 21. Shlugman D, Parulekar M, Elston JS, et al. Abnormal pupil activity in a brain stem–dead patient. Br J Anaesth 2001;86(5):717–20. 22. Wang MY, Wallace P, Gruen JP. Brain death documentation: analysis and issues. Neurosurgery 2002;15(3):731–6. 23. Thomke F, Weilmann LS. Current concepts in diagnosing brain death in Germany. Med Klin (Munich) 2000;95(2):85–9. 24. Nathanson M, Bergman PS, Anderson PJ. Significance of oculocephalic and caloric response in the unconscious patient. Neurology 1957;7(12): 829–32. 25. Sharpe MD, Young GB, Harris C. The apnea test for brain death determination: an alternative approach. Neurocrit Care 2004;1(3):363–6. 26. Wu XL, Fang Q, Li L, et al. Complication associated with the apnea test in the determination of the brain death. Chin Med J (Engl) 2008; 121(13):1169–72. 27. Wijdicks EF, Rabinstein AA, Manno EM, et al. Pronouncing brain death: contemporary practice and safety of the apnea test. Neurology 2008;71(16):1240–4. 28. Yee AH, Mandrekar J, Rabinstein AA, et al. Predictors of apnea test failure during brain death determination. Neurocrit Care 2010;12(3):352–5. 29. Conci F, Di Rienzo M, Castiglioni P. Blood pressure and heart variability and baroreflex sensitivity before and after brain death. J Neurosurg Psychiatry 2001;71(5):621–31. 30. Freitas J, Puig J, Rocha AP, et al. Heart rate variability in brain death. Clin Auton Res 1996;6(3):141–6.

31. Knuttgen D, Zur Nieden K, Muller-Georges MR, et al. Computer aided analysis of heart rate variability in brain death. Int J Clin Monit Comput 1997;14(1):37–42. 32. Ashwal S, Scheneider S. Brain death in the newborn. Pediatrics 1989;84(3):429–37. 33. Villani A, Onofri A, Bianchi R, et al. Determination of brain death in intensive pediatric therapy. Pediatr Med Chir 1998;20(1):19–23. 34. Parker BL, Frewen TC, Levine SD, et al. Declaring pediatric brain death: current practice in a Canadian pediatric critical care unit. CMAJ 1995;153(7):909–16. 35. Religious, cultural, legal, and ethical considerations. Crit Care Med 1993;21(12):1951–65. 36. Schimizu N, Shemie S, Miyasaka E, et al. Preliminary report: use of clinical criteria for the determination of pediatric brain death and confirmation by radionuclide cerebral blood flow. Masi 2000;49(10):1126–32. 37. Lustbader D, O’Hara D, Wijdicks EF, et al. Second brain death examination may negatively affect organ donation. Neurology 2011;76(2):119–24. 38. Nijboer WN, Moers C, Leuvenink HG, et al. How important is the duration of the brain death period for the outcome in kidney transplantation? Transpl Int 2011;24(1):14–20. 39. Varelas PN, Rehman M, Abdelhak T, et al. Single brain death examination is equivalent to dual brain death examinations. Neurocrit Care 2011;15(3):547–53. 40. Roberts DJ, MacCulloch KA, Versnick EJ, et al. Should ancillary brain blood flow analyses play a larger role in the neurological determination of death? Can J Anaesth 2010;57(10):927–35. 41. Wijdicks EF. The case against confirmatory tests for determining brain death in adults. Neurology 2010;75(1):77–83. 42. Young GB, Lee D. A critique of ancillary tests for brain death. Neurocrit Care 2004;1(4):499–508. 43. Young GB, Shemie SD, Doig J, et al. Brief review: the role of ancillary tests in the neurological determination of death. Can Anaesth 2006;53(6):540–3. 44. Wijdicks EFM. Determining brain death in adults. Neurology 1995;45: 1003–11. 45. Alvarez LA, Lipto RB, Hirschfeld A, et al. Brain death determination by angiography in the setting of a skull defect. Arch Neurol 1988;45(2):225–7. 46. Sharma D, Souter MJ, Moore AE, et al. Clinical experience with transcranial Doppler ultrasonography as a confirmatory test for brain death: a retrospective analysis. Neurocrit Care 2011;14(3):370–6. 47. Poularas J, Karakitsos D, Kouraklis G, et al. Comparison between transcranial color Doppler ultrasonography and angiography in the confirmation of brain death. Transplant Proc 2006;38(5):1213–17. 48. Valentin A, Karnik R, Winkler WB, et al. Transcranial Doppler for early identification of potential organ transplant donors. Wien Klin Wochenschr 1997;109(21):836–9. 49. Kuo JR, Chen CF, Chico CC, et al. Time dependant validity in the diagnosis of brain death using transcranial Doppler sonography. J Neurolsurg Psychiatry 2006;77(5):646–9. 50. Calleja S,Tembl JI, Sequra T. Sociedad Espanola Neurosonologia. Recommendations of the use of transcranial Doppler to determine the existence of cerebral circulatory arrest as diagnostic support of brain death. Neurolgia 2007;22(7):441–7. 51. Burger R. Value of transcranial Doppler ultrasonography compared with scintigraphic techniques and EEG in brain death. Zentrailbl Neurochir 2000;61(10):7–13. 52. Bertagna F, Barozzi O, Puta E, et al. Residual brain viability, evaluated by (99m)Tc-ECD SPECT, in patients with suspected brain death and with confounding clinical factors. Nucl Med Commun 2009;30(10):815–21. 53. Conrad GR, Sinha P. Scintography as a confirmatory test of brain death. Semin Nucl Med 2003;33(4):312–23. 54. Kurtek RW, Lia KK, Tauxe WN, et al. Tc 99 hexamethylpropylene amino oxime scintography in the diagnosis of brain death and its implications in the harvesting of organs used for transplant. Clin Nucl Med 2000; 25(1):7–10. 55. Pistoia F, Johnson DW, Darby JM, et al. The role of xenon CT measurements of cerebral blood flow in the clinical determination of brain death. AJNR Am J Neurodial 1991;12(1):97–103. 56. Figaji AA, Kent SJ. Brain tissue oxygenation in children diagnosed with brain death. Neurocrit Care 2010;12(1):56–61. 57. Smith ML, Counelis GJ, Maloney-Welinsky E, et al. Brain tissue oxygen tension in clinical brain death: a case series. Neurol Res 2007;29(7):755–9. 58. Palmer S, Badar MK. Brain tissue oxygenation in brain death. Neurocrit Care 2005;2(1):17–22. 59. Bohatyrewicz R, Sawicki M, Walecka A, et al. Computed tomographic angiography and perfusion in the diagnosis of brain death. Transplant Proc 2010;42(10):3941–6.

120.e2 Section II—Clinical and Laboratory Assessment 60. Escudero D, Otero J, Marqués L, et al. Diagnosing brain death by CT perfusion and multislice CT angiography. Neurocrit Care 2009;11(2): 261–71. 61. Berenguer CM, Davis FE, Howington JU. Brain death confirmation: comparison of computed tomographic angiography with nuclear medicine perfusion scan. J Trauma 2010;68(3):553–9. 62. Rimmele T, Malhicheikh A, Boselli E, et al. The electroencephalogram is not an adequate test to confirm the diagnosis of brain death. Can J Anaesth 2008;55(3):188–90. 63. Sethi NK, Sethi PK, Torgounick J. EMG artifact in brain death electroencephalogram, is it a cry of medullary death? Clin Neurol Neurosurg 2008;110(7):729–31. 64. Guerit JM. Evoked potential, a safe brain death confirmatory tool? Eur J Med 1992;1(4):233–43. 65. Wagner W. Scalp, ear lobe and nasopharyngeal recording of the median nerve somatosensory evoked P14 potential in coma and brain death patient and amplitude analysis. Brain 1996;119(Pt 5):1507–21. 66. Jarddim M. Brainstem auditory evoked potential as a model to assist diagnosis of brain death. Pro Fono 2008;20(2):123–8. 67. Bacigalupo F. The debate about death: an imperishable discussion. Biol Res 2007;40(4):523–34. 68. Nojszewska M. Determination of brain death. Neurol Neurochir Pol 2002;36(1):91–104. 69. Boobes Y, Al Daker N. What it means to die in Islam and modern medicine. Saudi J Kidney Dis Transpl 1996;7(2):121–7. 70. Bryne PA, O’Reilly S, Quary PM. Brain death: an opposing viewpoint. JAMA 1979;242(18):1985–90. 71. Trueba J. Clinical death, a diagnosis and a testimony. An Sist Sanit Nava 2007;30(Suppl 3):57–70. 72. Aker J, Pearson KS. AANA Journal Course. Update for nurse anesthetists brain death: terminology, clinical criteria, and diagnostic testing. AANA J 1997;65(2):129–35. 73. Truog RD, Fackler JC. Rethinking brain death. Crit Care Med 1992(12):1705–13. 74. Walker AE, Diamond EL, Moseley J. The neuropathological findings in irreversible coma: a critique of the respirator. J Neuropathol Exp Neurol 1975;34(4):295–323. 75. Machado-Curbelo C. A new formulation of death, definition, criteria and diagnostic tests. Rev Neurol 1998;26(154):1040–7. 76. Collins M. Reevaluating the dead donor rule. J Med Philos 2010;35(2): 154–79. 77. Cavanna AE, Cavanna SL, Servo S, et al. The neural correlates of impaired consciousness in coma and unresponsive states. Discov Med 2010;9(48):431–8. 78. Miller FG, Truog RD. Decapitation and the definition of death. J Med Ethics 2010;36(10):632–4. 79. Souter M, Van Norman G. Ethical controversies at end of life after traumatic brain injury: defining death and organ donation. Crit Care Med 2010;38(9 Suppl):S502–9. 80. Thomas AG. Continuing the definition of death debate: the report of the President’s Council on Bioethics on Controversies in the Determination of Death. Bioethics 2012;26(2):101–7. 81. Veatch RM. Transplanting hearts after death measured by cardiac criteria: the challenge to the dead donor rule. J Med Philos 2010;35(3):313–29.

82. Verheijde JL, Rady MY, McGregor J. Presumed consent for organ preservation in uncontrolled donation after cardiac death in the United States: a public policy with serious consequences. Philos Ethics Humanit Med 2009;4:15. 83. Dubois JM. The ethics of creating and responding to doubts about death criteria. J Med Philos 2010;35(3):365–80. 84. Manuel A, Solberg S, MacDonald S. Organ donation experiences of family members. Nephrol Nurs J 2010;37(3):229–37. 85. Kong AP, Barrios C, Salim A, et al. A multidisciplinary organ donor council and performance improvement initiative can improve donation outcomes. Am Surg 2010;76(10):1059–62. 86. Bleakley G. Implementing minimum notification criteria for organ donation in an acute hospital’s critical care units. Nurs Crit Care 2010;15(4):185–91. 87. Matesanz R, Marazuela R, Dominguez-Gil B, et al. The 40 donors per million population plan: an action plan for improvement of organ donation and transplantation in Spain. Transplant Proc 2009;41(8):3453–6. 88. de Groot YJ, Jansen NE, Bakker J, et al. Imminent brain death: point of departure for potential heart-beating organ donor recognition. Intensive Care Med 2010;36(9):1488–94. 89. Brown CV, Foulkrod KH, Dworaczyk S, et al. Barriers to obtaining family consent for potential organ donors. J Trauma 2010;68(2):447–51. 90. Ghorbani F, Khoddami-Vishteh HR, et al. Causes of family refusal for organ donation. Transplant Proc 2011;43(2):405–6. 91. Formanek M, Schöffski O. Difficulties with the organ donation process in small hospitals in Germany. Transplant Proc 2010;42(5):1445–8. 92. Anker AE, Feeley TH, Friedman E, et al. Teaching organ and tissue donation in medical and nursing education: a needs assessment. Prog Transplant 2009;19(4):343–8. 93. Lima CX, Lima MV, Cerqueira RG, et al. Organ donation: cross-sectional survey of knowledge and personal views of Brazilian medical students and physicians. Transplant Proc 2010;42(5):1466–71. 94. Rykhoff ME, Coupland C, Dionne J, et al. A clinical group’s attempt to raise awareness of organ and tissue donation. Prog Transplant 2010;20(1):33–9. 95. Murugan R, Venkataraman R, Wahed AS, et al, HIDonOR Study Investigators. Increased plasma interleukin-6 in donors is associated with lower recipient hospital-free survival after cadaveric organ transplantation. Crit Care Med 2008;36(6):1810–16. 96. Dictus C, Vienenkoetter B, Esmaeilzadeh M, et al. Critical care management of potential organ donors: our current standard. Clin Transplant 2009;23(Suppl 21):2–9. 97. Mascia L, Pasero D, Slutsky AS, et al. Effect of a lung protective strategy for organ donors on eligibility and availability of lungs for transplantation: a randomized controlled trial. JAMA 2010;304(23):2620–7. 98. Dubbeld J, van Hoek B, Ringers J. Use of a liver from donor after cardiac death: is it appropriate for the sick or the stable? Curr Opin Organ Transplant 2011;16(2):239–42. 99. Frontera JA. How I manage the adult potential organ donor: donation after cardiac death (part 2). Neurocrit Care 2010;12(1):111–16. 100. Esmaeilzadeh M, Dictus C, Kayvanpour E, et al. One life ends, another begins: management of a brain-dead pregnant mother—a systematic review. BMC Med 2010;8:74. 101. Yee AH, Rabinstein AA, Thapa P, et al. Factors influencing time to death after withdrawal of life support in neurocritical patients. Neurology 2010;74(17):1380–5.

Chapter

14

 

II

Glucose and Nutrition Sarice L. Bassin and Thomas P. Bleck

Introduction Hyperglycemia is common in acutely ill patients. In the past, stress hyperglycemia was considered to be a beneficial adaptive response. However, prospective observational and clinical trial data show a consistent and clear association between hyperglycemia and increased morbidity and mortality in all critically ill populations and in particular those with acute brain injury, stroke, and subarachnoid hemorrhage. Glycemic control therefore has become an important aspect of critical care. However, the optimal level of glycemic control in critical illness remains in debate since Van den Berghe et al. published their study conclusions in 2001 showing that strict glucose control was associated with reduced mortality.1,2 In these randomized trials intensive insulin therapy (IIT) was used to target a blood glucose of 80 to 110 mg/dL. Studies since then have not been able to duplicate these results (Normoglycemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation [NICE-SUGAR]),3 and so a more liberal glucose target of 140 to 180 mg/dL is favored. In addition, an association between hypoglycemia that can be caused by IIT, and high glycemic variability and poor outcome also is apparent, further emphasizing the importance of glucose control.4-7 The safety and efficacy of IIT may be influenced by patientrelated and intensive care unit–related variables. In particular, nutrition is closely associated with glycemic control.8,9 Furthermore, guidelines recommend use of early nutritional support, preferably enteral nutrition. However, optimal energy requirements and the timetable of nutritional support still are not fully resolved, in part because energy expenditure needs may not be met with enteral nutrition only, and there are different recommendations for parental nutrition in Europe and North America.10-15 This chapter addresses the importance of glucose control: how to monitor glucose levels in ICU patients, practical aspects of glucose control in ICUs, nutrition therapy, and methods to calculate nutritional requirements in critical care.

Glucose Plasma glucose usually is between 60 and 100 mg/dL before meals and up to 150 mg/dL after a meal. Hypoglycemia is defined as a blood glucose less than 50 mg/dL. Several factors such as malnutrition, cirrhosis, renal failure, and alcoholic ketoacidosis or drugs such as pentamidine, haloperidol, bactrim, or salicylates increase the risk of developing hypoglycemia. Traditionally, acute hyperglycemia was defined as a random glucose concentration greater than 200 mg/dL. In © Copyright 2013 Elsevier Inc. All rights reserved.

2010, the American Diabetes Association (ADA) proposed a threshold of 140 mg/dL (7.8 mmol/L; ADA Standards of Medical Care in Diabetes–2010 http://care.diabetesjournals. org/content/33/Supplement_1/S11.full). Hyperglycemia may be considered as mild (110-180 mg/dL), moderate (180400 mg/dL) or severe (>400 mg/dL). Table 14.1 lists the diagnostic criteria for diabetic ketoacidosis or hyperosmolar hyperglycemic state. In the hospitalized patient stress and medication (e.g., steroids) are factors associated with elevation of blood glucose. In addition, there can be relative insulin resistance after administration of catecholamines or glucocorticoids.

Assessment of Glucose in the Intensive Care Unit Blood to measure glucose can be obtained from a variety of sites (e.g., a fingerstick device, venipuncture, or through an intra-arterial or venous catheter). Fingersticks may be inaccurate when there is edema, hypoperfusion, or anemia, whereas capillary blood glucose monitoring may not be accurate in shock.16 In addition, care to prevent contamination by intravenous solutions is needed when using samples from arterial or venous catheters because pseudohyperglycemia may be present if a blood sample is drawn from a line where the patient is receiving dextrose 5% in water (D5W) or total parenteral nutrition (TPN). Laboratory analysis of plasma is the best means to analyze blood glucose levels. However, this technique may be too slow for care of critically ill patients. Many hospitals now have laboratories operated by licensed medical technologists in, or close to, the ICU that allow rapid assessment of blood gases, electrolytes, hemoglobin, prothrombin time (PT), and glucose through a blood gas analyzer or “stat” platform (e.g., i-STAT [Abbott Point of Care, Princeton, NJ], Radiometer ABL 825, or RapidLab 865).17 These devices generally are very accurate and can be used interchangeably with core laboratory devices,18 but turnaround time can still be a limiting factor.

Point-of-Care Testing Glucose testing using point-of-care (POC) devices has become increasingly common in hospital and ICU settings as well as in the operating room and in the outpatient environment.19 In addition, there are many different self-monitoring blood glucose (SMBG) devices available for patients to use, for example, Accu-Chek Active and Accu-Chek Performa (Roche Diagnostics, Indianapolis, IN), OneTouch Ultra2 (LifeScan 121

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Table 14.1  Diagnostic Criteria for Diabetic Ketoacidosis and Hyperosmolar Hyperglycemic State Criteria

Diabetic Ketoacidosis

Hyperosmolar Hyperglycemic State

Mild

Moderate

Severe

Plasma glucose (mg/dL)

>250

>250

>250

>600

Arterial pH

7.25-7.30

7.00-7.24

7.30

Serum bicarbonate (mEq/L)

15-18

10 to 320

Anion gap

>10

>12

>12

Variable

Level of consciousness

Alert

Alert/drowsy

Stupor/coma

Stupor/coma

†

Adapted from Kitabachi AE, Umpierrez GE, Murphy MB, et al. Hyperglycemic crisis in adult patients with diabetes: a consensus statement from the American Diabetes Association. Diabetes Care 2006;29:2739–48. * Effective serum osmolality = 2[measured Na+] + glucose/18. † Anion gap = Na+ − (Cl− + HCO3−)

Inc., Milpitas, CA), MediSense Optium or Xceed (Abbott Diabetes Care Inc., Alameda, CA), and others. These devices all are subject to strict regulatory standards (i.e., International Organization for Standardization. In vitro diagnostic test systems: requirements for blood glucose monitoring systems for self-testing in managing diabetes mellitus. [ISO 15197:2003 http://www.iso.org/iso/home/store/catalogue_tc/catalogue_ detail.htm?csnumber=26309; accessed Oct. 19, 2012.) Although POC devices are used at bedside, they are licensed under laboratory medical directors and governed by several regulatory bodies such as Health Care Financing Administration (HCFA), The Joint Commission, Clinical Laboratory Improvements Amendments of 1988 (CLIA 88), the College of American Pathologists (CAP), and individual state departments of health, hospital policies, and procedure manuals for each device. This means use of the devices must follow regulation, and there needs to be proficiency testing for accuracy and testing of unknown samples provided by CAP or commercial sources for comparison to reference range values to calibrate and verify the device. Staff who use the devices also are expected to receive annual competency testing. POC monitors are reasonably accurate, particularly when blood from a catheter is used. However, POC glucometers can be inaccurate (20%) when patients have low blood glucose levels17 and can differ from laboratory values20; not all achieve ISO 15197 accuracy criteria.21,22 This can limit their use when tight glucose control is targeted.23 Consequently it may be better to examine blood glucose levels using central lab or blood gas analyzers rather than POC devices24 and when POC devices are used careful clinical evaluation of each system for glucose measurement is critical.

i-STAT Analyzer This device can measure blood gases, electrolytes, glucose, and certain coagulation parameters through single-use sensors constructed using thin-film technology. Because the sensor film is thin, it can be used immediately and unlike thick film sensors does not require a calibration period. Waste, however, is a potential disadvantage of use.

GEM 3000 The GEM 3000 (Instrumentation Laboratories, Bedford, MA) has thick film sensors or electrodes in strips that can measure glucose, lactate, and blood gases. The sensors contain reagents and calibrators packed into small cartridges that are placed in the body of the analyzer. The cartridges can test multiple samples and the sensors are reusable. Samples with increased osmolalities, high protein, or high lipid volumes adversely affect the function. In addition, gallamine triethiodide, ethanol, sodium fluoride, potassium oxalate, acetaminophen, isoniazide, or thiocyanate may affect glucose or lactate levels.

Minimally Invasive Devices Continuous monitoring sensors (e.g., CDI 500 Parameter Monitoring System, Terumo Cardiovascular Systems, Ann Arbor, MI) that are inserted into the bloodstream are available but their benefit still needs to be elucidated. These monitors based on optical technology are primarily used to measure blood gases and most commonly have been used in cardiac surgery. However, electrochemical sensors that can monitor glucose are available.

Microdialysis In 2009 the Eirus system (Dipylon, Solna, Sweden) was CEmarked for continuous glucose and lactate monitoring in blood, and in 2011, the Eirus TLC catheter received its CE mark. This technology is based on microdialysis so no blood is removed from the patient, and it does not require a separate line because the device includes a central venous catheter. It allows second-by-second monitoring of glucose and lactate. The glucose value is presented on a monitor as a numeric value and a trend curve is provided. Studies have verified its technical feasibility, accuracy, and performance in the ICU.25,26 However, as of 2012 the device has not yet become commercially available.



Why Is Glycemic Control Important in the Neurocritical Care Unit? In critical illness, release of stress hormones (e.g., epinephrine and cortisol), medications such as exogenous glucocorticoids or catecholamines, and release of inflammatory mediators (e.g., in sepsis or trauma) all inhibit insulin release and action. This results in stress hyperglycemia, defined as an increase in blood glucose in the presence of acute illness,27 through enhanced gluconeogenesis, inhibition of glycogen synthesis, and impaired insulin-mediated glucose uptake by tissues. In addition, intravenous dextrose (e.g., in parenteral nutrition or in antibiotic solutions), can exacerbate or contribute to hyperglycemia. Overall, hyperglycemia may be present in 40% of critically ill patients; 80% of ICU patients with hyperglycemia have no history of diabetes before admission.28 Hyperglycemia during critical illness is associated with adverse outcome and an increased risk for infection, myocardial infarction, and neurologic and renal damage, particularly in patients who are not diabetic before admission.29 The effect of hyperglycemia also depends in part on patient pathology (i.e., ICU admission diagnosis).30 However, the impact of hyperglycemia on patients with preexisting diabetes is less clear even though diabetic patients are at greater risk for complications.31 In fact, in diabetic patients with elevated hemoglobin A1c (HbA1c) levels (>7%), glucose levels that are desirable in other patients appear to be “unsafe” in diabetic patients with chronic hyperglycemia.32 Although the likelihood of hyperglycemia is greater in sicker patients, it appears that hyperglycemia itself is an independent factor associated with outcome particularly in stroke, both hemorrhagic and ischemic, and acute coronary syndromes.33-40 In addition, survival is inversely associated with the duration of hyperglycemia.29 However, the exact threshold at which elevated blood glucose is deleterious remains uncertain. The relationship between hyperglycemia and increased risk of worse outcome has driven research into glucose control in the ICU, the value and structure of which remain debated, in part because tight glucose control is associated with an increased risk for hypoglycemia that in turn is associated with adverse outcome and mortality. Furthermore, glucose variability also is associated with an increased risk of poor outcome. For example, CueniVilloz et al.7 observed that increased blood glucose variability during therapeutic hypothermia was associated with in-hospital mortality after cardiac arrest, independent of injury severity and mean blood glucose levels. Consistent evidence from experimental and clinical studies demonstrates that hyperglycemia in the setting of acute neurologic injury is associated with worse outcomes; this concept is widely accepted in the management of critical neurologic illness in adults as well as children.41,42 Hyperglycemia at admission is present in almost half of acute stroke patients, and is an independent risk factor for mortality at 30 days, 1 year, and 6 years after stroke.33 Baird et  al. found that serum glucose greater than 130  mg/dL during the first 72 hours after a stroke was associated with significant increase in infarct size as measured by magnetic resonance imaging (MRI) 3 to 6 days after the ictus.34 Likewise, increased blood glucose is a risk factor for death and disability after aneurysmal subarachnoid hemorrhage (SAH).35,36,43 For example, McGirt et  al. observed that patients with blood glucose greater than 200  mg/dL for 2 or more days were seven times more likely

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to have a poor outcome at 10 months after SAH.37 Others have found that mean glucose concentrations greater than 140  mg/dL are associated with the development of symptomatic vasospasm after SAH.38,44 In traumatic brain injury (TBI) hyperglycemia also is associated with decreased survival, higher intracranial hypertension, and increased length of hospital stay.45,46 Whether hyperglycemia in the setting of acute neurologic injury is simply an epiphenomenon or actually serves a protective purpose remains controversial. The stress response associated with neurologic injury can lead to hyperglycemia through liberation of catecholamines that induce gluconeogenesis and insulin resistance. This may be an adaptive and protective response because glucose is the primary source of energy in the brain. However, some have postulated that in the setting of anaerobic metabolism, hyperglycemia will result in the accumulation of lactate and an intracellular acidosis, a potential mediator of secondary injury. Conversely, if the supply of glucose, the main energy substrate of the brain, is inadequate, there could be insufficient fuel for glycolysis in already ischemic tissue. Termed the glucose paradox of cerebral ischemia, this conundrum makes determination of an exact target for plasma glucose concentrations in patients with severe neurologic injury difficult.47 The conundrum is further complicated by accumulating evidence that in some circumstances after acute brain injury lactate is used as a fuel in the brain and may even be protective.48,49

Insulin Therapy in Critical Care In 2001 and 2006 two single center randomized clinical trials1,2 demonstrated the association between IIT and improved outcomes in critically ill patients in surgical ICUs (SICU) and medical ICUs (MICU). In these trials patients were randomly assigned to IIT (target glucose 80-110 mg/dL [4.4-6.1 mmol/L]) or standard care (target glucose 180200 mg/dL [9.9-11 mmol/L]). In SICU patients (n = 1548), Van den Berghe et al. observed that an IIT protocol that treated hyperglycemia by administration of intravenous infusion insulin adjusted to maintain blood glucose between 80 and110 mg/dL was associated with reduced mortality during intensive care (8% for conventional therapy vs. 4.6% for IIT) especially among patients who were in the ICU more than 5 days. Moreover, IIT reduced in-hospital mortality (10.9% for conventional care vs. 7.2% for IIT), bloodstream infection, renal failure, critical-illness polyneuropathy, and transfusions.1 The greatest reduction in mortality was observed for deaths associated with multiple-organ failure with a proven septic focus. A follow-up MICU study2 (n = 1200 patients) showed IIT was associated with prevention of newly acquired kidney injury, accelerated weaning from mechanical ventilation, and quicker discharge from the ICU and the hospital. In patients who received IIT, mortality was greater among those who were in the ICU less than 3 days but significantly decreased in those patients with MICU stays longer than 3 days.2 The mechanism by which IIT lowered mortality remains poorly understood and probably involves both glycemic and non­ glycemic pathways. The potential nonglycemic benefits of insulin include myocardial protection, partial correction of abnormal serum lipid profiles, and the prevention of excessive inflammation.50

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Table 14.2  Guidelines for Glycemic Control in the Intensive Care Unit Patient Population

Treatment Threshold

Target Glucose mg/dL

Definition of Hypoglycemia

Updated Since NICE-SUGAR Trial

Year

Organization

2009

American Association of Clinical Endocrinologists and American Diabetes Association

ICU patients

180

140-180

2.5). For example, the initial protein intake may need to be reduced to 1 to 1.3 g/kg/day and the daily blood urea nitrogen (BUN) followed. If the patient is oliguric, protein intake may need to be started at less than or equal to 0.6 g/kg/day and the daily BUN followed. Specific enteral nutritional supplements are available for these various conditions (e.g., Magnacal, Peptinex, NutriHep).

References 1. Van den Berghe G, Wouters P, Weekers F, et al. Intensive insulin therapy in critically ill patients. N Engl J Med 2001;345:1359–67. 2. Van den Berghe G, Wilmer A, Hermans G, et al. Intensive insulin therapy in medical intensive care patients. N Engl J Med 2006;354:449–61. 3. Wiener RS, Wiener DC, Larson RJ. Benefits and risks of tight glucose control in critically ill adults: a meta-analysis. JAMA 2008;300(8):933–44. 4. Jacka MJ, Torok-Both CJ, Bagshaw SM. Blood glucose control among critically ill patients with brain injury. Can J Neurol Sci 2009;36(4): 436–42. 5. Krinsley JS, Schultz MJ, Spronk PE, et al. Mild hypoglycemia is independently associated with increased mortality in the critically ill. Crit Care 2011;15(4):R173. 6. Duning T, van den Heuvel I, Dickmann A, et al. Hypoglycemia aggravates critical illness-induced neurocognitive dysfunction. Diabetes Care 2010; 33(3):639–44. Epub 2009, Dec 23. 7. Cueni-Villoz N, Devigili A, Delodder F, et al. Increased blood glucose variability during therapeutic hypothermia and outcome after cardiac arrest. Crit Care Med 2011;39(10):2225–31. 8. Kauffmann RM, Hayes RM, Jenkins JM, et al. Provision of balanced nutrition protects against hypoglycemia in the critically ill surgical patient. JPEN J Parenter Enteral Nutr 2011;35(6):686–94. Epub 2011, Jul 12. 9. Marik PE, Preiser JC. Toward understanding tight glycemic control in the ICU: a systematic review and metaanalysis. Chest 2010;137:544–51. 10. ASPEN Board of Directors and the Clinical Guidelines Task Force. Guidelines for the use of parenteral and enteral nutrition in adult and pediatric patients. J Parenter Enteral Nutr 2002;26S:1SA–138SA. 11. Kreymann KG, Berger MM, Deutz NE, et al. ESPEN guidelines on enteral nutrition: intensive care. Clin Nutr 2006;25:210–23. 12. Kreymann G, Adolph M, Druml W, et al. Intensive medicine: guidelines on parenteral nutrition. Ger Med Sci 2009;7:doc14. 13. Berger MM, Chiolero RL. Hypocaloric feeding: pros and cons. Curr Opin Crit Care 2007;13:180–6. 14. Heyland DK, Dhaliwal R, Drover JW, et al. Canadian clinical practice guidelines for nutrition support in mechanically ventilated, critically ill adult patients. JPEN J Parenter Enteral Nutr 2003;27:355–73. 15. McClave SA, Martindale RG, Vanek VW, et al. Guidelines for the provision and assessment of nutrition support therapy in the adult critically ill patient: Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (ASPEN). JPEN J Parenter Enteral Nutr 2009;33(3):277–316. 16. Juneja D, Pandey R, Singh O. Comparison between arterial and capillary blood glucose monitoring in patients with shock. Eur J Intern Med 2011;22(3):241–4. Epub 2011, Feb 16. 17. Corstjens AM, Ligtenberg JJ, van der Horst IC, et al. Accuracy and feasibility of point-of-care and continuous blood glucose analysis in critically ill ICU patients. Crit Care 2006;10(5):R135.

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129

18. Leino A, Kurvinen K. Interchangeability of blood gas, electrolyte and metabolite results measured with point-of-care, blood gas and core laboratory analyzers. Clin Chem Lab Med 2011;49(7):1187–91. Epub 2011, Apr 20. 19. Penfornis A, Personeni E, Borot S. Evolution of devices in diabetes management. Diabetes Technol Ther 2011;13(Suppl 1):S93–102. 20. Shearer A, Boehmer M, Closs M, et al. Comparison of glucose point-of-care values with laboratory values in critically ill patients. Am J Crit Care 2009;18(3):224–30. 21. Roth-Kleiner M, Stadelmann Diaw C, Urfer J, et al. Evaluation of different POCT devices for glucose measurement in a clinical neonatal setting. Eur J Pediatr 2010;169(11):1387–95. Epub 2010, Jun 24. 22. Meynaar IA, van Spreuwel M, Tangkau PL, et al. Accuracy of AccuChek glucose measurement in intensive care patients. Crit Care Med 2009;37(10): 2691–6. 23. Egi M, Finfer S, Bellomo R. Glycemic control in the ICU. Chest 2011;140(1):212–20. 24. Ichai C, Preiser JC, Société Française d’Anesthésie-Réanimation, et al. International recommendations for glucose control in adult non diabetic critically ill patients. Crit Care 2010;14(5):R166. Epub 2010, Sep 14. 25. Rooyackers O, Blixt C, Mattsson P, Wernerman J. Continuous glucose monitoring by intravenous microdialysis. Acta Anaesthesiologica Scandinavica 2010;54(7):841–7. 26. Möller F, Liska J, Franco-Cereceda A. Evaluation of a continuous blood glucose monitoring system using central venous microdialysis. Crit Care 2011;15(Suppl 1):P405. Published online 2011 March 11. doi: 10.1186/ cc9825. PMCID: PMC3068334. 27. Dungan KM, Braithwaite SS, Preiser JC. Stress hyperglycaemia. Lancet 2009;373:1798–807. 28. Farrokhi F, Smiley D, Umpierrez GE. Glycemic control in non-diabetic critically ill patients. Best Pract Res Clin Endocrinol Metab 2011;25(5):813–24. 29. Egi M, Bellomo R, Stachowski E, et al. Blood glucose concentration and outcome of critical illness: the impact of diabetes. Crit Care Med 2008;36: 2249–55. 30. Falciglia M, Freyberg RW, Almenoff PL, et al. Hyperglycemia-related mortality in critically ill patients varies with admission diagnosis. Crit Care Med 2009;37(12):3001–9. 31. Siegelaar SE, Hoekstra JB, DeVries JH. Special considerations for the diabetic patient in the ICU: targets for treatment and risks of hypoglycaemia. Best Pract Res Clin Endocrinol Metab 2011;25(5):825–34. 32. Egi M, Bellomo R, Stachowski E, et al. The interaction of chronic and acute glycemia with mortality in critically ill patients with diabetes. Crit Care Med 2011;39(1):105–11. 33. Williams LS, Rotich J, Qi R, et al. Effects of admission hyperglycemia on mortality and costs in acute ischemic stroke. Neurology 2002;59:67–71. 34. Baird TA, Parsons MW, Phanh T, et al. Persistent post stroke hyperglycemia is independently associated with infarct expansion and worse clinical outcomes. Stroke 2003;34:2208–14. 35. Juvela S, Siironen J, Kuhmonen J. Hyperglycemia, excess weight, and history of hypertension as risk factors for poor outcome and cerebral infarction after aneurysmal subarachnoid hemorrhage. J Neurosurg 2005;102(6):998–1003. 36. Frontera JA, Fernandez A, Claassen J, et al. Hyperglycemia after SAH: predictors, associated complications, and impact on outcome. Stroke 2006;37(1):199–203. 37. McGirt MJ, Woodworth GF, Ali M, et al. Persistent perioperative hyperglycemia as an independent predictor of poor outcome after aneurysmal subarachnoid hemorrhage. J Neurosurg 2007;107(6):1080–5. 38. Badjatia N, Topcuoglu MA, Buonanno FS, et al. Relationship between hyperglycemia and symptomatic vasospasm alter subarachnoid hemorrhage. Crit Care Med 2005;33:1603–9. 39. Worthley MI, Shrive FM, Anderson TJ, et al. Prognostic implication of hyperglycemia in myocardial infarction and primary angioplasty. Am J Med 2007;120(7):643.e1–e7. 40. Fogelholm R, Murros K, Rissanen A, et al. Admission blood glucose and short term survival in primary intracerebral haemorrhage: a population based study. J Neurol Neurosurg Psychiatry 2005;76:349–53. 41. Salim A, Hadjizacharia P, Dubose J, et al. Persistent hyperglycemia in severe traumatic brain injury: an independent predictor of outcome. Am Surg 2009;75(1):25–9. 42. Smith RL, Lin JC, Adelson PD, et al. Relationship between hyperglycemia and outcome in children with severe traumatic brain injury. Pediatr Crit Care Med 2012;13(1):85–91.

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43. Schmutzhard E, Rabinstein AA, Participants in the International Multi-Disciplinary Consensus Conference on the Critical Care Management of Subarachnoid Hemorrhage. Spontaneous subarachnoid hemorrhage and glucose management. Neurocrit Care 2011;15(2):281–6. 44. Dumont T, Rughani A, Silver J, et al. Diabetes mellitus increases risk of vasospasm following aneurysmal subarachnoid hemorrhage independent of glycemic control. Neurocrit Care 2009;11(2):183–9. Epub 2009, May 27. 45. Vogelzang M, Nijboer JMM, van der Horst ICC, et al. Hyperglycemia has a stronger relation with outcome in trauma patients than in other critically ill patients. J Trauma 2006;60:873–9. 46. Jeremitsky E, Omert LA, Dunham M, et al. The impact of hyperglycemia on patients with severe brain injury. J Trauma 2005;58:47–50.

47. McCormick MT, Muir KW, Gray CS, et al. Management of hyperglycemia in acute stroke: how, when, and for whom? Stroke 2008;39:2177–85. 48. Oddo M, Levine JM, Frangos S, et al. Brain lactate metabolism in humans with subarachnoid hemorrhage. Stroke 2012. Epub ahead of print. 49. Wyss MT, Jolivet R, Buck A, et al.. In vivo evidence for lactate as a neuronal energy source. J Neurosci 2011;31(20):7477–85. 50. Vanhorebeek I, Langouche L, Van den Berghe G. Glycemic and nonglycemic effects of insulin: how do they contribute to a better outcome of critical illness? Curr Opin Crit Care 2005;11:304–11. A complete list of references for this chapter can be found online at www.expertconsult.com.

Section II—Clinical and Laboratory Assessment 130.e1



References 1. Van den Berghe G, Wouters P, Weekers F, et al. Intensive insulin therapy in critically ill patients. N Engl J Med 2001;345:1359–67. 2. Van den Berghe G, Wilmer A, Hermans G, et al. Intensive insulin therapy in medical intensive care patients. N Engl J Med 2006;354:449–61. 3. Wiener RS, Wiener DC, Larson RJ. Benefits and risks of tight glucose control in critically ill adults: a meta-analysis. JAMA 2008;300(8):933–44. 4. Jacka MJ, Torok-Both CJ, Bagshaw SM. Blood glucose control among critically ill patients with brain injury. Can J Neurol Sci 2009;36(4): 436–42. 5. Krinsley JS, Schultz MJ, Spronk PE, et al. Mild hypoglycemia is independently associated with increased mortality in the critically ill. Crit Care 2011;15(4):R173. 6. Duning T, van den Heuvel I, Dickmann A, et al. Hypoglycemia aggravates critical illness-induced neurocognitive dysfunction. Diabetes Care 2010; 33(3):639–44. Epub 2009, Dec 23. 7. Cueni-Villoz N, Devigili A, Delodder F, et al. Increased blood glucose variability during therapeutic hypothermia and outcome after cardiac arrest. Crit Care Med 2011;39(10):2225–31. 8. Kauffmann RM, Hayes RM, Jenkins JM, et al. Provision of balanced nutrition protects against hypoglycemia in the critically ill surgical patient. JPEN J Parenter Enteral Nutr 2011;35(6):686–94. Epub 2011, Jul 12. 9. Marik PE, Preiser JC. Toward understanding tight glycemic control in the ICU: a systematic review and metaanalysis. Chest 2010;137:544–51. 10. ASPEN Board of Directors and the Clinical Guidelines Task Force. Guidelines for the use of parenteral and enteral nutrition in adult and pediatric patients. J Parenter Enteral Nutr 2002;26S:1SA–138SA. 11. Kreymann KG, Berger MM, Deutz NE, et al. ESPEN guidelines on enteral nutrition: intensive care. Clin Nutr 2006;25:210–23. 12. Kreymann G, Adolph M, Druml W, et al. Intensive medicine: guidelines on parenteral nutrition. Ger Med Sci 2009;7:doc14. 13. Berger MM, Chiolero RL. Hypocaloric feeding: pros and cons. Curr Opin Crit Care 2007;13:180–6. 14. Heyland DK, Dhaliwal R, Drover JW, et al. Canadian clinical practice guidelines for nutrition support in mechanically ventilated, critically ill adult patients. JPEN J Parenter Enteral Nutr 2003;27:355–73. 15. McClave SA, Martindale RG, Vanek VW, et al. Guidelines for the provision and assessment of nutrition support therapy in the adult critically ill patient: Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (ASPEN). JPEN J Parenter Enteral Nutr 2009;33(3):277–316. 16. Juneja D, Pandey R, Singh O. Comparison between arterial and capillary blood glucose monitoring in patients with shock. Eur J Intern Med 2011;22(3):241–4. Epub 2011, Feb 16. 17. Corstjens AM, Ligtenberg JJ, van der Horst IC, et al. Accuracy and feasibility of point-of-care and continuous blood glucose analysis in critically ill ICU patients. Crit Care 2006;10(5):R135. 18. Leino A, Kurvinen K. Interchangeability of blood gas, electrolyte and metabolite results measured with point-of-care, blood gas and core laboratory analyzers. Clin Chem Lab Med 2011;49(7):1187–91. Epub 2011, Apr 20. 19. Penfornis A, Personeni E, Borot S. Evolution of devices in diabetes management. Diabetes Technol Ther 2011;13(Suppl 1):S93–102. 20. Shearer A, Boehmer M, Closs M, et al. Comparison of glucose point-ofcare values with laboratory values in critically ill patients. Am J Crit Care 2009;18(3):224–30. 21. Roth-Kleiner M, Stadelmann Diaw C, Urfer J, et al. Evaluation of different POCT devices for glucose measurement in a clinical neonatal setting. Eur J Pediatr 2010;169(11):1387–95. Epub 2010, Jun 24. 22. Meynaar IA, van Spreuwel M, Tangkau PL, et al. Accuracy of AccuChek glucose measurement in intensive care patients. Crit Care Med 2009; 37(10):2691–6. 23. Egi M, Finfer S, Bellomo R. Glycemic control in the ICU. Chest 2011; 140(1):212–20. 24. Ichai C, Preiser JC, Société Française d’Anesthésie-Réanimatio, et al. International recommendations for glucose control in adult non diabetic critically ill patients. Crit Care 2010;14(5):R166. Epub 2010, Sep 14. 25. Rooyackers O, Blixt C, Mattsson P, Wernerman J. Continuous glucose monitoring by intravenous microdialysis. Acta Anaesthesiologica Scandinavica 2010;54(7):841–7. 26. Möller F, Liska J, Franco-Cereceda A. Evaluation of a continuous blood glucose monitoring system using central venous microdialysis. Crit Care 2011;15(Suppl 1):P405. Published online 2011 March 11. doi: 10.1186/ cc9825. PMCID: PMC3068334.

27. Dungan KM, Braithwaite SS, Preiser JC. Stress hyperglycaemia. Lancet 2009;373:1798–807. 28. Farrokhi F, Smiley D, Umpierrez GE. Glycemic control in non-diabetic critically ill patients. Best Pract Res Clin Endocrinol Metab 2011;25(5):813–24. 29. Egi M, Bellomo R, Stachowski E, et al. Blood glucose concentration and outcome of critical illness: the impact of diabetes. Crit Care Med 2008;36:2249–55. 30. Falciglia M, Freyberg RW, Almenoff PL, et al. Hyperglycemia-related mortality in critically ill patients varies with admission diagnosis. Crit Care Med 2009;37(12):3001–9. 31. Siegelaar SE, Hoekstra JB, DeVries JH. Special considerations for the diabetic patient in the ICU: targets for treatment and risks of hypoglycaemia. Best Pract Res Clin Endocrinol Metab 2011;25(5): 825–34. 32. Egi M, Bellomo R, Stachowski E, et al. The interaction of chronic and acute glycemia with mortality in critically ill patients with diabetes. Crit Care Med 2011;39(1):105–11. 33. Williams LS, Rotich J, Qi R, et al. Effects of admission hyperglycemia on mortality and costs in acute ischemic stroke. Neurology 2002;59:67–71. 34. Baird TA, Parsons MW, Phanh T, et al. Persistent post stroke hyperglycemia is independently associated with infarct expansion and worse clinical outcomes. Stroke 2003;34:2208–14. 35. Juvela S, Siironen J, Kuhmonen J. Hyperglycemia, excess weight, and history of hypertension as risk factors for poor outcome and cerebral infarction after aneurysmal subarachnoid hemorrhage. J Neurosurg 2005;102(6):998–1003. 36. Frontera JA, Fernandez A, Claassen J, et al. Hyperglycemia after SAH: predictors, associated complications, and impact on outcome. Stroke 2006;37(1):199–203. 37. McGirt MJ, Woodworth GF, Ali M, et al. Persistent perioperative hyperglycemia as an independent predictor of poor outcome after aneurysmal subarachnoid hemorrhage. J Neurosurg 2007;107(6):1080–5. 38. Badjatia N, Topcuoglu MA, Buonanno FS, et al. Relationship between hyperglycemia and symptomatic vasospasm alter subarachnoid hemorrhage. Crit Care Med 2005;33:1603–9. 39. Worthley MI, Shrive FM, Anderson TJ, et al. Prognostic implication of hyperglycemia in myocardial infarction and primary angioplasty. Am J Med 2007;120(7):643.e1–e7. 40. Fogelholm R, Murros K, Rissanen A, et al. Admission blood glucose and short term survival in primary intracerebral haemorrhage: a population based study. J Neurol Neurosurg Psychiatry 2005;76:349–53. 41. Salim A, Hadjizacharia P, Dubose J, et al. Persistent hyperglycemia in severe traumatic brain injury: an independent predictor of outcome. Am Surg 2009;75(1):25–9. 42. Smith RL, Lin JC, Adelson PD, et al. Relationship between hyperglycemia and outcome in children with severe traumatic brain injury. Pediatr Crit Care Med 2012;13(1):85–91. 43. Schmutzhard E, Rabinstein AA. Participants in the International Multi-Disciplinary Consensus Conference on the Critical Care Management of Subarachnoid Hemorrhage. Spontaneous subarachnoid hemorrhage and glucose management. Neurocrit Care 2011;15(2):281–6. 44. Dumont T, Rughani A, Silver J, et al. Diabetes mellitus increases risk of vasospasm following aneurysmal subarachnoid hemorrhage independent of glycemic control. Neurocrit Care 2009;11(2):183–9. Epub 2009, May 27. 45. Vogelzang M, Nijboer JMM, van der Horst ICC, et al. Hyperglycemia has a stronger relation with outcome in trauma patients than in other critically ill patients. J Trauma 2006;60:873–9. 46. Jeremitsky E, Omert LA, Dunham M, et al. The impact of hyperglycemia on patients with severe brain injury. J Trauma 2005;58:47–50. 47. McCormick MT, Muir KW, Gray CS, et al. Management of hyperglycemia in acute stroke: how, when, and for whom? Stroke 2008;39:2177–85. 48. Oddo M, Levine JM, Frangos S, et al. Brain lactate metabolism in humans with subarachnoid hemorrhage. Stroke 2012; Epub ahead of print. 49. Wyss MT, Jolivet R, Buck A, et al. In vivo evidence for lactate as a neuronal energy source. J Neurosci 2011;31(20):7477–85. 50. Vanhorebeek I, Langouche L, Van den Berghe G. Glycemic and nonglycemic effects of insulin: how do they contribute to a better outcome of critical illness? Curr Opin Crit Care 2005;11:304–11. 51. NICE-SUGAR Study Investigators, Finfer S, Chittock DR, et al. Intensive versus conventional glucose control in critically ill patients. N Engl J Med 2009;360(13):1283–97. Epub 2009, Mar 24. 52. Shetty S, Inzucchi SE, Goldberg PA, et al. Adapting to the New Consensus Guidelines for Managing Hyperglycemia During Critical Illness: the

130.e2 Section II—Clinical and Laboratory Assessment Updated Yale Insulin Infusion Protocol. Endocr Pract 2011;2:1–19. Epub ahead of print. 53. Van den Berghe G. How does blood glucose control with insulin save lives in intensive care? J Clin Invest 2004;114:1187–95. 54. Ven den Berghe G, Schoonheydt K, Becx P, et al. Insulin therapy protects the central and peripheral nervous system of intensive care patients. Neurology 2005;64:1348–53. 55. Hermans G, Wilmer A, Meersseman W, et al. Impact of intensive insulin therapy on neuromuscular complications and ventilator dependency in the medical intensive care unit. Am J Respir Crit Care Med 2007;175: 480–98. 56. Wieske L, Harmsen RE, Schultz MJ, et al. Is critical illness neuromyopathy and duration of mechanical ventilation decreased by strict glucose control? Neurocrit Care 2011;14(3):475–81. 57. Gray CS, Hildreth AJ, Sandercock PA, et al. Glucose-potassium-insulin infusions in the management of post-stroke hyperglycemia: the UK Glucose Insulin in Stroke Trial (GIST-UK). Lancet Neurol 2007;6:397–406. 58. Bilotta F, Spinelli A, Giovannini F, et al. The effect of intensive insulin therapy ion infection rate, vasospasm, neurologic outcome, and mortality in the neurointensive care unit after intracranial aneurysm clipping in patients with acute subarachnoid hemorrhage: a randomized prospective pilot trial. J Neurosurg Anesthesiol 2007;19:156–60. 59. Bilotta F, Caramia R, Cernak I, et al. Intensive insulin therapy after severe traumatic brain injury: a randomized clinical trial. Neurocrit Care 2008;9(2):159–66. 60. Green DM, O’Phelan KH, Bassin SL, et al. Intensive versus conventional insulin therapy in critically ill neurologic patients. Neurocrit Care 2010;13(3):299–306. 61. Graffagnino C, Gurram AR, Kolls B, et al. Intensive insulin therapy in the neurocritical care setting is associated with poor clinical outcomes. Neurocrit Care 2010;13(3):307–12. 62. Tiemessen CA, Hoedemaekers CW, van Iersel FM, et al. Intensive insulin therapy increases the risk of hypoglycemia in neurocritical care patients. J Neurosurg Anesthesiol 2011;23(3):206–14. 63. Shan L, Hao PP, Chen YG. Efficacy and safety of intensive insulin therapy for critically ill neurologic patients: a meta-analysis. J Trauma 2011;71(5):1460–4. 64. Coester A, Neumann CR, Schmidt MI. Intensive insulin therapy in severe traumatic brain injury: a randomized trial. J Trauma 2010;68(4):904–11. 65. Bruno A, Kent TA, Coull BM, et al. Treatment of hyperglycemia in ischemic stroke (THIS): a randomized pilot trial. Stroke 2008;39:384–9. 66. Johnston KC, Hall CL, Kissela BM, et al. Glucose Regulation in Acute Stroke Patients (GRASP) trial: a randomized pilot trial. Stroke 2009;40(12):3804–9. 67. Graetz D, Nagel A, Schlenk F, et al. Role of hyperglycemia and insulin treatment for cerebral metabolism in aneurysmal SAH. Meeting abstract. 59th Annual Meeting of the German Society of Neurosurgery, Wurzberg, Germany, 2008. 68. Vespa PM, McArthur D, O’Phelan K, et al. Persistently low extracellular glucose correlates with poor outcome 6 months after human traumatic brain injury despite a lack of increased lactate: a microdialysis study. J Cerebral Blood Flow Metab 2003;23:865–77. 69. Vespa P, Boonyaputthikul R, McArthur DL, et al. Intensive insulin therapy reduces microdialysis glucose values without altering glucose utilization or improving the lactate/pyruvate ratio after traumatic brain injury. Crit Care Med 2006;34:850–6. 70. Oddo M, Schmidt JM, Carrera C, et al. Impact of tight glycemic control on cerebral glucose metabolism after severe brain injury: a microdialysis study. Crit Care Med 2008;36:3233–8. 71. Schlenk F, Vajkoczy P, Sarrafzadeh A. Inpatient hyperglycemia following aneurysmal subarachnoid hemorrhage: relation to cerebral metabolism and outcome. Neurocrit Care 2009;11(1):56–63. Epub 2009, May 6. 72. Liogier LE, Macyszyn L, Kosty JA, et al. Brain and blood glucose after subarachnoid hemorrhage: a change in relationship that depends on blood glucose levels. New Orleans: AANS/CNS Joint Section on Cerebrovascular Disease Annual Meeting; 2012. 73. Zetterling M, Hillered L, Enblad P, et al. Relation between brain interstitial and systemic glucose concentrations after subarachnoid hemorrhage. J Neurosurg 2011;115(1):66–74. Epub 2011, Apr 8. 74. Helbok R, Schmidt JM, Kurtz P, et al. Systemic glucose and brain energy metabolism after subarachnoid hemorrhage. Neurocrit Care 2010;12(3):317–23. 75. Davidson PC, Steed RD, Bode BW. Glucommander: a computer-directed intravenous insulin system shown to be safe, simple, and effective in 120,618 h of operation. Diabetes Care 2005;28:2418–23.

76. Louie K, Cheema R, Dodek P, et al. Intensive nursing work schedules and the risk of hypoglycaemia in critically ill patients who are receiving intravenous insulin. Qual Saf Health 2010;19(6):e42. Epub 2010, Aug 4. 77. Campion TR Jr, May AK, Waitman LR, et al. Characteristics and effects of nurse dosing over-rides on computer-based intensive insulin therapy protocol performance. J Am Med Inform Assoc 2011;18(3):251–8. Epub 2011, Mar 14. 78. Berger MM, Que YA. Bioinformatics assistance of metabolic and nutrition management in the ICU. Curr Opin Clin Nutr Metab Care 2011;14(2): 202–8. 79. Krinsley JS. Glycemic variability: a strong independent predictor of mortality in critically ill patients. Crit Care Med 2008;36:3008–13. 80. Meyfroidt G, Keenan DM, Wang X, et al. Dynamic characteristics of blood glucose time series during the course of critical illness: effects of intensive insulin therapy and relative association with mortality. Crit Care Med 2010;38:1021–9. 81. Matsushima K, Peng M, Velasco C, et al. Glucose variability negatively impacts long-term functional outcome in patients with traumatic brain injury. J Crit Care 2011. Epub ahead of print. 82. Egi M, Bellomo R, Stachowski E, et al. Hypoglycemia and outcome in critically ill patients. Mayo Clin Proc 2010;85:217–24. 83. Rubinson L, Diette GB, Song X, et al. Low caloric intake is associated with nosocomial blood stream infections in patients in the medical intensive care unit. Crit Care Med 2004;(32):350–7. 84. Heyland DK, Stephens KE, Day AG, et al. The success of enteral nutrition and ICU-acquired infections: a multicenter observational study. Clin Nutr 2011;30(2):148–55. Epub 2010, Oct 25. 85. Serón-Arbeloa C, Puzo-Foncillas J, Garcés-Gimenez T, et al. A retrospective study about the influence of early nutritional support on mortality and nosocomial infection in the critical care setting. Clin Nutr 2011;30(3): 346–50. Epub 2010, Dec 4. 86. Hartl R, Gerber LM, Ni Q, et al. Effect of early nutrition on deaths due to severe traumatic brain injury. J Neurosurg 2008;109:50–6. 87. Montejo JC. Enteral nutrition-related gastrointestinal complications in critically ill patients: a multicenter study. Crit Care Med 1999;27: 1447–53. 88. Krishnan JA, Parce PB, Martinz A, et al. Caloric intake in medical ICU patients: consistency of care with guidelines and relationship to clinical outcomes. Chest 2003;124:297–305. 89. Brain Trauma Foundation, American Association of Neurological Surgeons, Congress of Neurological Surgeons. Guidelines for the management of severe traumatic brain injury. Nutrition J Neurotrauma 2007;24(Suppl 1): S77–82. 90. Cerra F, Benitez MR, Blackburn, et al. Applied nutrition in ICU patients: a consensus statement of the American College of Chest Physicians. Chest 1997;111:769–78. 91. Dennis M. Nutrition after stroke. Br Med Bull 2000;56:466–75. 92. Kinoshita K, Moriya T, Utagawa A, et al. Change in brain glucose after enteral nutrition in subarachnoid hemorrhage. J Surg Res 2010;162(2): 221–4. Epub 2009, Sep 22. 93. Marik PE, Zaloga GP. Early enteral nutrition in acutely ill patients: a systematic review. Crit Care Med 2001;29:2264–70. 94. Rubinson L, Diette GB, Song X, et al. Low caloric intake is associated with nosocomial bloodstream infections in patients in the medical intensive care unit. Crit Care Med 2004;32:350–7. 95. Villet S, Chiolero RL, Bollmann MD, et al. Negative impact of hypocaloric feeding and energy balance on clinical outcome in ICU patients. Clin Nutr 2005;24:502–9. 96. Nguyen NQ, Besanko LK, Burgstad C, et al. Delayed enteral feeding impairs intestinal carbohydrate absorption in critically ill patients. Crit Care Med 2012;40(1):50–4. 97. Hartl R, Gerber LM, Ni Q, et al. Effect of early nutrition on deaths due to severe traumatic brain injury. J Neurosurg 2008;109:50–6. 98. Taylor S, Fettes S, Jewkes C, et al. Prospective, randomized, controlled trial to determine the effect of early enhanced enteral nutrition on clinical outcome in mechanically ventilated patients suffering head in-jury. Crit Care Med 1999;27:2525–31. 99. Davalos A, Ricart W, Gonzalex-Huix F. Effect of malnutrition after acute stroke on clinical outcome. Stroke 1996;27:1028–32. 100. Kudsk KA. Effect of route and type of nutrition on intestine-derived inflammatory responses. Am J Surg 2003;185:16–21. 101. McClave SA, Sexton LK, Spain DA, et al. Enteral tube feeding in the intensive care unit: factors impeding adequate delivery. Crit Care Med 1999;27:1252–6.

102. McClave SA, Lukan JK, Stefater JA, et al. Poor validity of residual volumes as a marker for risk of aspiration in critically ill patients. Crit Care Med 2005;33:324–30. 103. Rice TW, Swope T, Bozeman S, et al. Variation in enteral nutrition delivery in mechanically ventilated patients. Nutrition 2005;21:786–92. 104. Grahm T, Zadroxny D, Harrington T. The benefits of early jejunal hyperalimentation in the head-injured patients. Neurosurgery 1989;25: 729–35. 105. Montecalvo MA, Steger KA, Farber HW, et al. Nutritional outcome and pneumonia in critical care patients randomized to gastric versus jejunal tube feedings. The Critical Care Research Team. Crit Care Med 1992;20(10):1377–87. 106. Peterson S, Chen Y. Systemic approach to parenteral nutrition in the ICU. Curr Drug Saf 2010;5(1):33–40. 107. Casaer MP, Mesotten D, Hermans G, et al. Early versus late parenteral nutrition in critically ill adults. N Engl J Med 2011;365(6):506–17. Epub 2011, Jun 29. 108. Borzotta AP, Pennings J, Papasadero B, et al. Enteral versus parenteral nutrition after severe closed head injury. J Trauma 1994;37:459–68. 109. Snydman DR. Shifting patterns in the epidemiology of nosocomial Candida infections. Chest 2003;123:500S–3S. 110. Woodcock, NP, Zeigler D, Palmer D, et al. Enteral versus parenteral nutrition: a pragmatic study. Nutrition 2001;17:1–12. 111. Hadley M, Grahn T, Harrington T, et al. Nutritional support and neurotrauma: a critical review of early nutrition in forty-five acute head injury patients. Neurosurgery 1986;19:367–73. 112. Doshi P, Divgiovine B. Effects of early enteral feeding on the outcome of critically ill mechanically ventilated medical patients on vasopressors. Chest 2006;130 (Supp):101S.

Section II—Clinical and Laboratory Assessment 130.e3 113. Berger MM, Revelly JP, Cayeux MC, et al. Enteral nutrition in critically ill patients with severe hemodynamic failure after cardiopulmonary bypass. Clin Nutr 2005;24:124–32. 114. Boullata J, Williams J, Cottrell F, et al. Accurate determination of energy needs in hospitalized patients. J Am Diet Assoc 2007;107:393–401. 115. American Association for Respiratory Care. AARC clinical practice guidelines. Metabolic measurement using indirect calorimetry during mechanical ventilation. Respir Care 1994;39(12):1170–5. 116. McClave SA, Kushner R, Van Way CW 3rd, et al. Nutrition therapy of the severely obese, critically ill patient: summation of conclusions and recommendations. JPEN J Parenter Enteral Nutr 2011;35(5 Suppl):88S–96S. 117. Martindale RG, DeLegge M, McClave S, et al. Nutrition delivery for obese ICU patients: delivery issues, lack of guidelines, and missed opportunities. JPEN J Parenter Enteral Nutr 2011;35(5 Suppl):80S–7S. 118. Flancbaum L, Choban PS, Sambucco S, et al. Comparison of indirect calorimetry, the Fick method, and prediction equations in estimating the energy requirements of critically ill patients. Am J Clin Nutr 1999;69:461–6. 119. Frankenfield DC, Rowe WA, Smith JS, et al. Validation of several established equations for resting metabolic rate in obese and nonobese people. J Am Diet Assoc 2003;103:1152–9. 120. de Jong PCM, Wesdorp RIC, Volovics A, et al. The value of objective measurements to select patients who are malnourished. Clin Nutr 1985;4:61–6. 121. Hall JC. The use of internal validity in the construct of an index of undernutrition. J Parenter Enteral Nutr 1990;14:582–7. 122. Harris J, Benedict F. A biometric study of basal metabolism in man. Washington, DC: Carnegie Institute of Washington; 1919. 123. Bistrian BR, Blackburn GL, Sherman M, et al. Therapeutic index of nutritional depletion in hospitalized patients. Surg Gynecol Obstet 1975;141:512–16.

Chapter

15

 

II

Hematology and Coagulation Monisha A. Kumar

Introduction Bleeding and thrombosis are common complications in the intensive care unit (ICU); their impact on neurologically ill patients is of particular concern because these complications may result in permanent neurologic disability. Sequelae from unrecognized bleeding can lead to cerebral ischemia, organ hypoperfusion, multiorgan failure, and death. Thrombotic complications, such as deep vein thrombosis (DVT), are common in neurologically injured patients given the associated limb weakness and complicated by the altered mental state. Multimodality monitoring in the neurologic ICU may preempt and thus mitigate the consequences of these common conditions. The first part of this chapter briefly reviews the physiology of erythropoises and the consequences of anemia and thrombocytopenia, explores the complications of blood transfusion, and discusses alternatives to blood product administration in neurologically critically ill patients. The clinical utility and application of new monitoring techniques available to evaluate anemia and thrombocytopenia in the ICU are discussed. The latter portion of this chapter is devoted to the diagnosis, monitoring, and management of venous thromboembolism.

Hematology Erythropoiesis and Blood Counts Erythropoiesis is catalyzed by the hormone erythropoietin and leads to production of mature erythrocytes. Reticulocytes are immature erythrocytes that are released into the circulation. Within 1 day, reticulocytes transform into mature red blood cells that circulate for 100 to 120 days. Ultimately, senescent red blood cells (RBCs) are removed from circulation by macrophages in the spleen and other reticuloendothelial tissues. On average, the number of erythrocytes formed is equivalent to the number destroyed. The complete blood count (CBC) provides accurate information about hemoglobin (Hgb) concentration and cell counts as well as calculated indices of erythrocyte size and Hgb content.1 The Hgb concentration varies by both age and gender (Table 15-1). In the average adult male, the Hgb concentration varies between 13 and 17.5 g/dL; in women it ranges from 12 to 16 g/dL. A high white blood cell (WBC) count, lipemia, or a precipitating monoclonal protein can result in a spuriously high Hgb. High altitude will result in an increased Hgb concentration; the rise in Hgb is proportional to the magnitude of elevation. Women of childbearing age © Copyright 2013 Elsevier Inc. All rights reserved.

have an average Hgb 10% lower than men of the same age.1 Because of the wide range of normal Hgb and hematocrit (Hct) values, it often is difficult to diagnose mild anemia. The RBC count is the number of RBCs per unit volume. It generally ranges between 4.2 and 5.9 million cells per microliter.1,2 RBCs are the most common cell type present in blood. They are smaller than white blood cells but larger than platelets. A normal platelet count is between 150,000 and 400,000/µL. Thrombocytopenia is defined as a platelet count less than 150,000/µL.2 The Hct is the ratio of RBCs to blood volume. With modern laboratory equipment, the Hct is calculated and not measured directly. The mean concentration of Hgb within the red cell population (mean corpuscular hemoglobin concentration [MCHC] is the quotient of the Hgb divided by the Hct. The red cell distribution width (RDW), another parameter of red cell size, measures the variability in red cell size of circulating erythrocytes.3 For example, the etiology of anemia with a low MCV and a high RDW is most likely iron deficiency; even though the anemia is microcytic, the variability of RBC size is high. In contrast, a macrocytic anemia would yield both a high MCV and RDW. Together with the reticulocyte count, the MCV and RDW can narrow the differential diagnosis of anemia. The reticulocyte count (RC) measures the number of immature RBCs in circulation and is a marker of RBC production. This count may be inaccurate in the presence of nucleated RBCs or nuclear debris in the peripheral blood. When the RC is reported as a percentage, it should be adjusted for the total number of RBCs present. This correction can be made by multiplying the reticulocyte count by the Hct and divided by age and gender specific normative Hct values. Alternatively, the percent of reticulocytes can be multipied by the red cell count to determine the absolute RC.2 The normal absolute reticulocyte count (ARC) is between 25,000 and 75,000/µL.2 In the presence of anemia, an ARC less than 75,000/µL indicates a hypoproliferative process, whereas an ARC greater than 100,000/µL indicates hemolysis or an appropriate erythropoietin response. RCs between 75,000 and 100,000/µL must be interpreted for the degree of anemia present.2 Review of the peripheral blood smear remains an informative diagnostic tool. Not only can it confirm findings of an automated CBC, but it also may suggest a marrow disease or hemolytic process. Microcytic, hypochromic cells may suggest iron deficiency or thalassemia, whereas macrocytosis with ovalocytes may suggest a megaloblastic anemia. The peripheral smear may demonstrate echinocytes, seen in uremia; 131

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Table 15.1  Reference Hematologic Values in Children and Adults* Hemoglobin (g/dL) Age

Hematocrit (%)

Red Blood Cell Count (1012/L)

MCV (fL)

MCH (pg)

MCHC (g/dL)

Mean

−2 SD

Mean

−2 SD

Mean

−2 SD

Mean

−2 SD

Mean

−2 SD

Mean

−2 SD

Birth (cord blood)

16.5

13.5

51

42

4.7

3.9

108

98

34

31

33

30

1-3 days (capillary)

18.5

14.5

56

45

5.3

4.0

108

95

34

31

33

29

1 week

17.5

13.5

54

42

5.1

3.9

107

88

34

28

33

28

2 weeks

16.5

12.5

51

39

4.9

3.6

105

86

34

28

33

28

1 month

14.0

10.0

43

31

4.2

3.0

104

85

34

28

33

29

2 months

11.5

9.0

35

28

3.8

2.7

96

77

30

26

33

29

3-6 months

11.5

9.5

35

29

3.8

3.1

91

74

30

25

33

30

0.5-2 years

12.0

10.5

36

33

4.5

3.7

78

70

27

23

33

30

2-6 years

12.5

11.5

37

34

4.6

3.9

81

75

27

24

34

31

6-12 years

13.5

11.5

40

35

4.6

4.0

86

77

29

25

34

31

Female

14.0

12.0

41

36

4.6

4.1

90

78

30

25

34

31

Male

14.5

13.0

43

37

4.9

4.5

88

78

30

25

34

31

Female

14.0

12.0

41

36

4.6

4.0

90

80

30

26

34

31

Male

15.5

13.5

47

41

5.2

4.5

90

80

30

26

34

31

12-18 YEARS

18-49 YEARS

Data from Dallman PR: Blood-forming tissues. In: Rudolph A, editor. Pediatrics. 16th ed. New York: Appleton-Century-Crofts; 1977. p. 1111. MCH, Mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; MCV, mean corpuscular volume. *These data have been compiled from several sources. Emphasis is given to studies employing electronic counters and to the selection of populations that are likely to exclude individuals with iron deficiency. The mean −2 SD can be expected to include 95% of the observations in a normal population.

acanthocytes, observed in liver disease; or schistocytes, found in disseminated intravascular coagulation (DIC). Special stains of the peripheral smear may assist in the diagnosis of anemia, particularly when there is rouleaux formation and automated counters may be inaccurate. Early after acute hemorrhage, red cell mass and plasma volume contract at the same rate; therefore, there may not be any observed reduction in Hgb concentration or Hct. The platelet count often increases after acute blood loss and there often is an increase in reticulocyte count. Because young erythrocytes are larger than mature ones, the MCV is usually slightly elevated. Bleeding is usually accompanied by an increase in indirect bilirubin, which reflects the catabolism of heme from extravasated RBCs.

mechanical ventilation and may be particularly detrimental for patients in the neurocritical care unit (NCCU) with reduced cerebrovascular reserve. Anemia is associated with increased ICU length of stay and increased mortality in critically ill patients.5 In surgical ICU patients with cardiac disease, anemia is associated with increased risk of death.8 Anemia also is associated with the development of left ventricular hypertrophy in patients with end-stage renal disease, and its correction is associated with fewer cardiovascular events.9 Preoperative anemia is associated with worse surgical outcomes10 and preprocedural anemia among patients undergoing percutaneous coronary intervention is associated with increased adverse in-hospital outcomes.11

Anemia

Causes of Anemia in the Intensive Care Unit

Anemia in the Intensive Care Unit Anemia is a common problem among critically ill patients. According to the World Health Organization, anemia is clinically defined as an Hgb concentration less than or equal to 12 g/dL for women and 13 g/dL for men.4 Nearly two thirds of patients are anemic on admission to the ICU5 and between 70% and 95% of patients become anemic by day 3.6,7 Anemia is potentially deleterious because lower Hgb levels decrease oxygen carrying capacity of the blood and may reduce tissue oxygenation. This is detrimental for patients with critical illness who often have increased metabolic demand for oxygen from infection, sepsis, fever, and

The causes of anemia in the ICU are varied and may occur concurrently. These include sepsis, trauma, burns, infections, hemolysis, immune-associated iron deficiency, decreased endogenous erythropoietin production, renal failure, liver disease, malignancy, collagen vascular disease, nutritional deficiency, gastrointestinal bleeding, drug-related causes, and phlebotomy. Phlebotomy is the most significant modifiable factor associated with anemia in the ICU and is a predictor of blood transfusion12; it accounts for 40 to 70 mL per day of blood loss early in the ICU period.13,14 Smoller observed that the amount of blood drawn per day varied from 12 mL per day on the ward, to 33 mL a day in the ICU in patients without

an arterial line, to 74 mL a day in ICU patients with an arterial line.15 For every 100 mL of blood removed by phlebotomy, Hgb and Hct levels fall by 0.7 g/dL and 1.9%, respectively.12 ICU patients with evidence of inflammation and multiorgan failure develop anemia despite a lack of active bleeding. This “anemia of critical illness” results from underproduction of erythrocytes and is similar to anemia of chronic disease, which is thought to be due to inflammation. Inflammatory cytokines, such as tumor necrosis factor-α (TNFα), interferon-α (IFNα), and interleukin-1 (IL-1), suppress erythropoiesis and are central in the pathogenesis of anemia in these patients.16 These inflammatory mediators inhibit hypoxia-induced (as opposed to anemia-induced) erythropoietin (EPO) production by up to 89%.17 Proinflammatory cytokines not only induce bone marrow suppression of erythropoiesis but also aggravate bleeding and disrupt iron metabolism. These cytokines exacerbate intestinal bleeding through increased permeability of the intestinal wall. They alter iron metabolism by stimulating phagocytosis of RBCs. More than 90% of ICU patients have low levels of serum iron (Fe), total iron binding capacity (TIBC), and Feto-TIBC ratio, but have normal or elevated serum ferritin.18,19 Despite low levels of circulating iron, EPO levels remain only modestly increased and are not markedly elevated. This blunted EPO response results from the inhibition of EPO transcription by inflammatory mediators. Rogiers et al. found that at the same serum level of Hgb, ambulatory anemic patients had an eight times higher level of EPO than did septic ICU patients.18 The etiology of anemia in the ICU is multifactorial and can be difficult to determine. The diagnosis of anemia in the ICU is complicated because serial monitoring of hematologic profiles (i.e., phlebotomy) can exacerbate the condition.

Monitoring Anemia in the Intensive Care Unit Modern laboratory testing and the availability of automated cell counters provide a wealth of diagnostic information for interpretation. The extended differential count (EDC) quantifies other cell types in the peripheral blood including nucleated RBCs (NRBCs). Although NRBCs typically are only seen in neonates, their presence has been identified in adults, notably in patients with septicemia, massive hemorrhage, and severe hypoxia.20,21 When identified in adults, the presence and burden of NRBC may correlate with mortality and poor outcome. For example, Stachon observed a mortality rate of 44% in surgical patients with NRBCs compared with 4.2% for patients without.21 Other parameters of cellular analysis available through automated analyzers include the immature reticulocyte fraction (IRF), mean reticulocyte hemoglobin content (CHr), mean reticulocyte volume (MCVr), fragmented RBC (FRBC) count, and the immature platelet fraction (IPF). IRF is an early and sensitive index of erythropoiesis. When characterized with total reticulocyte count, it can discriminate between anemias with increased erythropoiesis (increased total reticulocyte count and IRF) such as hemolytic anemias; decreased marrow function (decreased total reticulocyte count and IRF); and conditions such as acute infections and myelodysplastic syndrome with dissociation of total reticulocyte count and

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IRF (total reticulocyte count low, IRF high).20 It also is useful to identify resumption of marrow activity after bone marrow transplantation or chemotherapy. The CHr and the MCVr are reticulocyte indices that reflect the adequacy of iron stores available for erythropoiesis. The CHr is important because it can help identify iron-deficiency anemia in the face of the acute phase response when total iron stores, as evidenced by an elevated ferritin and transferrin, are adequate. This may be seen in anemia of chronic disease. The MCVr has not been well studied, but has been used to evaluate possible EPO abuse in sports.22 The main limitations of these new indices include limited availability of the machines and variable sensitivity of the analyses. FRBCs can be found in a variety of diseases from microangiopathies to cardiovascular disorders (valve prostheses and endocarditis). Microangiopathies need immediate diagnosis and treatment, and expedient identification and quantification is paramount. The sensitivity of the new analyzers to diagnose microangiopathy is very high (>90%), but the specificity is low (20%-50%).23,24 Therefore in certain populations, the FRBC count may be a good screening test for microangiopathies, but further study is warranted. In addition to new laboratory indices of red cell size and function, new monitoring devices permit measurements of total Hgb concentration. In contrast to the standard cyanomethemoglobin method of Hgb determination, co-oximeters use spectrophotometry to determine Hgb concentration. The methodology of Hgb measurement is similar to that of oxyhemoglobin measurement by conventional pulse oximetry, except that instead of two wavelengths of light, multiple wavelengths are transmitted through the finger to measure the light absorbance characteristics of Hgb.25 Point-of-care co-oximeters, such as the HemoCue (Angelholm, Sweden), allow for capillary measurement of Hgb concentration at the bedside, whereas noninvasive co-oximeters, such as the Radical-7 (Masimo Corp, Irvine, CA) device, provide continuous Hgb measurements. The accuracy of these devices compare well against standard laboratory assays, although the Radical-7 may give lower readings than the HemoCue during surgery.26,27 Hgb measurements with these devices have the additional benefit of providing rapid results that may facilitate monitoring in the operating room, ICU, and emergency department.

Anemia in the Neurocritical Care Unit Anemia is common in the NCCU and, depending on the definition, occurs in nearly 40% of patients.28 It has been identified as an independent factor associated with death or severe disability in several disorders including subarachnoid hemorrhage (SAH), particularly in patients who develop delayed cerebral ischemia, traumatic brain injury (TBI), or intracerebral hemorrhage (ICH).28-34 However, there remains variation in how anemia is managed. In the uninjured brain, vasodilation of the cerebral arteries compensates for anemia-related reduction in oxygen carrying capacity; therefore, frank brain hypoxia does not typically occur at Hgb concentrations greater than 6 g/dL.35 The ability of cerebral vessels to vary their caliber to maintain constant perfusion is termed cerebral autoregulation. With impairment of cerebral autoregulation, such as may occur after SAH or TBI, tissue hypoxia may occur at higher Hgb concentrations. Consistent with this, fewer ischemic events are observed in

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SAH patients with higher Hgb concentrations.33 However, the Hgb threshold below which cerebral metabolic dysfunction occurs is only beginning to be elucidated. A fundamental tenet of neurocritical care is that ischemia is an important cause of brain injury. Anemia and compromised oxygen delivery may exacerbate ischemia; therefore anemia may represent a therapeutic target in the NCCU. However, the ramifications of anemia may vary by the type of brain injury. The consequences of anemia after SAH, particularly among patients with severe vasospasm or delayed cerebral ischemia (DCI), may be dire. In contrast, the significance of cerebral ischemia in other neorocritically ill subpopulations is less clear; therefore, anemia may be of less concern.

Optimal Hemoglobin Threshold in the Neurocritical Care Unit Population Several physiology studies in neurocritically ill patients have sought to define an Hgb threshold by measuring markers of cerebral metabolism.35-37 Brain tissue oxygen tension (PbtO2) monitoring and lactate-to-pyruvate ratio (LPR) measurements from cerebral microdialysis demonstrated increased brain hypoxia and cell energy dysfunction when Hgb levels were less than 9 g/dL in SAH patients.37 However, the physiologic data in TBI are conflicting.37-39 Although TBI patients frequently have pathologic evidence of cerebral infarction, premortem evidence of ischemia is debatable.40-42 Early evidence demonstrated compromised cerebral blood flow suggestive of ischemia; however, it was later demonstrated that the altered blood flow correlated with decreased cerebral metabolism.40,43,44 Regardless, anemia appears to be a predictor of poor outcome, although transfusion of PRBCs does not always appear to mitigate its effect.45 The treatment of anemia in the NCCU is unclear in part because of the heterogeneous pathophysiology of diseases treated therein. Moreover, transfusion trials in general ICUs included very few or excluded neurologically critically ill patients and therefore results cannot be easily extrapolated from them.46,47 Transfusion studies in patients with active cardiac ischemia have not demonstrated consistent benefit from a liberal transfusion approach.5,8 It is unclear whether this is analogous to patients with cerebral ischemia.

Thrombocytopenia Thrombocytopenia in the Critically Ill The importance of platelets and their role in thrombus formation is clear, but their significance in sepsis is being elucidated.48 Thrombocytopenia occurs in 13% to 58% of ICU patients49-53; 23% have at least one platelet count less than 100,000/mm3 and 10% had counts less than 50,000 mm3.50 Sepsis is considered the major independent risk factor for thrombocytopenia in the ICU. Other factors associated with thrombocytopenia are episodes of bleeding or transfusion, longer ICU stays, and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores greater than 15.52 The development of thrombocytopenia during the ICU stay is associated with decreased ICU survival and may have a greater implication for prognosis than admission thrombocytopenia.51,53,54 For example, Cawley et al. observed that a drop in platelet count to less than 50% of admission levels was

associated with greater mortality than admission APACHE II, Simplified Acute Physiology Score (SAPS), or multiple organ dysfunction syndrome (MODS) scores.49 ICU-related thrombocytopenia is primarily caused by peripheral loss, destruction, and margination of platelets rather than bone marrow hypoplasia or nutritional deficiency. Sepsis accounts for 48% of cases. Other causes include liver disease, hypersplenism, consumption, platelet destruction, DIC, medications, immune phenomena, and intravascular devices.55 The cause of a low platelet count in the ICU can be difficult to determine and in more than 25% of critically ill patients the cause is multifactorial. Pseudothrombocytopenia occurs when platelets clump in association with an ethylenediamine tetra-acetic acid (EDTA)–dependent platelet agglutinin.52 An accurate platelet count can be determined by collecting the sample in a citrated collection tube or by using a heparinized blood sample. Postresuscitative hemodilution can result in thrombocytopenia (i.e., after blood transfusion or with crystalloid or colloid replacement therapy for blood loss). The post-transfusion reduction in platelet count is associated with both splenic sequestration of platelets and a reduction in viable platelets in stored blood. Platelets play a complex role in sepsis and multiorgan dysfunction. Platelets of septic patients may display increased adhesion and aggregation.56,57 Bacteria and bacterial products may affect platelet function. Lipopolysaccharide increases platelet aggregation in some animal models, but has the opposite effect on human platelets in vitro.48 Lipoteichoic acid, a cellular membrane component of gram-positive bacteria, inhibits platelet aggregation in human platelets.48 Escherichia coli endotoxin may indirectly reduce platelet responsiveness.48

Drug-Induced Thrombocytopenia Drug-induced thrombocytopenia (DIT) is a common nonimmune-mediated disorder, associated with bone marrow suppression and accelerated platelet destruction and defined as a platelet count between 50 and 150,000 × 106/L with any degree of spontaneous bleeding.58 It is observed in 19% to 25% of ICU patients59,60 and associated with medications such as cytotoxic chemotherapeutic agents,61,62 thiazide diuretics, ethanol, tolbutamide, and bleomycin. DIT typically develops 2 to 3 days after a previously administered medication, and 7 days after a virgin drug. Discontinuation of the medication normalizes the platelet count by 5 to 8 days.63 A major bleeding event can occur in 4% of patients,63 and these patients may benefit from intravenous immunoglobulin (IVIg), plasmapheresis, or platelet transfusion64 but not corticosteroids.65

Drug-Induced Immune Thrombocytopenia Drug-induced immune thrombocytopenia (DITP) is a disorder characterized by the development of drug-dependent antibodies that bind to glycoproteins on the surface of platelets and accelerate their destruction in the presence of the specific drug. This type of disorder may be more severe than DIT. Hundreds of drugs have been associated with this type of thrombocytopenia; the most common are heparin, quinine (cinchona alkaloids), penicillin, sulfonamides, nonsteroidal anti-inflammatory drugs (NSAIDs), anticonvulsants, antirheumatics, oral hypoglycemics, gold salts, diuretics, rifampicin, ranitidine, and the glycoprotein (GP) IIb/IIIa inhibitors

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(e.g., abciximab, tirofiban, or eptifibatide).58 The precise mechanisms by which various drugs incite the immune response are beyond the scope of this chapter. Some patients can make both drug-independent and drug-dependent antibodies during the course of medication exposure. The drugindependent antibodies (autoantibodies) usually are transient but if they persist, can result in a chronic autoimmune thrombocytopenic purpura. When agents such as GPIIb/IIIa inhibitors are used, platelet counts should be frequently monitored. If the platelet count is less than 50,000/µL, the drug should be discontinued. If the platelet count is less than 10,000/µL and there is severe bleeding or if an invasive procedure is required, then platelet transfusion should be considered.66 Readministration of GPIIb/IIIa at a later date is not recommended because the rechallenge might prove more severe than the initial event.

Heparin-Induced Thrombocytopenia Heparin-induced thrombocytopenia (HIT) is an anticoagulantinduced prothrombotic immune disorder caused by heparindependent platelet-activating IgG antibodies that recognize complexes of platelet factor 4 (PF4) bound to heparin.67,68 HIT should be suspected when the platelet count falls to less than 50% of the baseline level or an absolute number of less than 150,000/µL between days 5 and 14 of heparin exposure. Several factors are associated with the development of HIT: (1) the dose or duration of heparin use; (2) the type of heparin administered; (3) the patient population; and (4) patient gender69 (Table 15.2). A greater risk of HIT is observed in patients exposed to a high dose of heparin or a long duration of treatment, with unfractionated heparin rather than low molecular weight heparin (LMWH), with surgical rather than medical patients, and in females. PF4 is a tetrameric protein, involved with hemostasis, immunoregulation, and angiogenesis. Heparin binding induces a conformational change in PF4. HIT differs from most other drug-induced immune thrombocytopenias in that the induced antibodies engage the Fc receptor (not Fab region) and thereby activate platelets (i.e., they promote thrombosis and a hypercoagulable state, which is characteristic of HIT). PF4 also neutralizes the anticoagulant effect of heparin, which exacerbates the prothrombotic milieu.

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Clinical complications of HIT include both venous and arterial thromboses.55 Arterial thrombosis is more common in those with known cardiac disease, whereas DVT is seen in postoperative patients. Cerebral sinus thrombosis, venous limb gangrene, and hemorrhagic adrenal infarction also are reported.67 Concomitant prothrombotic risk factors include diabetes mellitus, malignancy, systemic lupus erythematosus (SLE), antiphospholipid antibody syndrome, indwelling catheters, and trauma.55 The incidence of stroke is 3.1% among patients with HIT and is more common in females, in patients with more severe thrombocytopenia, and early in the course of HIT. Myocardial infarction can occur in 3% to 5% of patients and amputation in as many as 20% of patients with HIT and limb thrombosis. In SAH, HIT may occur in up to 15% of patients, and its risk is increased in Fisher grade 3 patients, females, and perhaps endovascular treatments.70 The incidence of hypodensity on computed tomography (CT) scans and worse outcome is increased. PF4 antibodies are transient and are undetectable a median of 50 to 85 days after an episode of HIT.71 In some patients antibodies remain detectable at low levels for several months. If heparin is readministered to a patient with high levels of antibodies, development of thrombocytopenia can be rapid. This is unlikely more than 100 days from exposure. The “4 T’s”—Thrombocytopenia, Timing, Thrombosis, and oTher plausible explanations for the clinical scenario—is an eightpoint clinical scoring system that evaluates the likelihood of developing HIT (Table 15.3).72 It has a high negative predictive value and can help rule out HIT. If HIT is suspected all heparin sources must be stopped, preferably before the demonstration of HIT antibodies. The direct thrombin inhibitor family of anticoagulants should replace heparin because treatment with LMWH does not fully eradicate the risk of HIT.

Thrombotic Microangiopathies: Thrombotic Thrombocytopenic Purpura Thrombotic thrombocytopenic purpura (TTP) is a rare but potentially fatal disorder that mostly affects adult women. It is characterized by red cell fragmentation (microangiopathy), hemolytic anemia, and thrombosis (consumptive thrombocytopenia) that lead to ischemic organ damage.73 The predilection for thrombosis is a consequence of abnormal numbers of

Table 15.2  Risk Factors for Immune Heparin-Induced Thrombocytopenia Risk Factor

Odds Ratio

Comment

Duration of heparin use (>1 week vs. 1 week) ∼2% versus risk for “delayed-onset HIT” (without prophylaxis) ∼0.02%-0.1%

Type of Heparin UFH > LMWH > fondaparinux

∼10-15

Difference in risk for HIT between heparin types is established for postsurgical thromboprophylaxis (UFH vs. LMWH) and is more pronounced in women. ORs shown are for UFH versus LMWH (woman, postsurgical prophylaxis) [18]

Type of patient (surgery > medical > pregnancy)

∼3-4

Highest reported frequencies of HIT are in postsurgical thromboprophylaxis (OR shown is for surgery vs. medical) [18]

Gender (female > male)

∼1.5-2.0

Difference in risk for HIT between women and men has only been established for UFH thromboprophylaxis

Used with permission from Warkentin TE. Heparin-induced thrombocytopenia. Hematol Oncol Clin North Am 2007;21(4):592. HIT, Heparin-induced thrombocytopenia; LMWH, low molecular weight heparin; UFH, unfractionated heparin.

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Table 15.3  Estimating the Pretest Probability of Heparin-Induced Thrombocytopenia: The “4 T’s” Scoring System Points (0, 1, or 2 for each of 4 categories: maximum possible score = 8) Date :

2

1

0

Thrombocytopenia* Score = _____________

>50% platelet decrease to nadir ≥20 × 109/L

30%-50% platelet count decrease (or >50% directly resulting from surgery) or nadir 10 − 19 × 109/L

100 µmol/L), marfanoid features, mental retardation, and premature arterial and venous thromboses. It is caused by mutations in either cystathionineβ-synthase or methyl tetrahydrofolate reductase. Contrary to homocystinuria, mild hyperhomocysteinemia is common and occurs in about 5% to 10% of the general population.233 Its clinical relevance and contribution to stroke risk are unknown. Folate supplementation may be considered in patients with hyperhomocysteinemia; however, there is no compelling evidence to suggest that reducing homocysteine levels abrogates stroke risk.



Anticoagulants Parenteral anticoagulants may be broadly divided into two groups: indirect and direct anticoagulants. Indirect anticoagulants rely on plasma cofactors for thrombin inactivation, whereas direct anticoagulants do not. The indirect anticoagulants include UFH, LMWHs, fondaparinux, and danaparoid. The direct agents target thrombin and include recombinant hirudins, bivalirudin and argatroban.

Heparin Heparin is a mucopolysaccharide of heterogeneous molecular size; it can vary in weight from 3,000 to 30,000 kDa and averages approximately 45 saccharide units.241-243 Its major anticoagulant effect is mediated by its interaction with antithrombin (AT), but it also inhibits factors Xa, IXa, XIa, and XIIa. Heparin binds to AT and converts it from a slow to a fast inactivator of thrombin. Heparin binds to AT through a glucosamine unit, which contains a unique pentasaccharide sequence. One third of heparin chains are of sufficient length to bridge the heparin/AT to thrombin, forming a ternary AT/ heparin/thrombin complex, which potentiates inhibition. Heparin then dissociates from thrombin and is available for reuse. Smaller chains that contain the high affinity pentasaccharide can inhibit factor Xa, although thrombin is 10-fold more sensitive to inhibition than factor Xa.244 Heparin also has anticoagulant effects independent of the pentasaccharide sequence. It binds to heparin cofactor II and catalyzes the inactivation of factor IIa; however, this effect is chain length dependent, requiring heparin chains of at least 24 saccharide units.245 Heparin is administered intravenously or subcutaneously. Subcutaneous administration requires higher dosing given the reduced bioavailability. Intravenous (IV) bolus administration can provide an immediate effect. Heparin binds plasma proteins, endothelial cells, and macrophages246,247; this phenomenon results in an unpredictable anticoagulant response and may explain some of the apparent heparin resistance. Heparin resistance may also be due to AT deficiency,248 increased heparin clearance,249,250 elevated factor VIII,251,252 and elevated fibrinogen.252 The risk of bleeding associated with heparin increases at higher doses and with concomitant administration of fibrinolytic agents253,254 or GPIIb/IIIa inhibitors.255 Recent surgery, trauma, invasive procedures, and defects of hemostasis are also risk factors for bleeding.244 Monitoring of heparin and dose adjustment has become standard practice given the variable anticoagulant response. When given in therapeutic doses, the anticoagulant effect is monitored by the aPTT. The activated clotting time (ACT) is used to monitor high heparin doses administered to patients, such as during endovascular neurosurgical procedures or percutaneous coronary interventions. Unlike the evidence supporting a target range for the INR for warfarin monitoring, the data to adjust the dose of heparin to target a therapeutic range are weak. An aPTT ratio of 1.5 to 2.5 times control was suggested by a retrospective study in the 1970s that demonstrated lower risk of VTE; this practice has been widely adopted despite a lack of strong evidence in its support.256 However, neither has this practice been rigorously studied by randomized control trials, nor are

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the same instruments used to measure the aPTT.257-261 Therefore the therapeutic range for the aPTT is laboratory specific.261,262 Although many heparin nomograms exist, none is applicable to all aPTT reagents. For patients who require high levels of heparin administration (>35,000 units/day UFH), it may be reasonable to monitor anti-Xa levels and adjust the dose accordingly because this practice lessens the amount of heparin administered without compromising clinical outcomes.251 The anticoagulant effects of heparin can be reversed with IV protamine sulfate, a protein that complexes with heparin to form a stable salt: 1 mg of IV protamine will neutralize 100 units of IV heparin.244 The half-life of heparin is 60 to 90 minutes; therefore, when reversing with protamine, only heparin administered over the last few hours needs to be considered when calculating the dose. Caution is needed when administering protamine because it can cause anaphylaxis.244 The main side effects of heparin therapy are HIT (see earlier) and osteoporosis.

Low Molecular Weight Heparin LMWHs are derived from UFH and are less active against thrombin relative to factor Xa.263,264 The anti–Xa-to-anti–IIa ratio of LWMHs is 2 to 4 : 1 (based on molecular size distribution), whereas the anti–Xa-to-anti–IIa ratio of UFH is 1 : 1.244 LMWHs are one third the molecular weight of UFH, which roughly corresponds to 15 saccharide units. They have a more predictable pharmacokinetic profile than UFH due to a reduced binding affinity for cells and proteins; this also extends their plasma half-life.265 The lower incidence of HIT also is related to the decrease in platelet binding. The various LMWHs have different anticoagulant profiles and are thus not interchangeable. Routine laboratory monitoring generally is not recommended for most patients treated with LMWH. The ACCP recommends anti-Xa monitoring in some special populations, such as in pregnant women who require treatment with LMWH.244 Others suggest monitoring in obese patients and those with renal insufficiency. The ACCP recommends weight-based dosing in the treatment or prophylaxis of obese patients and preferential use of UFH in patients with severe renal dysfunction.126-128 Although protamine sulfate incompletely neutralizes the anticoagulant effect of LMWHs, it should be administered at a dose of 1 mg per 100 anti-Xa units of LMWH in the acutely bleeding patient if it was administered during the preceding 8 hours.244 A second dose of protamine sulfate at 0.5 mg per 100 units of anti-Xa should be given if bleeding continues. Side effects of LMWH include HIT and osteoporosis. The frequency of HIT is threefold lower with LMWH; however, LMWHs can form complexes with PF4 that are capable of binding HIT antibodies and therefore LMWHs should not be used in the treatment of HIT.

Fondaparinux Fondaparinux is a synthetic analog of the AT-binding pentasaccharide found in both UFH and LMWH that has higher anti-Xa activity than LMWH and a longer half-life (~17 hours).266,267 It does not increase the rate of thrombin inhibition by AT. Due to its predictable pharmacokinetics and negligible nonspecific binding, fondaparinux can be administered

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subcutaneously once daily in fixed doses without laboratory monitoring. It is not intended for use in patients with renal insufficiency. Routine monitoring is not recommended, but if needed the anticoagulant activity can be measured with anti-Xa assays. The anticoagulant effects of fondaparinux are not reversible with protamine sulfate; recombinant factor VIIa may be effective.268 There have been no reports of HIT with fondaparinux, and it has been used to safely treat patients with this disorder.269

Danaparoid Danaparoid is a mixture of glycosaminoglycans (heparan sulfate, dermatan sulfate, and chondroitin sulfate); its anticoagulant properties are derived from inhibition of factor Xa in an AT-dependent manner.244 Its use is limited to treatment of HIT. An advantage of danaparoid is that it does not prolong INR, which is beneficial when transitioning patients to vitamin K antagonists. However, the 25-hour half-life is a significant disadvantage because there is no antidote for it.

Direct Anticoagulants In contrast to the indirect anticoagulants, the direct thrombin inhibitors bind to thrombin and block its enzymatic activity. The aPTT is used to monitor the anticoagulant effects of direct thrombin inhibitors; however, this test is not always accurate. The dose response is not linear and the aPTT plateaus at high doses of these drugs. The ecarin clotting time may be more accurate, but lack of availability and standardization generally precludes its routine use.

Hirudin Hirudin, derived from the salivary gland of the medicinal leech, is available in recombinant form as lepirudin or desirudin. They both irreversibly inactivate thrombin. They have an identical pharmacokinetic profile and mechanism of action; the amino-terminal domain interacts with active site of thrombin, and the carboxy-terminus binds to the substrate-binding site. The plasma half-life of the hirudins is 60 minutes when administered IV and 120 minutes when given subcutaneously.270 Hirudins are renally excreted and so are contraindicated in patients with renal failure.271 When used to treat HIT, the anticoagulant effect of lepirudin is monitored by the aPTT with the goal ratio between 1.5 and 2.5. When administered for thromboprophylaxis, routine monitoring is unnecessary.244 Antibodies against hirudin develop in 40% of patients treated with lepirudin.244 These antibodies generally do not have much clinical impact; however, analphylaxis may occur if patients with antibodies are reexposed to hirudin.

Bivalirudin Bivalirudin is a hirudin analog that reversibly binds to the active site of thrombin. Bivalirudin has a plasma half-life of 25 minutes after IV injection. Bivalirudin is licensed as an alternative to heparin for patients undergoing percutaneous coronary interventions (PCIs) in patients with HIT. In contrast to hirudin, bivalirudin is not immunogenic. The anticoagulant effect may be monitored with the aPTT

and the ACT, but the results are variable and unreliable.244,272 New anti-factor IIa assays hold promise to better monitor the effects of this anticoagulant without a veritable antidote.272

Argatroban Argatroban is a reversible thrombin inhibitor with a 45minute plasma half-life. It is hepatically metabolized via the cytochrome p450 system and caution must be used in the face of liver dysfunction.244 It is indicated for the treatment of HIT and as an alternative to heparin for PCI in patients with HIT. All of the direct thrombin inhibitors increase the INR, but this is especially true of argatroban. This complicates the transition from argatroban to vitamin K antagonists. Some target a goal INR greater than 4 when vitamin K antagonists (VKAs) are given in conjunction with direct thrombin inhibitors; however, monitoring a chromogenic assay of factor X levels may be a safer practice.244

Oral Direct Thrombin Inhibitors The need for a fixed-dose oral anticoagulant with a broader therapeutic window and lower inter- and intrapatient variability that does not require serial laboratory testing and dose adjustment led to the novel anticoagulants dabigatran, rivaroxaban, apixaban, and edoxaban. These agents inhibit thrombin (dabigatran) or factor Xa (rivaroxaban, apixaban, and edoxaban) directly rather than through a cofactor. Although they reversibly bind their substrate, their anticoagulant effect is irreversible because there is no veritable antidote. These agents provide rapid onset to therapeutic effect in contrast to warfarin. They all demonstrate low variability in pharmacodynamic characteristics, thus obviating the need for routine coagulation monitoring. Apixaban has demonstrated efficacy and safety for the prevention of venous thromboembolism after elective hip or knee replacement273,274 and to prevent stroke in patients with nonvalvular atrial fibrillation (AF).275 The FDA has approved rivaroxaban for the prevention of stroke secondary to AF. Dabigatran has been compared with warfarin to prevent stroke and systemic embolization in more than 18,000 patients with AF.276 At a dose of 110 mg twice daily, dabigatran proved noninferiority to warfarin and demonstrated lower rates of symptomatic ICH. A higher dose of 150 mg twice daily was associated with lower rates of stroke but similar rates of symptomatic hemorrhage compared with warfarin. Although these oral anticoagulants have proven effective at reducing secondary stroke due to AF, concerns remain about the lack of reversibility of its anticoagulant effect.

Vitamin K Antagonists Warfarin is a vitamin K antagonist (VKA) that produces an anticoagulant effect by obstructing the cyclic interconversion of vitamin K and its 2,3 epoxide, thereby modulating γ-carboxylation of glutamate residues on the N-terminal regions of vitamin K–dependent proteins. Not only do VKAs have anticoagulant properties due to inhibition of vitamin K–dependent coagulation factors II, VII, IX, and X, but they also may have procoagulant properties by inhibiting carboxylation of the regulatory anticoagulant proteins C, S, and Z.277

VKAs are used to treat venous thromboembolism, atrial fibrillation, and valvular heart disease.198 They are complex agents with a narrow therapeutic index and many food and drug interactions. VKAs require routine monitoring and frequent dose adjustments to maintain their safety and efficacy. Advances in warfarin management have been made through dedicated anticoagulation clinics and patient self-testing and management. Despite these advances, in 2007 more than 60,000 emergency department visits were related to warfarin therapy, the majority of which were for acute hemorrhage.278 Health care resources dedicated to warfarin management substantially exceed the cost of the drug itself.

Point of Care Testing POCT is diagnostic testing performed with rapid generation of results at or near the site of the patient in order to optimize patient care. These assays often do not require laboratory support, are easy to perform, and efficiently deliver results. Some of these tests use capillary blood and others use venous blood or citrated samples. Careful attention to manufacturers’ recommendations is necessary because erroneous values may be obtained if the inappropriate sample type is used. This discussion focuses on those POCTs with a self-contained reagent system. Much of this literature has been driven by use of POCT in cardiac surgery, because these patients have platelet dysfunction and high bleeding risk and require antiplatelet and anticoagulant medications. Some POCTs do not contain a self-contained reagent system and may require samples to be pipetted or centrifuged. Quality assurance may be limited because there are no formal external quality assessment measures for many of these devices, although some commercially available quality control samples with established reference ranges are available. Internal quality controls also must be performed routinely to ensure reliability of results. Maintenance of current standard operating procedures specifying sample collection, handling and storing practices, selection of appropriate reagents, and generation of adequate records and reporting are mandatory for optimal utility. The quality of the results also depends on personnel and frequency of practice. The combination of internal and external quality assurance is imperative to provide both precise and accurate results. Practical limitations of POCT devices include (1) difficulty in obtaining sufficient sample volume; (2) difficulty in accessing test strip or application reservoir; (3) insufficient time to deliver blood sample; (4) inaccuracies based on presence of heparin or other medications/drugs; and (5) ineligibility for patients with blood abnormalities such as presence of lupus anticoagulant or extremes of Hct.

Prothrombin Time/International Normalized Ratio Historically, blood product replacement after surgery has been based on clinical judgment. The POCT PT/INR can guide blood product administration expediently in patients who undergo major surgery. Different devices are based on different principles to generate the INR value. Some use light reflectance properties as metal particles move through a magnetic field, whereas others monitor movement of blood in capillary tubes, changes in electrochemical impedence, or thrombin

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generation through cleavage of a peptide substrate.143 Inaccuracies may be predicted by the principle underlying the technology. For example, POCT monitors that measure capillary blood flow may give lower INR values for samples with a high Hct.

Activated Partial Thromboplastin Time The aPTT may be used to screen preoperatively for abnormalities in hemostasis (especially when used with the PT) or to guide heparin dosing. A number of studies have shown that POCT devices can accurately measure the aPTT and thus guide management of patients on UFH during a variety of procedures.279-284 However, the correlation between POCT aPTT and central laboratory aPTT remains controversial.285-287 Moreover, POC aPTT may be more susceptible to effects of other medications such as aprotinin or epsilon aminocaproic acid.288 The demand for POCT aPTT has been low and the reliability of the results remains suspect. Only the Hemochron device remains available.289

Activated Clotting Time The ACT is exclusively used to monitor anticoagulation with high doses of UFH (e.g., during cardiac bypass surgery or interventional vascular procedures) because high concentrations of UFH result in an unclottable aPTT. A baseline ACT should be obtained on all patients before UFH administration. The ACT may be affected by the choice of activator, hypothermia, hemodilution, or medications. Currently available POCT devices for the aPTT include the Hepcon Haemostasis Management System (HMS), the Hemochron Response device, the Actalyke MAX-ACT, the Hemochron Junior II and the i-Stat analyzer.

Estimations and Modifications of the Thrombin Time Historically, the thrombin time was used to monitor patients on UFH; however, there is a poor correlation between heparin concentration and thrombin time. Furthermore, at high concentrations of heparin, the thrombin time becomes unclottable and therefore is unsuitable to monitor patients treated with high UFH doses. The high dose thrombin time (HiTT, Hemochron) is more specific to heparin effects than the ACT.290 In contrast to the ACT, the HiTT is not affected by hypothermia or hemodilution. However, there is poor correlation between the HiTT and the ACT, which has been previously validated in the cardiac surgery population. The Hepcon HMS establishes whole blood heparin concentration using an automated heparin-protamine titration method. There are some concerns that HMS may overestimate the heparin dose required to maintain adequate anticoagulation as compared with the ACT method.291

Thromboelastography Thromboelastography (TEG) and rotational thromboelastometry (ROTEM) are POCTs that measure clot formation, clot strength, and clot dissolution. It has been suggested that this technology better reflects in vivo hemostasis and thus may provide more information than standard coagulation assays,

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especially in the perioperative setting. TEG analyzes hemostasis using whole blood, which better accounts for the effect of cellular elements in the coagulation process than the traditional “cascade” model. The cascade model of coagulation is helpful to understand hemostasis in vitro but does not fully explain it in vivo. TEG has been shown to significantly reduce the use of blood component therapy144,145 and overall blood loss.292 TEG yields several parameters of clotting.293 The reaction time, R, represents the time until to initial fibrin formation after mechanical stress and reflects the ability to generate thrombin. Prolongation of this time reflects anticoagulant activity, whereas a shortened R time suggests hypercoagulability. The alpha, or angle parameter, represents the rate of fibrin generation and cross linkage. The faster the rate of fibrin generation, the larger is the measured angle. The K value also measures clot kinetics; specifically it assesses the time it takes to reach amplitude of 20 mm. The maximum amplitude (MA) represents the tensile strength of the clot; the stronger the clot, the larger the MA. Platelets contribute most to clot strength and therefore contribute most significantly (80%) to the MA, whereas fibrinogen, which binds platelets, contributes about 20%. The G value is an exponential expression of the MA; it is more sensitive to changes in platelet function than the MA at higher values. The coagulation index (CI) represents the linear relationship between the R value, the K value, the angle, and MA. A CI greater than 3 represents hypercoagulability. The estimated percent lysis (EPL) and LY30 (lysis after 30 minutes) are measures of clot dissolution. The EPL is the percent change in the MA over time and the LY30 is the amplitude 30 minutes after the MA divided by the MA. An EPL greater than 7.5% and an LY30 greater than 15% represent fibrinolysis; if associated with a CI less than 1 is it primary fibrinolysis with a tendency toward bleeding, and if CI is greater than 3 it is secondary fibrinolysis, not characterized by bleeding. The analysis was originally performed on whole blood without an activator. Subsequent modifications have been developed that allow faster result generation and test standardization. The choice of activator depends on the clinical setting. Rapid-thromboelastography (r-TEG), uses TF as the activator; it allows for faster curve generation but compromises some of the results (e.g., the R value). Without activation TEG takes 30 to 60 minutes to provide all information. Quality assurance needs to be performed daily. Since 2000, a variety of POC testing (POCT) devices have become available to examine platelet function and measure the effect of antiplatelet medications (see previous section on Platelet Function Assays).

D-Dimer Assays Combined with a pretest probability score, D-dimer assays can be used to reliably exclude a diagnosis of VTE. Some D-dimer assays use capillary blood whereas others use heparinized blood or citrated plasma. The sensitivity of POC D-dimer tests appears to be less sensitive than the best available clinical laboratory tests.211,294-296

Conclusion Anemia, bleeding, and thrombosis occur frequently in the NCCU, and their treatment can be complicated. The diagnosis

of anemia, through serial laboratory testing, exacerbates the condition. Anemic patients may be at higher risk of cerebral ischemia. Neurosurgical patients are among the most frequent of surgical populations to develop DVT and fatal PE given postoperative immobility, hemiparesis, and altered mental state. Combined modalities of thromboprophylaxis and intensive surveillance may prove the best method to identify and treat VTE. Understanding the pathogenesis of these various conditions, suspicion that they may exist, and multimodality monitoring in the NCCU may identify these disorders earlier, thereby minimizing the devastating impact of these common ailments.

References 1. Bunn HF. Approach to the anemias. 24th ed. Philadelphia: Elsevier; 2012. 2. Marks PW, Glader B. Approach to anemia in the adult and child. 5th ed. Philadelphia: Churchill Livingstone; 2009. 3. Ginder G. Microcytic and hypochromic anemias. In: Goldman L, Schafer A, editors. Goldman’s Cecil Textbook of Medicine. 24th ed. Philadelphia: Elsevier; 2012. p. 1039–44. 4. Nutritional anaemias. Report of a WHO scientific group. World Health Organ Tech Rep Ser 1968;405:5–37. 5. Hebert PC, Wells G, Tweeddale M, et al. Does transfusion practice affect mortality in critically ill patients? Transfusion Requirements in Critical Care (TRICC) investigators and the Canadian Critical Care Trials Group. Am J Respir Crit Care Med 1997;155(5):1618–23. 6. Corwin HL. Blood transfusion in the critically ill patient. Dis Mon 1999;45(10):409–26. 7. Groeger JS, Guntupalli KK, Strosberg M, et al. Descriptive analysis of critical care units in the United States: patient characteristics and intensive care unit utilization. Crit Care Med 1993;21(2):279–91. 8. Carson JL, Duff A, Poses RM, et al. Effect of anaemia and cardiovascular disease on surgical mortality and morbidity. Lancet 1996;348(9034): 1055–60. 9. Spiess BD, Ley C, Body SC, et al. Hematocrit value on intensive care unit entry influences the frequency of Q-wave myocardial infarction after coronary artery bypass grafting. The Institutions of the Multicenter Study of Perioperative Ischemia (McSPI) research group. J Thorac Cardiovasc Surg 1998;116(3):460–7. 10. Kuriyan M, Carson JL. Anemia and clinical outcomes. Anesthesiol Clin North America 2005;23(2):315–25, vii. 11. McKechnie RS, Smith D, Montoye C, et al. Prognostic implication of anemia on in-hospital outcomes after percutaneous coronary intervention. Circulation 2004;110(3):271–7. 12. Chant C, Wilson G, Friedrich JO. Anemia, transfusion, and phlebotomy practices in critically ill patients with prolonged ICU length of stay: a cohort study. Crit Care 2006;10(5):R140. 13. Corwin HL, Gettinger A, Pearl RG, et al. The CRIT Study: anemia and blood transfusion in the critically ill—current clinical practice in the United States. Crit Care Med 2004;32(1):39–52. 14. Vincent JL, Baron JF, Reinhart K, et al. Anemia and blood transfusion in critically ill patients. JAMA 2002;288(12):1499–507. 15. Smoller BR, Kruskall MS. Phlebotomy for diagnostic laboratory tests in adults: pattern of use and effect on transfusion requirements. N Engl J Med 1986;314(19):1233–5. 16. Shander A. Anemia in the critically ill. Crit Care Clin 2004;20(2):159–78. 17. Faquin WC, Schneider TJ, Goldberg MA. Effect of inflammatory cytokines on hypoxia-induced erythropoietin production. Blood 1992;79(8):1987–94. 18. Rogiers P, Zhang H, Leeman M, et al. Erythropoietin response is blunted in critically ill patients. Intensive Care Med 1997;23(2):159–62. 19. Rodriguez RM, Corwin HL, Gettinger A, et al. Nutritional deficiencies and blunted erythropoietin response as causes of the anemia of critical illness. J Crit Care 2001;16(1):36–41. 20. Buttarello M, Plebani M. Automated blood cell counts: state of the art. Am J Clin Pathol 2008;130(1):104–16. 21. Stachon A, Kempf R, Holland-Letz T, et al. Daily monitoring of nucleated red blood cells in the blood of surgical intensive care patients. Clin Chim Acta 2006;366:329–35. 22. Parisotto R, Wu M, Ashenden MJ, et al. Detection of recombinant human erythropoietin abuse in athletes utilizing markers of altered erythropoiesis. Haematologica. 2001;86:128–37.

23. Zini G, DiMario A, Garzia M. Clinical usefulness of red cell fragments identified by the Sysmex XE-2100 hematological analyser [lecture]. Proceeding of the Sysmex European Haematology Symposium. Lisbon, Portugal; June 13-14, 2007. 24. Lesesve JF, Salignac S, Alla F, et al. Comparative evaluation of schistocyte counting by an automated method and by microscopic determination. Am J Clin Pathol 2004;121:739–45. 25. Berkow L, Rotolo S, Mirski E. Continuous noninvasive hemoglobin monitoring during complex spine surgery. Anesth Analg 2011;113(6): 1396–402. 26. Frasca D, Dahyot-Fizelier C, Catherine K, et al. Accuracy of a continuous noninvasive hemoglobin monitor in intensive care unit patients. Crit Care Med 2011;39(10):2277–82. 27. Lamhaut L, Apriotesei R, Combes X, et al. Comparison of the accuracy of noninvasive hemoglobin monitoring by spectrophotometry (SpHb) and HemoCue with automated laboratory hemoglobin measurement. Anesthesiology 2011;115(3):548–54. 28. Wartenberg KE, Schmidt JM, Claassen J, et al. Impact of medical complications on outcome after subarachnoid hemorrhage. Crit Care Med 2006;34(3):617–23; quiz 24. 29. Kramer AH, Gurka MJ, Nathan B, et al. Complications associated with anemia and blood transfusion in patients with aneurysmal subarachnoid hemorrhage. Crit Care Med 2008;36(7):2070–5. 30. Van Beek JG, Mushkudiani NA, Steyerberg EW, et al. Prognostic value of admission laboratory parameters in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007;24(2):315–28. 31. Salim A, Hadjizacharia P, DuBose J, et al. Role of anemia in traumatic brain injury. J Am Coll Surg 2008;207(3):398–406. 32. Steyerberg EW, Mushkudiani N, Perel P, et al. Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med 2008;5(8):e165; discussion e. 33. Kramer AH, Zygun DA, Bleck TP, et al. Relationship between hemoglobin concentrations and outcomes across subgroups of patients with aneurysmal subarachnoid hemorrhage. Neurocrit Care 2009;10(2):157–65. 34. Kimberly WT, Wu O, Arsava EM, et al. Lower hemoglobin correlates with larger stroke volumes in acute ischemic stroke. Cerebrovasc Dis Extra 2011;1(1):44–53. 35. Zygun DA, Nortje J, Hutchinson PJ, et al. The effect of red blood cell transfusion on cerebral oxygenation and metabolism after severe traumatic brain injury. Crit Care Med 2009;37(3):1074–8. 36. Kurtz P, Schmidt JM, Claassen J, et al. Anemia is associated with metabolic distress and brain tissue hypoxia after subarachnoid hemorrhage. Neurocrit Care 2010;13(1):10–6.

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37. Oddo M, Milby A, Chen I, et al. Hemoglobin concentration and cerebral metabolism in patients with aneurysmal subarachnoid hemorrhage. Stroke 2009;40:1275–81. 38. Leal-Noval SR, Munoz-Gomez M, Murillo-Cabezas F. Optimal hemoglobin concentration in patients with subarachnoid hemorrhage, acute ischemic stroke and traumatic brain injury. Curr Opin Crit Care 2008;14(2): 156–62. 39. Sahuquillo J, Poca MA, Garnacho A, et al. Early ischaemia after severe head injury. Preliminary results in patients with diffuse brain injuries. Acta Neurochir (Wien) 1993;122(3-4):204–14. 40. Vespa P, Bergsneider M, Hattori N, et al. Metabolic crisis without brain ischemia is common after traumatic brain injury: a combined microdialysis and positron emission tomography study. J Cereb Blood Flow Metab 2005;25(6):763–74. 41. Menon DK. Brain ischaemia after traumatic brain injury: lessons from 15O2 positron emission tomography. Curr Opin Crit Care 2006;12(2): 85–9. 42. Graham DI, Adams JH, Doyle D. Ischaemic brain damage in fatal non-missile head injuries. J Neurol Sci 1978;39(2-3):213–34. 43. Vespa PM. The implications of cerebral ischemia and metabolic dysfunction for treatment strategies in neurointensive care. Curr Opin Crit Care 2006;12(2):119–23. 44. McLaughlin MR, Marion DW. Cerebral blood flow and vasoresponsivity within and around cerebral contusions. J Neurosurg 1996;85(5):871–6. 45. Carlson AP, Schermer CR, Lu SW. Retrospective evaluation of anemia and transfusion in traumatic brain injury. J Trauma 2006;61(3):567–71. 46. Diringer MN, Bleck TP, Claude Hemphill J, 3rd, et al. Critical care management of patients following aneurysmal subarachnoid hemorrhage: recommendations from the Neurocritical Care Society’s Multidisciplinary Consensus Conference. Neurocrit Care 2011;15(2):211–40. 47. Le Roux PD. Anemia and transfusion after subarachnoid hemorrhage. Neurocrit Care 2011;15(2):342–53. 48. Vincent JL, Yagushi A, Pradier O. Platelet function in sepsis. Crit Care Med 2002;30(5 Suppl):S313–17. 49. Cawley MJ, Wittbrodt ET, Boyce EG, et al. Potential risk factors associated with thrombocytopenia in a surgical intensive care unit. Pharmacotherapy 1999;19(1):108–13. 50. Baughman RP, Lower EE, Flessa HC, et al. Thrombocytopenia in the intensive care unit. Chest 1993;104(4):1243–7.

A complete list of references for this chapter can be found online at www.expertconsult.com.

Section II—Clinical and Laboratory Assessment 147.e1



References 1. Bunn HF. Approach to the anemias. 24th ed. Philadelphia: Elsevier; 2012. 2. Marks PW, Glader B. Approach to anemia in the adult and child. 5th ed. Philadelphia: Churchill Livingstone; 2009. 3. Ginder G. Microcytic and hypochromic anemias. In: Goldman L, Schafer A, editors. Goldman’s Cecil Textbook of Medicine. 24th ed. Philadelphia: Elsevier; 2012. p. 1039–44. 4. Nutritional anaemias. Report of a WHO scientific group. World Health Organ Tech Rep Ser 1968;405:5–37. 5. Hebert PC, Wells G, Tweeddale M, et al. Does transfusion practice affect mortality in critically ill patients? Transfusion Requirements in Critical Care (TRICC) investigators and the Canadian Critical Care Trials Group. Am J Respir Crit Care Med 1997;155(5):1618–23. 6. Corwin HL. Blood transfusion in the critically ill patient. Dis Mon 1999;45(10):409–26. 7. Groeger JS, Guntupalli KK, Strosberg M, et al. Descriptive analysis of critical care units in the United States: patient characteristics and intensive care unit utilization. Crit Care Med 1993;21(2):279–91. 8. Carson JL, Duff A, Poses RM, et al. Effect of anaemia and cardiovascular disease on surgical mortality and morbidity. Lancet 1996;348(9034): 1055–60. 9. Spiess BD, Ley C, Body SC, et al. Hematocrit value on intensive care unit entry influences the frequency of Q-wave myocardial infarction after coronary artery bypass grafting. The Institutions of the Multicenter Study of Perioperative Ischemia (McSPI) research group. J Thorac Cardiovasc Surg 1998;116(3):460–7. 10. Kuriyan M, Carson JL. Anemia and clinical outcomes. Anesthesiol Clin North America 2005;23(2):315–25, vii. 11. McKechnie RS, Smith D, Montoye C, et al. Prognostic implication of anemia on in-hospital outcomes after percutaneous coronary intervention. Circulation 2004;110(3):271–7. 12. Chant C, Wilson G, Friedrich JO. Anemia, transfusion, and phlebotomy practices in critically ill patients with prolonged ICU length of stay: a cohort study. Crit Care 2006;10(5):R140. 13. Corwin HL, Gettinger A, Pearl RG, et al. The CRIT Study: anemia and blood transfusion in the critically ill—current clinical practice in the United States. Crit Care Med 2004;32(1):39–52. 14. Vincent JL, Baron JF, Reinhart K, et al. Anemia and blood transfusion in critically ill patients. JAMA 2002;288(12):1499–507. 15. Smoller BR, Kruskall MS. Phlebotomy for diagnostic laboratory tests in adults: pattern of use and effect on transfusion requirements. N Engl J Med 1986;314(19):1233–5. 16. Shander A. Anemia in the critically ill. Crit Care Clin 2004;20(2):159–78. 17. Faquin WC, Schneider TJ, Goldberg MA. Effect of inflammatory cytokines on hypoxia-induced erythropoietin production. Blood 1992;79(8):1987–94. 18. Rogiers P, Zhang H, Leeman M, et al. Erythropoietin response is blunted in critically ill patients. Intensive Care Med 1997;23(2):159–62. 19. Rodriguez RM, Corwin HL, Gettinger A, et al. Nutritional deficiencies and blunted erythropoietin response as causes of the anemia of critical illness. J Crit Care 2001;16(1):36–41. 20. Buttarello M, Plebani M. Automated blood cell counts: state of the art. Am J Clin Pathol 2008;130(1):104–16. 21. Stachon A, Kempf R, Holland-Letz T, et al. Daily monitoring of nucleated red blood cells in the blood of surgical intensive care patients. Clin Chim Acta 2006;366:329–35. 22. Parisotto R, Wu M, Ashenden MJ, et al. Detection of recombinant human erythropoietin abuse in athletes utilizing markers of altered erythropoiesis. Haematologica. 2001;86:128–37. 23. Zini G, DiMario A, Garzia M. Clinical usefulness of red cell fragments identified by the Sysmex XE-2100 hematological analyser [lecture]. Proceeding of the Sysmex European Haematology Symposium. Lisbon, Portugal; June 13-14, 2007. 24. Lesesve JF, Salignac S, Alla F, et al. Comparative evaluation of schistocyte counting by an automated method and by microscopic determination. Am J Clin Pathol 2004;121:739–45. 25. Berkow L, Rotolo S, Mirski E. Continuous noninvasive hemoglobin monitoring during complex spine surgery. Anesth Analg 2011;113(6):1396–402. 26. Frasca D, Dahyot-Fizelier C, Catherine K, et al. Accuracy of a continuous noninvasive hemoglobin monitor in intensive care unit patients. Crit Care Med 2011;39(10):2277–82. 27. Lamhaut L, Apriotesei R, Combes X, et al. Comparison of the accuracy of noninvasive hemoglobin monitoring by spectrophotometry (SpHb) and HemoCue with automated laboratory hemoglobin measurement. Anesthesiology 2011;115(3):548–54.

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Monitoring Inflammation Alejandro M. Spiotta, Alan Siu, and J. Javier Provencio

Introduction The basic tenet of neurocritical care is prevention of secondary injury. Secondary injuries following the initial ictus include global increases in intracranial pressure (ICP), alterations in cerebral perfusion, hydrocephalus, and seizures, among others. In addition, systemic insults such as infections, hypotension, thromboemboli, hyperglycemia, hyperthermia, malnutrition, and other complications can affect patients in the neurocritical care unit (NCCU) adversely. Accumulating evidence suggests that inflammation can exacerbate secondary injury in brain disease and in particular subarachnoid hemorrhage, vasospasm, traumatic brain injury (TBI), and stroke; it can even be epileptogenic.1-6 Monitoring neuroinflammation therefore may allow better understanding of the impact of therapies aimed at preventing or minimizing secondary injury. Whether prevention of inflammation will improve patient outcome following brain injury is still to be defined because although pharmacologic therapies to attenuate inflammation can ameliorate pathology, microglial activation that is central to the inflammatory response also plays a role in recovery and regeneration (i.e., inflammation may have a dual role).

Monitoring Neuroinflammation As the understanding of the pathophysiologic process following acute brain injury including subarachnoid hemorrhage (SAH), stroke, and TBI has increased, awareness about the deleterious effects of inflammatory activation as both a trigger and exacerbating factor of secondary injury has created new opportunities in monitoring neuroinflammation. For example, findings from clinical studies suggest that neutrophils play a critical role in ischemia-reperfusion injury, because tissue damage is associated with extent of neutrophil infiltration.7-9 The critical role that systemic as well as local inflammatory activators play in determining the extent of central nervous system (CNS) injury following an ictus is highlighted by the emergence and widespread use of anti-inflammatory pharmaceuticals, such as statins, in neurocritical care.10-14 3-Hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase inhibitors, commonly known as statins, have lipidlowering properties, and animal models of acute brain injury have demonstrated their anti-inflammatory properties.15-18 There is mounting evidence for the role of neuroinflammation as a contributor to secondary brain tissue injury in stroke, 148

neurotrauma, SAH, and various chronic CNS diseases. Inflammatory mediators are indeed elevated in the cerebrospinal fluid (CSF) and serum of patients with acute and chronic brain injury, and are associated with poor outcome.19-25 Various animal models also point to potential protective mechanisms with the inhibition of proinflammatory mediators. As the role of neuroinflammation in secondary brain injury becomes more evident, the need to monitor its activity in the NCCU becomes important. The knowledge that may be gained by monitoring neuroinflammation and its clinical utility can be organized into three main areas: 1. Identifying risk factors to predict secondary injury 2. Providing endpoints to monitor responses to specific therapies aimed at modulating the inflammatory state 3. Gaining insights into the pathophysiology of the disease process Monitoring of neuroinflammation thus may provide a more sensitive and earlier detection of secondary injury and in turn widen the therapeutic window. Furthermore, studying the response of the various measured parameters to conventional and experimental medical and interventional therapies should augment our knowledge of the disease course and potentially lead to new therapeutic strategies.

Basic Science of Inflammation The brain was once considered to be an “immune-privileged” organ system, inaccessible and independent from systemic inflammation. Although the CNS has unique features, this view has largely fallen out of favor because there is accumulating evidence of crosstalk between the CNS and the immune system outside of the CNS. For example, CNS cells have been shown to modulate peripheral immune function in response to peripheral disease and injury through the systemic release of various cytokines (i.e., interleukin-1 [IL-1], IL-6, tumor necrosis factor-α [TNFα]) and vagal efferents.26,27 Cerebral edema has many potential causes but can be considered an inflammatory process. Indeed IL-1 neutralizing antibodies in animal models can attenuate brain edema.28 Because the skull is functionally a closed box, significant development of edema occupies the excess space in the cranium, after which pressure increases and so can damage neurons and glia. Cerebral edema occurs at different times in © Copyright 2013 Elsevier Inc. All rights reserved.

different cerebral injuries. In TBI and SAH, cerebral edema develops quickly and can cause increased ICP in many patients. Conversely, in ischemic stroke, cerebral edema develops slowly over the first 72 hours after the initial ictus. The reason for the differences in these time courses is not well defined; however, the course of cerebral edema could be predicted by monitoring inflammation. Inflammatory processes contribute to CNS injury and neurodegeneration.20,27 In addition there is accumulating evidence that inflammation and in particular leukocyte-endothelial cell interactions, play a critical role in the pathogenesis of vasospasm after SAH2,29 and that inflammatory processes contribute to formation of cerebral aneurysms.30-32 Various types of acute and chronic brain injuries result in gliosis, a reaction characterized by the activation, proliferation, and hypertrophy of mononuclear phagocytic-type cells,33-35 which occurs in a well-defined manner to promote a systematic restoration of the brain parenchyma in the setting of neuronal injury. This process is mediated by the resident astrocytes and microglia, which produce various chemical mediators to recruit peripherally derived immune cells to further enhance the inflammatory response. The inhibition of these chemical mediators (i.e., TNFα, IL-1) and the key components that modulate leukocyte trafficking across the blood-brain barrier (BBB) have shown great potential to improve outcome in neuroinflammatory diseases such as multiple sclerosis and hold the same potential in acute brain injury (natalizumab therapy).

Biology of the Brain’s Immune System Inflammatory processes within the CNS are different from the periphery because the CNS parenchyma lacks resident dendritic cells, with inflammation instead being initiated by the resident microglia.36 The exact role of microglia remains under debate because they release a number of factors that modulate both secondary injury and recovery after injury, including pro- and anti-inflammatory cytokines, chemokines, nitric oxide, prostaglandins, growth factors, and superoxide species.37 The most unique quality, however, is the presence of a BBB that regulates the subsequent immune amplification by the peripheral inflammatory cells. The BBB, along with the neuroepithelial cells, modulate the inflammatory mediators and ultimately the peripheral leukocytes that participate in a neuroinflammatory state.36,38-41 These key mediators, namely the cytokines and adhesion molecules, are the focus of current drug development.42 CNS injury can result in acute or chronic neurodegeneration. In the acute setting, conditions such as TBI and cerebral ischemia lead to parenchymal injury that is characterized by substantial nerve cell loss from excitotoxicity (i.e., glutamate release), oxidative stress, and regional electrolyte disturbances among other pathophysiologic processes. Proinflammatory cytokines are elevated in human CSF and serum after TBI. In addition, increased microglial activation can be detected in vivo using the positron emission tomography (PET) ligand [11C](R)PK11195 even years after an acute injury.43 Animal models of acute injury have further implicated these proinflammatory cytokines as contributors to the extent of brain injury because their inhibition can reduce the extent of cell death. Extensive investigations into various conditions of

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chronic neurodegeneration such as multiple sclerosis and Alzheimer’s disease have also implicated a role for inflammation,44,45 because cytokines such as TNFα and interferon-γ (IFNγ) are elevated in the CSF. In addition, in vitro studies point to inflammation’s damaging effects on neurons, whereas cytokine inhibition in animal models slows the disease process.46 Interestingly, immune responses also are necessary for neuroregeneration, suggesting there is an innate balance between adaptive and deleterious immune activation or immunomodulation.47 The entry of leukocytes into the CNS parenchyma depends on the expression of specific molecules by the endothelium (intracellular adhesion molecules [ICAMs], integrins, selectins, and chemokines) along the capillary and postcapillary venules in the brain. The production of chemokines and the activation of the endothelium are initiated by the activated parenchymal microglia, which produce the cytokines and other inflammatory mediators to further stimulate the inflammatory cascade.36 The activated endothelium is marked by an up-regulation of cell-adhesion molecules (i.e., selectins and integrins) that act to increase interactions to anchor peripheral leukocytes to promote transmigration. In this multistep paradigm of leukocyte-endothelial interactions to cross the BBB, the first step is tethering, which is characterized by a transient contact between the glycosylated ligands on leukocytes and selectins on the endothelium. The next step is rolling, which is mediated by the shear forces of flowing blood to promote locomotion of the leukocyte and increase exposure to activating factors (i.e., cytokines, chemokines) immobilized on the endothelial luminal surface. Further activation of the leukocytes is characterized by conformational changes of integrins into a higher affinity state for stronger interactions with endothelial cell-adhesion molecules (ICAM-1, vascular cell adhesion molecule 1 [VCAM-1]), resulting in leukocyte arrest onto the endothelial surface. The arrested leukocytes then can extend protrusions enriched in chemokine receptors, and extravasate across the BBB by either a paracellular or transcellular route. Various matrix metalloproteinases (MMPs) are secreted to facilitate the transmigration process.

The Febrile State: Monitoring Brain and Body Temperature Fever is the oldest and most easily measured marker of an underlying inflammatory condition, with careful records of elevated temperature and its relationship to disease course dating back to antiquity.48 Raised core body temperature is associated with worse outcome following a variety of acute neurologic insults.49-54 The exact mechanism by which hyperthermia exacerbates CNS injury is not yet fully elucidated. Animal infarct models demonstrate that hyperthermia can enhance the depth and extent of injury by one of two mechanisms: increased cytokine release and inflammation or increased energy expenditure and a widened metabolic gap.5559 However, hyperthermia in a brain-injured patient has many disparate causes. First, pharmaceutical and infectious etiologies are common.60-62 Second, there may be direct hypothalamic injury. Third, factors such as heat shock protein (HSP) synthesis, release of proinflammatory cytokines such as IL-1, IL-6, TNFα, and interferon, or increased glutamate63-65 each,

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or in combination, may act as the stimulus to trigger fever after TBI (for review see reference 62). Factors that may aggravate neurologic outcome in the setting of hyperthermia include increased glucocorticoid production, increased metabolic expenditure, altered oxygen consumption, glutamate or nitric oxide release, increased myeloid cell and cytokine activity, or increased vascular permeability.58,66-70 Given the complex interplay between factors for fever following SAH, it is not surprising that fever has been found to be an independent risk factor for the development of vasospasm following SAH in some studies,53,54 whereas others have not found this relationship.71 Fever at admission also is a risk factor for vasospasm after TBI72 and is associated with poor clinical grade after aneurysm rupture.73 It is now possible to routinely monitor brain temperature (BT; see Chapter 37). Although brain and body temperature may correlate after SAH and TBI, average BT is usually greater than the average rectal temperature by about 1° C. The difference between brain and body temperature becomes greater as a patient becomes febrile.74-77 The effect of BT on brain physiology is not well understood. Some studies have demonstrated that fever may be associated with increased ICP,75 while others suggest that brain hyperthermia may not affect brain oxygen78 or may even increase it.79 In part these different results may be associated with changes in cerebral blood volume or cerebral blood flow. On the other hand, microdialysis studies suggest that fever control can attenuate markers of cerebral energy dysfunction in the brain.80 However, exactly what the relationship between BT and energy dysfunction is, is not clear. The clinical utility of BT monitoring, and in particular the relationship of BT with cerebral metabolism requires more study.

Serum Inflammatory Markers Systemic indices of inflammation revolve around markers of acute phase reactants such as serum white blood cell (WBC) count and C reactive protein (CRP). Elevation in WBCs can occur in the setting of infection, inflammation, and stress or tissue necrosis. The limitation of these parameters is their nonspecific nature in CNS injury. This can limit an interpretation about CNS inflammation because elevation of these parameters may reflect other organ injury or secondary infection. Despite these limitations, several converging lines of evidence suggest that monitoring acute phase reactants may help develop models to predict secondary injury following brain injury.81 SAH is a disease in which inflammation monitoring may be the most advantageous and in particular to evaluate vasospasm.2,82-84 For example, leukocytosis has been found to be an independent risk factor for delayed cerebral ischemia (DCI) following aneurysmal SAH, with each increase of 1000 in the serum WBC associated with a 9% increase in the likelihood of developing DCI.73,85 Furthermore, a peak serum WBC greater than 15,000 is associated with a 3.3-fold greater incidence of DCI,73 whereas a CSF neutrophil content of greater than 62% on the third day after SAH is an independent factor associated with later vasospasm.86 The relationship between CRP, vasospasm and the development of DCI is still to be fully elucidated.85,87 For example, Rothoerl et al.87 observed that CRP values were higher in patients who developed DCI 5 to 8 days after aneurysm

rupture. This likely represents the response to ischemia. There was a trend observed for higher CRP values on the preceding days but these did not achieve significance. Serum CRP also was greater in poor-grade patients, which makes it difficult to conclude a “causal” relationship between a heightened acute phase response and vasospasm, or that CRP simply reflects the severity of the initial brain injury. In ischemic stroke, CRP and leukocytosis also are independent factors associated with outcome including cognitive outcome among survivors.88-90 In addition, several lines of evidence demonstrate a relationship between progression of infarction and worse neurologic outcome and elevated serum cytokines IL-1, IL-6, and TNFα.89,91-95 What is unclear is whether there is a causal relationship.

Cerebrospinal Fluid Inflammatory Markers Cytokines and downstream activators of the inflammatory response can be measured in the CSF. This is better than brain biopsy but there are limitations to CSF sampling including: (1) sampling error when relative concentrations of proteins and molecules must diffuse into the CSF from a heterogeneously injured brain (i.e., the measured values likely reflect a weighted average from surrounding tissue and its proximity to the subarachnoid space); (2) CSF levels of individual cytokines may be related to their diffusion properties in fluids and distance from the source; (3) it is restricted to intermittent (e.g., daily) sampling; and (4) different half-lives of these inflammatory markers both in the CSF and collecting vials. In addition, it should be remembered that most cytokines act over short distances to effect local cells. It may therefore be desirable in some patients to obtain tissue and fluid closest to the injury, to allow for more specific sampling of brain inflammation. Several clinical studies suggest that CSF and blood are functionally separate compartments when cytokine concentrations are measured. For example, Shiozaki et  al.96 compared CSF and serum concentrations of several cytokines from patients suffering from multiorgan trauma and TBI to those with isolated TBI. The concentrations of the proinflammatory cytokines TNFα and IL-1 were greater in CSF than serum in those with isolated brain injury. In patients with multiorgan trauma, serum levels were greater than in CSF, whereas CSF concentrations of both proinflammatory and anti-inflammatory cytokines were similar to those with isolated CNS injury. There was an association between Injury Severity Score, an index of systemic injury burden, and tumor necrosis factor-α receptor 1 (TNFr1). Patients with elevated ICP had higher concentrations of CSF IL-1, IL-10, IL-Ira, and TNFr1 than those with normal ICP. These results suggest that CSF cytokine monitoring will more accurately reflect CNS pathology than serum cytokines. Hydrocephalus that requires external ventricular drainage is common following SAH; hence CSF samples often are available. SAH has been found to cause an increase in cytokines IL-1, IL-6, transforming growth factor-β (TGFβ) and TNFα released from leukocytes in CSF21,97-99 and so monitoring the inflammatory response and in particular IL-6 maybe a useful tool to help guide care of SAH patients.84 However, in SAH patients who develop systemic inflammatory response

syndrome (SIRS) ventricular CSF cytokine levels do not appear to correlate with serum levels of IL-1 and TNFα.97 In addition, although SIRS is associated with poor outcome, it may not always be associated with vasospasm.100,101 In general SIRS is more common in patients in poor clinical grade, and some but not all studies suggest it is associated with how an aneurysm is occluded.100,101 IL-1 and IL-6 levels consistently have been observed to be greater in poor-grade than good-grade patients although an initial inflammatory response is observed in patients of all clinical grades.102 There also appears to be a relationship with DCI and inflammatory markers particularly in the CSF.102,103 For example, Mathiesen et al.21 analyzed CSF daily following SAH and found IL-1 to increase during delayed ischemic neurologic deficit (DIND). Elevated IL-1 and TNFα levels also correlated with poor outcome.21 Kwon and Jeon found that admission IL-6 concentration correlated with delayed ischemic deficits.98 SAH also appears to induce the production of nitric oxide metabolites, as inferred by the association with increased levels of nitric oxide breakdown products, nitrite and nitrate (NOx), in CSF.104 However, nitric oxide metabolites in CSF appear to be different from serum concentrations.104,105 In patients who develop vasospasm and DCI, CSF concentrations of NOx are greater between 2 and 8 days after aneurysm rupture.106 In TBI, CSF cytokine concentrations are elevated.65,107-109 The highest concentrations usually are measured during the first 24 hours, after which there is a decline.110 However, there is a difference between CSF and serum concentrations of various cytokines.96,111,112 The difference between plasma and CSF levels of cytokines does not appear to be associated with BBB breakdown. This suggests that the cytokines are released by microglia, astrocytes, and neurons112 rather than simply reflecting “spill-over” from the blood. There are conflicting data on what cytokine levels in the CSF mean. Some studies show that IL-1 concentration in CSF is associated with unfavorable outcome96,108 following TBI. Other studies, however, suggest that peak CSF IL-6 levels are associated with improved outcome,113 IL-6 deficiency is associated with poor outcome,114 and up-regulation of IL-10 production may play a neuro­ protective role by attenuating TNFα release.111,115

Methods to Sample Cytokines and Monitor Neuroinflammation in Clinical Practice Immune system cells and brain cells produce cytokines that act as intercellular signaling molecules. Depending on their concentration, cytokines can have toxic or trophic effects and can be pro- or anti-inflammatory.116 In addition several cytokines can have synergistic effects, and therefore a full understanding of the interactions between both deleterious and protective cytokines rather than just the absolute concentration of a particular cytokine may be needed to derive meaningful interpretation of clinical data. Several other factors make clinical interpretation of human cytokine data complex. First, each cytokine is produced during a defined time period and so results may depend on when the samples are obtained. Second, cytokines are produced in different amounts within different compartments—blood, brain, extracellular fluid (ECF), and CSF—and hence what is sampled will influence

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the findings. It appears that IL-1b and vascular endothelial growth factor (VEGF) levels are greater in brain ECF than in CSF, whereas IL-6, TNF, IL-8 and IL-1ra are greater in CSF than in microdialysate.3 Third, there are complex interactions of the immune system with the BBB and blood-CSF barriers that influence the findings. Finally, it is unclear whether it is the peak cytokine level, the area under the curve, or the specific cytokine production relative to other mediators that is most important to the biologic effect. In clinical practice there are four basic approaches to examine the role of inflammatory mediators: (1) blood sampling (both arterial and jugular venous), (2) CSF sampling, (3) microdialysis, and (4) direct tissue sampling from ex vivo or postmortem tissue. In addition, PET studies may be used to examine microglial activation. Blood sampling is the easiest technique because it is readily available, can be easily repeated, requires no specialized equipment, and cytokines can be screened for with multiplex assay techniques. However, cytokines in arterial blood samples may indicate both intracranial and extracranial pathology. Paired arterial and jugular venous sampling can be used to help examine the relative contributions of the brain or the systemic inflammatory response. However, detection of a gradient is not always feasible because the absolute concentrations of some cytokines are close to the limit of sensitivity of the assay techniques. External ventricular drainage when used provides a useful method to evaluate CSF inflammation because CSF production of cytokines is thought to represent brain production. However, the concentration of a cytokine may depend on how the CSF is drained (i.e., intermittently or continuously)117 and CSF production. In addition, it is unclear whether CSF drainage is a method to eliminate various cytokines (i.e., is “therapeutic”). This then raises the question of the biologic relevance of any immune mediator detected in the CSF. Microdialysis continuously samples the brain interstitial space (see Chapter 36). This may be the most biologically relevant compartment because inflammatory mediators are secreted here and act on their surface membrane target receptors. It can be difficult to assay cytokines and inflammatory mediators using microdialysis because these proteins have a greater molecular weight than the metabolic intermediaries (glucose, lactate, pyruvate) commonly examined with this technique. Consequently cytokines diffuse across the microdialysis membrane at a slower rate, and a smaller proportion crosses into the catheter (i.e., the relative recovery is low). Several techniques can be used to address this, including use of catheters with larger molecular weight cutoff membranes (e.g., 100 kDa), addition of colloids (such as dextrans or albumin) to the perfusate, and use of sensitive multiplex techniques to assay the cytokines (e.g., the Luminex xMAP platform). In the laboratory setting cytokine binders (e.g., heparin) have been added to the perfusion fluid. This has not been used clinically because it is conceivable that heparin is lost from the perfusate into the ECF.118

Future Investigation Further Understanding of the Dual Effects of Cytokines Following Acute Brain Injury Acute brain injury is followed by a cytokine-triggered influx of lymphocytes and myeloid cells into the injured region.

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These infiltrating cells are further stimulated in an autocrine and paracrine fashion to produce an inflammatory environment, which may contribute to further tissue injury. However, some signals are adaptive and confer neuroprotection as well as promote tissue repair.119 For example, IL-6 is both a neurotropic and inflammatory factor.120 The complex interplay of the various factors and downstream effectors involved in an inflammatory response in the setting of acute brain injury is only beginning to be elucidated. The major challenge when monitoring cytokines as markers of inflammation is that many cytokines can exert different effects that depend on the local environment. This also presents an obstacle when interpreting animal and clinical studies that relate inflammatory mediators and extent of brain injury or outcome. It is likely a balance between the various implicated cytokines and their intracellular signaling cascades that determines whether the inflammatory response is adaptive or maladaptive. Thus, monitoring cytokines in isolation may not be useful unless its role is incorporated into the greater context of the inflammatory environment and individualized to each particular patient.

Further Investigation on the Interplay Between Systemic and CNS Inflammatory Pathways The relationship between cerebral inflammatory response and the systemic, extracerebral response needs to be better understood. They are distinct but not independent pathways, and it is likely that systemic factors influence those occurring in the CNS and that the neuroinflammatory pathway modulates the systemic cascade.

Continuous, Bedside Monitoring of Neuroinflammation It is feasible to measure intrathecal interleukins at bedside using point-of-care testing with an immunoassay chip-test. These bedside results are similar to those obtained with laboratory testing.81 Microdialysis techniques to sample inflammatory mediators in the tissue most at risk for secondary injury, may further advance the ability to monitor neuroinflammation.110 For example, the balance between members of the IL-1 cytokine family, in particular between IL-1b and its endogenous inhibitor IL-1ra, may be more important than absolute levels of IL-1b. In TBI patients, the microdialysate IL-1ra:IL-1b ratio is greater in patients with favorable rather than unfavorable outcomes.121 The critical factor is whether following trends in neuroinflammation heralds the onset of secondary injury in a timely and predictable manner to alter management, or whether it is a late sign at a time when intervention is not likely to affect the outcome.

Conclusion Inflammatory processes, initiated by the resident microglia within the CNS, occur after a variety of acute neurological insults. These processes may have a dual role, that is, inflammatory responses can play a role in recovery whereas accumulating evidence indicates that inflammation can aggravate secondary injury in conditions such as TBI, stroke, or SAH.

Consistent with this, animal studies suggest that the inhibition of proinflammatory mediators can provide neuroprotection. Monitoring of inflammatory markers in the CNS that may be measured in the serum, CSF, or brain interstitial fluid using microdialysis therefore will likely play an increasing role in the NCCU.

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39. Man S, Ubogu EE, Ransohoff RM. Inflammatory cell migration into the central nervous system: a few new twists on an old tale. Brain Pathol 2007; 17:243–50. 40. Pachter JS, de Vries HE, Fabry Z. The blood-brain barrier and its role in immune privilege in the central nervous system. J Neuropathol Exp Neurol 2003;62:593–604. 41. Ransohoff RM, Kivisakk P, Kidd G. Three or more routes for leukocyte migration into the central nervous system. Nat Rev Immunol 2003;3:569–81. 42. Simard JM, Geng Z, Woo SK, et al. Glibenclamide reduces inflammation, vasogenic edema, and caspase-3 activation after subarachnoid hemorrhage. J Cereb Blood Flow Metab 2009;29:317–30. 43. Ramlackhansingh AF, Brooks DJ, Greenwood RJ, et al. Inflammation after trauma: microglial activation and traumatic brain injury. Ann Neurol 2011;70(3):374–83. Epub 2011 Jun 27. 44. De Santi L, Polimeni G, Cuzzocrea S, et al. Neuroinflammation and neuroprotection: an update on (future) neurotrophin-related strategies in multiple sclerosis treatment. Curr Med Chem 2011;18(12):1775–84. 45. Amor S, Puentes F, Baker D, van der Valk P. Inflammation in neurodegenerative diseases. Immunology 2010;129(2):154–69. 46. Laskowitz DT, Vitek MP. Apolipoprotein E and neurological disease: therapeutic potential and pharmacogenomic interactions. Pharmacogenomics 2007;8:959–69. 47. Iannotti CA, Clark M, Horn KP, et al. A combination immunomodulatory treatment promotes neuroprotection and locomotor recovery after contusion SCI. Exp Neurol 2011;230(1):3–15. Epub 2010 Mar 23. 48. Thompson HJ. Fever: a concept analysis. J Adv Nurs 2005;51:484–92. 49. Busto R, Dietrich WD, Globus MY, et al. Small differences in intraischemic brain temperature critically determine the extent of ischemic neuronal injury. J Cereb Blood Flow Metab 1987;7:729–38. 50. Diringer MN, Reaven NL, Funk SE, et al. Elevated body temperature independently contributes to increased length of stay in neurologic intensive care unit patients. Crit Care Med 2004;32:1489–95. A complete list of references for this chapter can be found online at www.expertconsult.com.

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References 1. Mashaly HA, Provencio JJ. Inflammation as a link between brain injury and heart damage: the model of subarachnoid hemorrhage. Cleve Clin J Med 2008;75(Suppl 2):S26–30. 2. Pradilla G, Chaichana KL, Hoang S, et al. Inflammation and cerebral vasospasm after subarachnoid hemorrhage. Neurosurg Clin N Am 2010; 21(2):365–79. 3. Helmy A, De Simoni MG, Guilfoyle MR, et al. Cytokines and innate inflammation in the pathogenesis of human traumatic brain injury. Prog Neurobiol 2011;95(3):352–72. Epub 2011 Sep 16. 4. Brough D, Tyrrell PJ, Allan SM. Regulation of interleukin-1 in acute brain injury. Trends Pharmacol Sci 2011;32(10):617–22. Epub 2011 Jul 23. 5. Ravizza T, Balosso S, Vezzani A. Inflammation and prevention of epileptogenesis. Neurosci Lett 2011;497(3):223–30. Epub 2011 Feb 26. 6. Denes A, Thornton P, Rothwell NJ, et al. Inflammation and brain injury: acute cerebral ischaemia, peripheral and central inflammation. Brain Behav Immun 2010;24:708–23. 7. Ott L, McClain CJ, Gillespie M, et al. Cytokines and metabolic dysfunction after severe head injury. J Neurotrauma 1994;11:447–72. 8. Ross SA, Halliday MI, Campbell GC, et al. The presence of tumour necrosis factor in CSF and plasma after severe head injury. Br J Neurosurg 1994;8: 419–25. 9. Shohami E, Novikov M, Bass R, et al. Closed head injury triggers early production of TNF alpha and IL-6 by brain tissue. J Cereb Blood Flow Metab 1994;14:615–19. 10. Chou SH, Smith EE, Badjatia N, et al. A randomized, double-blind, placebo-controlled pilot study of simvastatin in aneurysmal subarachnoid hemorrhage. Stroke 2008;39:2891–3. 11. Lynch JR, Wang H, McGirt MJ, et al. Simvastatin reduces vasospasm after aneurysmal subarachnoid hemorrhage: results of a pilot randomized clinical trial. Stroke 2005;36:2024–6. 12. McGirt MJ, Blessing R, Alexander MJ, et al. Risk of cerebral vasospasm after subarachnoid hemorrhage reduced by statin therapy: a multivariate analysis of an institutional experience. J Neurosurg 2006;105:671–4. 13. Sillberg VA, Wells GA, Perry JJ. Do statins improve outcomes and reduce the incidence of vasospasm after aneurysmal subarachnoid hemorrhage: a meta-analysis. Stroke 2008;39:2622–6. 14. Tseng MY, Czosnyka M, Richards H, et al. Effects of acute treatment with pravastatin on cerebral vasospasm, autoregulation, and delayed ischemic deficits after aneurysmal subarachnoid hemorrhage: a phase II randomized placebo-controlled trial. Stroke 2005;36:1627–32. 15. Chen SF, Hung TH, Chen CC, et al. Lovastatin improves histological and functional outcomes and reduces inflammation after experimental traumatic brain injury. Life Sci 2007;81:288–98. 16. Lu D, Goussev A, Chen J, et al. Atorvastatin reduces neurological deficit and increases synaptogenesis, angiogenesis, and neuronal survival in rats subjected to traumatic brain injury. J Neurotrauma 2004;21:21–32. 17. Lu D, Qu C, Goussev A, et al. Statins increase neurogenesis in the dentate gyrus, reduce delayed neuronal death in the hippocampal CA3 region, and improve spatial learning in rats after traumatic brain injury. J Neurotrauma 2007;24:1132–46. 18. Turkoglu OF, Eroglu H, Okutan O, et al. Atorvastatin efficiency after traumatic brain injury in rats. Surg Neurol 2009;72:146–52. 19. Feuerstein G, Wang X, Barone FC. Cytokines in brain ischemia—the role of TNF alpha. Cell Mol Neurobiol 1998;18:695–701. 20. Lucas SM, Rothwell NJ, Gibson RM. The role of inflammation in CNS injury and disease. Br J Pharmacol 2006;147 Suppl 1:S232–40. 21. Mathiesen T, Edner G, Ulfarsson E, et al. Cerebrospinal fluid interleukin-1 receptor antagonist and tumor necrosis factor-alpha following subarachnoid hemorrhage. J Neurosurg 1997;87:215–20. 22. Rodriguez-Yanez M, Castillo J. Role of inflammatory markers in brain ischemia. Curr Opin Neurol 2008;21:353–7. 23. Stefini R, Catenacci E, Piva S, et al. Chemokine detection in the cerebral tissue of patients with posttraumatic brain contusions. J Neurosurg 2008;108:958–62. 24. Waje-Andreassen U, Krakenes J, Ulvestad E, et al. An early marker for outcome in acute ischemic stroke. Acta Neurol Scand 2005;111:360–5. 25. Welsh P, Lowe GD, Chalmers J, et al. Associations of proinflammatory cytokines with the risk of recurrent stroke. Stroke 2008;39:2226–30. 26. Borovikova LV, Ivanova S, Zhang M, et al. Vagus nerve stimulation attenuates the systemic inflammatory response to endotoxin. Nature 2000; 405:458–62. 27. Rothwell NJ, Luheshi GN. Interleukin 1 in the brain: biology, pathology and therapeutic target. Trends Neurosci 2000;23:618–25.

28. Clausen F, Hanell A, Israelsson C, et al. Neutralization of interleukin-1beta reduces cerebral edema and tissue loss and improves late cognitive outcome following traumatic brain injury in mice. Eur J Neurosci 2011;34:110–23. 29. Chaichana KL, Pradilla G, Huang J, et al. Role of inflammation (leukocyteendothelial cell interactions) in vasospasm after subarachnoid hemorrhage. World Neurosurg 2010;73(1):22–41. Epub 2009 Aug 6. 30. Kataoka H, Aoki T. Molecular basis for the development of intracranial aneurysm. Expert Rev Neurother 2010;10(2):173–17. 31. Tulamo R, Frösen J, Hernesniemi J, et al. Inflammatory changes in the aneurysm wall: a review. J Neurointerv Surg 2010;2(2):120–30. Epub 2010 Mar 12. 32. Aoki T, Nishimura M. Targeting chronic inflammation in cerebral aneurysms: focusing on NF-kappaB as a putative target of medical therapy. Expert Opin Ther Targets 2010;14(3):265–73. 33. Norton WT, Aquino DA, Hozumi I, et al. Quantitative aspects of reactive gliosis: a review. Neurochem Res 1992;17:877–85. 34. O’Callaghan JP. Quantitative features of reactive gliosis following toxicant-induced damage of the CNS. Ann N Y Acad Sci 1993;679:195–210. 35. Perry VH, Gordon S. Macrophages and the nervous system. Int Rev Cytol 1991;125:203–44. 36. Town T, Nikolic V, Tan J. The microglial “activation” continuum: from innate to adaptive responses. J Neuroinflammation 2005;2:24. 37. Loane DJ, Byrnes KR. Role of microglia in neurotrauma. Neurotherapeutics 2010;7(4):366–77. 38. Engelhardt B, Ransohoff RM. The ins and outs of T-lymphocyte trafficking to the CNS: anatomical sites and molecular mechanisms. Trends Immunol 2005;26:485–95. 39. Man S, Ubogu EE, Ransohoff RM. Inflammatory cell migration into the central nervous system: a few new twists on an old tale. Brain Pathol 2007;17:243–50. 40. Pachter JS, de Vries HE, Fabry Z. The blood-brain barrier and its role in immune privilege in the central nervous system. J Neuropathol Exp Neurol 2003;62:593–604. 41. Ransohoff RM, Kivisakk P, Kidd G. Three or more routes for leukocyte migration into the central nervous system. Nat Rev Immunol 2003;3: 569–81. 42. Simard JM, Geng Z, Woo SK, et al. Glibenclamide reduces inflammation, vasogenic edema, and caspase-3 activation after subarachnoid hemorrhage. J Cereb Blood Flow Metab 2009;29:317–30. 43. Ramlackhansingh AF, Brooks DJ, Greenwood RJ, et al. Inflammation after trauma: microglial activation and traumatic brain injury. Ann Neurol 2011;70(3):374–83. Epub 2011 Jun 27. 44. De Santi L, Polimeni G, Cuzzocrea S, et al. Neuroinflammation and neuroprotection: an update on (future) neurotrophin-related strategies in multiple sclerosis treatment. Curr Med Chem 2011;18(12):1775–84. 45. Amor S, Puentes F, Baker D, van der Valk P. Inflammation in neurodegenerative diseases. Immunology 2010;129(2):154–69. 46. Laskowitz DT, Vitek MP. Apolipoprotein e and neurological disease: therapeutic potential and pharmacogenomic interactions. Pharmacogenomics 2007;8:959–69. 47. Iannotti CA, Clark M, Horn KP, et al. A combination immunomodulatory treatment promotes neuroprotection and locomotor recovery after contusion SCI. Exp Neurol 2011;230(1):3–15. Epub 2010 Mar 23. 48. Thompson HJ. Fever: a concept analysis. J Adv Nurs 2005;51:484–92. 49. Busto R, Dietrich WD, Globus MY, et al. Small differences in intraischemic brain temperature critically determine the extent of ischemic neuronal injury. J Cereb Blood Flow Metab 1987;7:729–38. 50. Diringer MN, Reaven NL, Funk SE, et al. Elevated body temperature independently contributes to increased length of stay in neurologic intensive care unit patients. Crit Care Med 2004;32:1489–95. 51. Hajat C, Hajat S, Sharma P. Effects of poststroke pyrexia on stroke outcome: a meta-analysis of studies in patients. Stroke 2000;31:410–14. 52. Naidech AM, Bendok BR, Bernstein RA, et al. Fever burden and functional recovery after subarachnoid hemorrhage. Neurosurgery 2008;63:212–17; discussion 217–18. 53. Oliveira-Filho J, Ezzeddine MA, Segal AZ, et al. Fever in subarachnoid hemorrhage: relationship to vasospasm and outcome. Neurology 2001;56: 1299–304. 54. Weir B, Disney L, Grace M, et al. Daily trends in white blood cell count and temperature after subarachnoid hemorrhage from aneurysm. Neurosurgery 1989;25:161–5. 55. Chen H, Chopp M, Welch KM. Effect of mild hyperthermia on the ischemic infarct volume after middle cerebral artery occlusion in the rat. Neurology 1991;41:1133–5. 56. Dietrich WD. The importance of brain temperature in cerebral injury. J Neurotrauma 1992;9 Suppl 2:S475–85.

153.e2 Section II—Clinical and Laboratory Assessment 57. Morimoto T, Ginsberg MD, Dietrich WD, et al. Hyperthermia enhances spectrin breakdown in transient focal cerebral ischemia. Brain Res 1997; 746:43–51. 58. Whalen MJ, Carlos TM, Clark RS, et al. The relationship between brain temperature and neutrophil accumulation after traumatic brain injury in rats. Acta Neurochir Suppl 1997;70:260–1. 59. Matthews DS, Bullock RE, Matthews JN, et al. Temperature response to severe head injury and the effect on body energy expenditure and cerebral oxygen consumption. Arch Dis Child 1995;72:507–15. 60. Stocchetti N, Rossi S, Zanier ER, et al. Pyrexia in head-injured patients admitted to intensive care. Intensive Care Med 2002;28:1555–62. 61. Stubbe HD, Greiner C, Van Aken H, et al. Cerebral vascular and metabolic response to sustained systemic inflammation in ovine traumatic brain injury. J Cereb Blood Flow Metab 2004;24:1400–8. 62. Thompson HJ, Tkacs NC, Saatman KE, et al. Hyperthermia following traumatic brain injury: a critical evaluation. Neurobiol Dis 2003;12:163–73. 63. Allan SM, Rothwell NJ. Cytokines and acute neurodegeneration. Nat Rev Neurosci 2001;2:734–44. 64. Huang WT, Tsai SM, Lin MT. Involvement of brain glutamate release in pyrogenic fever. Neuropharmacology 2001;41:811–18. 65. Morganti-Kossmann MC, Rancan M, Otto VI, et al. Role of cerebral inflammation after traumatic brain injury: a revisited concept. Shock 2001;16:165–77. 66. Adachi H, Fujisawa H, Maekawa T, et al. Changes in the extracellular glutamate concentrations in the rat cortex following localized by hyperthermia. Int J Hyperthermia 1995;11:587–99. 67. Chatzipanteli K, Alonso OF, Kraydieh S, et al. Importance of posttraumatic hypothermia and hyperthermia on the inflammatory response after fluid percussion brain injury: biochemical and immunocytochemical studies. J Cereb Blood Flow Metab 2000;20:531–42. 68. Rovlias A, Kotsou S. The influence of hyperglycemia on neurological outcome in patients with severe head injury. Neurosurgery 2000;46:335–42; discussion 342–3. 69. Saper CB, Breder CD. The neurologic basis of fever. N Engl J Med 1994;330:1880–6. 70. Young B. Nutritional and metabolic management of the head-injured patient. Neurotrauma 1996:345–63. 71. McGirt MJ, Mavropoulos JC, McGirt LY, et al. Leukocytosis as an independent risk factor for cerebral vasospasm following aneurysmal subarachnoid hemorrhage. J Neurosurg 2003;98:1222–6. 72. Shahlaie K, Keachie K, Hutchins IM, et al. Risk factors for posttraumatic vasospasm. J Neurosurg 2011;115(3):602–11. Epub 2011 Jun 10. 73. Hanafy KA, Morgan Stuart R, Fernandez L, et al. Cerebral inflammatory response and predictors of admission clinical grade after aneurysmal subarachnoid hemorrhage. J Clin Neurosci 2010;17(1):22–5. Epub 2009 Dec 8. 74. Gupta AK, Al-Rawi PG, Hutchinson PJ, et al. Effect of hypothermia on brain tissue oxygenation in patients with severe head injury. Br J Anaesth 2002;88:188–92. 75. Rossi S, Zanier ER, Mauri I, et al. Brain temperature, body core temperature, and intracranial pressure in acute cerebral damage. J Neurol Neurosurg Psychiatry 2001;71(4):448–54. 76. Rumana CS, Gopinath SP, Uzura M, et al. Brain temperature exceeds systemic temperature in head-injured patients. Crit Care Med 1998;26: 562–7. 77. Soukup J, Zauner A, Doppenberg EM, et al. The importance of brain temperature in patients after severe head injury: relationship to intracranial pressure, cerebral perfusion pressure, cerebral blood flow, and outcome. J Neurotrauma 2002;19:559–71. 78. Spiotta AM, Stiefel MF, Heuer GG, et al. Brain hyperthermia after traumatic brain injury does not reduce brain oxygen. Neurosurgery 2008;62:864–72; discussion 872. 79. Stocchetti N, Protti A, Lattuada M, et al. Impact of pyrexia on neurochemistry and cerebral oxygenation after acute brain injury. J Neurol Neurosurg Psychiatry 2005;76(8):1135–9. 80. Oddo M, Frangos S, Milby A, et al. Induced normothermia attenuates cerebral metabolic distress in patients with aneurysmal subarachnoid hemorrhage and refractory fever. Stroke 2009;40(5):1913–6. 81. Dengler J, Schefold JC, Graetz D, et al. Point-of-care testing for interleukin-6 in cerebro spinal fluid (CSF) after subarachnoid haemorrhage. Med Sci Monit 2008;14(12):BR265–8. 82. Maiuri F, Gallicchio B, Donati P, et al. The blood leukocyte count and its prognostic significance in subarachnoid hemorrhage. J Neurosurg Sci 1987;31:45–8. 83. Rovlias A, Kotsou S. The blood leukocyte count and its prognostic significance in severe head injury. Surg Neurol 2001;55:190–6.

84. Muroi C, Mink S, Seule M, et al. Monitoring of the inflammatory response after aneurysmal subarachnoid haemorrhage in the clinical setting: review of literature and report of preliminary clinical experience. Acta Neurochir Suppl 2011;110(Pt 1):191–6. 85. Kasius KM, Frijns CJ, Algra A, et al. Association of platelet and leukocyte counts with delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage. Cerebrovasc Dis 2010;29(6):576–83. Epub 2010 Apr 8. 86. Provencio JJ, Fu X, Siu A, et al. CSF neutrophils are implicated in the development of vasospasm in subarachnoid hemorrhage. Neurocrit Care 2010;12(2):244–51. 87. Rothoerl RD, Axmann C, Pina AL, et al. Possible role of the C-reactive protein and white blood cell count in the pathogenesis of cerebral vasospasm following aneurysmal subarachnoid hemorrhage. J Neurosurg Anesthesiol 2006;18:68–72. 88. Muir KW, Weir CJ, Alwan W, et al. C-reactive protein and outcome after ischemic stroke. Stroke 1999;30:981–5. 89. Smith CJ, Emsley HC, Gavin CM, et al. Peak plasma interleukin-6 and other peripheral markers of inflammation in the first week of ischaemic stroke correlate with brain infarct volume, stroke severity and long-term outcome. BMC Neurol 2004;4:2. 90. Rothenburg LS, Herrmann N, Swardfager W, et al. The relationship between inflammatory markers and post stroke cognitive impairment. J Geriatr Psychiatry Neurol 2010;23(3):199–205. Epub 2010 Jul 2. 91. Blanco M, Castellanos M, Rodriguez-Yanez M, et al. High blood pressure and inflammation are associated with poor prognosis in lacunar infarctions. Cerebrovasc Dis 2006;22:123–9. 92. Castellanos M, Castillo J, Garcia MM, et al. Inflammation-mediated damage in progressing lacunar infarctions: a potential therapeutic target. Stroke 2002;33:982–7. 93. Leira R, Rodriguez-Yanez M, Castellanos M, et al. Hyperthermia is a surrogate marker of inflammation-mediated cause of brain damage in acute ischaemic stroke. J Intern Med 2006;260:343–9. 94. Oto J, Suzue A, Inui D, et al. Plasma proinflammatory and antiinflammatory cytokine and catecholamine concentrations as predictors of neurological outcome in acute stroke patients. J Anesth 2008;22: 207–12. 95. Vila N, Castillo J, Davalos A, et al. Proinflammatory cytokines and early neurological worsening in ischemic stroke. Stroke 2000;31:2325–9. 96. Shiozaki T, Hayakata T, Tasaki O, et al. Cerebrospinal fluid concentrations of anti-inflammatory mediators in early-phase severe traumatic brain injury. Shock 2005;23:406–10. 97. Gruber A, Rossler K, Graninger W, et al. Ventricular cerebrospinal fluid and serum concentrations of STNFR-I, IL-1RA, and IL-6 after aneurysmal subarachnoid hemorrhage. J Neurosurg Anesthesiol 2000;12:297–306. 98. Kwon KY, Jeon BC. Cytokine levels in cerebrospinal fluid and delayed ischemic deficits in patients with aneurysmal subarachnoid hemorrhage. J Korean Med Sci 2001;16:774–80. 99. Takizawa T, Tada T, Kitazawa K, et al. Inflammatory cytokine cascade released by leukocytes in cerebrospinal fluid after subarachnoid hemorrhage. Neurol Res 2001;23:724–30. 100. Tam AK, Ilodigwe D, Mocco J, et al. Impact of systemic inflammatory response syndrome on vasospasm, cerebral infarction, and outcome after subarachnoid hemorrhage: exploratory analysis of CONSCIOUS-1 database. Neurocrit Care 2010;13(2):182–9. 101. Dhar R, Diringer MN. The burden of the systemic inflammatory response predicts vasospasm and outcome after subarachnoid hemorrhage. Neurocrit Care 2008;8(3):404–12. 102. Sarrafzadeh A, Schlenk F, Gericke C, et al. Relevance of cerebral interleukin-6 after aneurysmal subarachnoid hemorrhage. Neurocrit Care 2010;13(3):339–46. 103. Zanier ER, Brandi G, Peri G, et al. Cerebrospinal fluid pentraxin 3 early after subarachnoid hemorrhage is associated with vasospasm. Intensive Care Med 2011;37(2):302–9. Epub 2010 Nov 12. 104. Suzuki Y, Osuka K, Noda A, et al. Nitric oxide metabolites in the cisternal cerebral spinal fluid of patients with subarachnoid hemorrhage. Neurosurgery 1997;41(4):807–11. 105. Rejdak K, Petzold A, Sharpe MA, et al. Serum and urine nitrate and nitrite are not reliable indicators of intrathecal nitric oxide production in acute brain injury. J Neurol Sci 2003;208:1–7. 106. Woszczyk A, Deinsberger W, Boker DK. Nitric oxide metabolites in cisternal CSF correlate with cerebral vasospasm in patients with a subarachnoid haemorrhage. Acta Neurochir (Wien) 2003;145(4):257–63. 107. Bell MJ, Kochanek PM, Doughty LA, et al. Interleukin-6 and interleukin-10 in cerebrospinal fluid after severe traumatic brain injury in children. J Neurotrauma 1997;14:451–7.

108. Hayakata T, Shiozaki T, Tasaki O, et al. Changes in CSF S-100B and cytokine concentrations in early-phase severe traumatic brain injury. Shock 2004;22:102–7. 109. Kossmann T, Stahel PF, Lenzlinger PM, et al. Interleukin-8 released into the cerebrospinal fluid after brain injury is associated with blood-brain barrier dysfunction and nerve growth factor production. J Cereb Blood Flow Metab 1997;17:280–9. 110. Perez-Barcena J, Ibáñez J, Brell M, et al. Lack of correlation among intracerebral cytokines, intracranial pressure, and brain tissue oxygenation in patients with traumatic brain injury and diffuse lesions. Crit Care Med 2011;39(3):533–40. 111. Csuka E, Morganti-Kossmann MC, Lenzlinger PM, et al. IL-10 levels in cerebrospinal fluid and serum of patients with severe traumatic brain injury: relationship to IL-6, TNF-alpha, TGF-beta1 and blood-brain barrier function. J Neuroimmunol 1999;101:211–21. 112. Maier B, Schwerdtfeger K, Mautes A, et al. Differential release of interleukines 6, 8, and 10 in cerebrospinal fluid and plasma after traumatic brain injury. Shock 2001;15:421–6. 113. Singhal A, Baker AJ, Hare GM, et al. Association between cerebrospinal fluid interleukin-6 concentrations and outcome after severe human traumatic brain injury. J Neurotrauma 2002;19:929–37.

Section II—Clinical and Laboratory Assessment 153.e3 114. Ley EJ, Clond MA, Singer MB, et al. IL6 deficiency affects function after traumatic brain injury. J Surg Res 2011;170(2):253–6. Epub 2011 Mar 29. 115. de Waal Malefyt R, Abrams J, Bennett B, et al. Interleukin 10(IL-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of il-10 produced by monocytes. J Exp Med 1991;174:1209–20. 116. McCombe PA, Read SJ. Immune and inflammatory responses to stroke: good or bad? Int J Stroke 2008;3:254–65. 117. Suzuki S, Tanaka K, Suzuki N. Ambivalent aspects of interleukin-6 in cerebral ischemia: Inflammatory versus neurotrophic aspects. J Cereb Blood Flow Metab 2009;29:464–79. 118. Viviani B, Bartesaghi S, Corsini E, et al. Cytokines role in neurodegenerative events. Toxicol Lett 2004;149:85–9. 119. Shore PM, Thomas NJ, Clark RS, et al. Continuous versus intermittent cerebrospinal fluid drainage after severe traumatic brain injury in children: effect on biochemical markers. J Neurotrauma 2004;21:1113–22. 120. Duo J, Stenken JA. In vitro and in vivo affinity microdialysis sampling of cytokines using heparin-immobilized microspheres. Anal Bioanal Chem 2011;399:783–93. 121. Hutchinson PJ, O’Connell MT, Rothwell NJ, et al. Inflammation in human brain injury: intracerebral concentrations of IL-1alpha, IL-1beta, and their endogenous inhibitor IL1-ra. J of Neurotrauma 2007;24:1545–57.

II

Chapter

17

 

Infection Barnett R. Nathan and John J. Stern

Introduction Infections in the intensive care setting are common, both as the reason for the intensive care unit (ICU) admission and as a nosocomial complication of critical illness. Nosocomial infections, now referred to as hospital acquired infections (HAIs), are thought to complicate between one quarter and one half of all ICU admissions. In the Extended Prevalence of Infection in Intensive Care (EPIC II) study, a 1-day, prospective, point prevalence study, 51% of 13,796 adult (older than 18 years) patients in 1265 participating ICUs from 75 countries were considered infected; 9084 (71%) were receiving antibiotics.1 The ICU mortality rate of the infected patients was twofold greater than that of noninfected patients (25% vs. 11%). Although central nervous system (CNS) infections are far less common as admission diagnoses or as complications of critical care, these infections, including the hospital-acquired complications of neurosurgical intervention and the community-acquired infections of meningitis, encephalitis, and brain abscess are the focus of this chapter. Each of these infections is discussed separately to provide insights on what tests are needed to make the diagnosis. Infections such as catheter-associated bloodstream infections (BSIs) and ventilator-associated pneumonia (VAP) are reviewed in Chapter 6. Finally, the role of infection surveillance, prevention, and control is reviewed.

Bacterial Infections Bacterial Central Nervous System Space-Occupying Lesions Examples of space-occupying lesions of the CNS include parenchymal abscesses, epidural abscesses, and empyemas. The most common sources of brain abscesses are from hematologic spread (most common lung), direct extension from a parameningeal source (including the sinuses, middle ear, or after dental procedures, head trauma, or surgery), suppurative lung disease, or congenital heart disease (e.g., patent foramen ovale or patent ductus arteriosus, i.e., right to left shunting). Rare causes of brain abscess have been reported after tongue piercing or endovascular occlusion of aneurysms using Guglielmi detachable coils.2 Infective endocarditis occasionally presents first with a brain abscess. 154

Clinical Presentation of Bacterial Central Nervous System Space-Occupying Lesions Parenchymal brain abscess may present with many symptoms. Although the classic triad of fever, headache, and focal neurologic signs is helpful, this occurs in less than half of patients, and the presentation may be more of a mass lesion than an infection. Other manifestations, including symptoms and signs of the original infection (otitis or sinusitis), may be present and more impressive. Although the average course of brain abscesses from the time of symptom presentation to hospital admission can be as short as 5 days,3 the course may be more indolent. Subdural empyema also may present with the triad of sinusitis, fever, and neurologic deficit. However, signs of cortical irritation such as seizures (50%), raised intracranial pressure (headache, vomiting, and papilledema [50%]), or focal deficits (75%) are a frequent presentation. Spinal epidural abscess is a neurosurgical emergency, and the typical presenting features include back pain, malaise, and fever. Neurologic deficits associated with spinal epidural abscesses often are associated with venous thrombophlebitis and so may evolve rapidly or be greater than the lesion size suggests.

Epidemiology The frequency of brain abscesses in the United States ranges from 0.3 to 1.3 cases per 100,000 persons per year, with a predominance occurring in men between the ages of 30 to 40. Twenty five percent of all brain abscesses occur in children between the ages of 4 to 7, resulting from either cyanotic heart disease or extension from an otic source. The organism causing the infection depends in part on the source of the infection and the patient’s age. Common organisms in adults include anaerobic organisms, in particular Bacteroides and Peptostreptococcus in some series, whereas in others, aerobic organisms especially Staphylococcus, Streptococcus (most common), Enterobacteriaceae, and Haemophilus are more common. In infants Proteus and Citrobacter are the most frequent cause, whereas in children (3-5 years old) Haemophilus, Streptococcus pneumoniae, and Bacteroides fragilis (otogenic spread) are common. Staphylococcus, S. pneumoniae, and Haemophilus influenzae are common from sinus spread and Streptococcus or Staphylococcus aureus from cyanotic heart disease. Since © Copyright 2013 Elsevier Inc. All rights reserved.

1981 the incidence of human immunodeficiency virus (HIV)– related brain abscesses due to toxoplasmosis has become the most common cause of a protozoal space-occupying brain lesion and must be considered in any patient presenting with a ring-enhancing brain lesion. These lesions may be single or multiple and should lead to expeditious HIV serologic testing. Aspergillus is the most common fungal organism to cause a brain abscess. Subdural empyemas (SDEs)—a collection of purulence located between the arachnoid and dura—account for 15% to 20% of all space-occupying infections and result from extension of a suppurative process in a paranasal sinus or otorhinologic infection. Less commonly, subdural empyemas result from head trauma or after a neurosurgical procedure. Tewari et al., found the majority of SDEs are identified in infancy through the third decade of life (60%).4 Spinal epidural abscesses usually occur as the result of hematogenous seeding of the epidural space from a distant suppurative focus such as infective endocarditis, from an infected central line catheter, or from the injection of intravenous drugs. S. aureus, and less commonly aerobic and anaerobic streptococci, and gram-negative rods cause the vast majority of epidural infections.

Diagnosis of Central Nervous System Space-Occupying Lesions Fever with or without a peripheral white count and symptoms of new CNS deficit suggest an intracranial infection. Other signs and symptoms such as headache, vomiting, and papilledema are not specific to these diagnoses. Cranial imaging with computed tomography (CT) or magnetic resonance imaging (MRI) are sensitive tests; MRI is able to provide more infor­ mation and better resolution.5 On MRI diffusion-weighted imaging (DWI) an intraparenchymal abscess demonstrates high signal on DWI and low apparent diffusion coefficient (ADC) in the abscess cavity.6,7 In subdural empyema, there may be a disproportionate amount of underlying cortical and white matter edema and enhancement relative to the size of the fluid collection. In patients with spinal epidural abscess there may evidence of diskitis and vertebral body infection. However, even imaging does not have the sensitivity required to definitively diagnose all infections. Lumbar puncture should not be performed in those with brain abscesses given the risk of herniation.

Laboratory and Microbiologic Analysis Laboratory Studies The most useful blood test is the complete blood count with a manual differential. Although an elevated white blood cell (WBC) count is always helpful, patients presenting with a significant suppurative process may have a normal peripheral WBC count. In these patients bandemia may be the only abnormal finding to guide the clinician toward making the diagnosis of an infectious process. It is imperative that the treating team request a manual differential on presentation. Furthermore, a markedly elevated platelet count such as one greater than 500,000 can also help suggest the presence of a suppurative CNS process. An elevated erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) may be useful but are nonspecific.

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Microbiologic Analysis Blood cultures should always be obtained on admission to identify a potential hematogenous source for the CNS or epidural infection. CNS-obtained material must be sent to a laboratory for Gram stain, routine aerobic and anaerobic culture, and in select patients for mycobacterial and fungal cultures. In the immunocompromised patient, a silver stain should be requested to identify Aspergillus species along with a request for modified acid-fast bacillus (AFB) staining to potentially identify a Nocardia species. In an HIV-infected patient pathologic specimens should be sent to a lab to look for Toxoplasma gondii tachyzoites. In the event that routine cultures fail to grow after 4 to 5 days, the clinician must consider whether he or she is dealing with a routine anaerobic process that failed to grow or a more unusual pathogen such as a Nocardia species, fungal or mycobacterial infection, or T. gondii in an HIV-infected patient. In these patients, consultation with an infectious diseases expert and the microbiology laboratory is advised.

Follow-up The most effective approach to evaluate a patient’s response to therapy is to follow the patient’s temperature and WBC trend and the patient’s mental status and to obtain CNS imaging on a regular basis to assess structural improvement.

Management of Space-Occupying Infections Treatment of brain abscess is both surgical and medical. Abscesses greater than 2.5 cm in diameter or those associated with mass effect should be excised or aspirated. Aspiration may be performed with image guidance and through a twist drill or burr hole. Brain imaging should be used to follow the treatment response, with repeat scans every 1 to 2 weeks. In patients with ventriculitis, meningitis, or hydrocephalus that requires cerebrospinal fluid (CSF) drainage, or those with inaccessible abscesses or early abscess formation (cerebritis), medical treatment alone can be attempted preferably after microbiologic analysis on blood or CSF. Broad-spectrum antibiotics are started and refined when culture results are available. Empiric drug regimens for immunocompetent patients should include coverage for methicillin-resistant S. aureus (MRSA), anaerobes, and gram-negative bacilli (including Pseudomonas coverage in the setting of trauma or post neurosurgery) with a regimen such as vancomycin, metronidazole, and cefotaxime, typically for 6 to 8 weeks. The treatment response can be followed initially with weekly brain imaging. This can be spaced out to every 2 weeks during the remainder of the 6- to 8-week antibiotic course, with follow-up scans every 2 to 4 months for the following year to assess for recurrences. The treatment of subdural empyema is surgical either through a craniotomy or burr holes. Early treatment (within 72 hours of symptom onset or sooner) is preferable.8 Broadspectrum empiric antibiotics (similar to that described for brain abscess) should be started early. Once the cause of the infection is defined from culture analysis, antibiotics can be tailored to the organism and continued for 3 to 4 weeks after drainage. Spinal epidural abscess is a neurosurgical

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emergency. Without treatment, severe and permanent spinal cord damage can occur in just a few hours in part because of venous thrombosis rather than compression alone. Treatment includes surgical decompression and drainage, a search for the infectious source (if possible), and antibiotics (empiric as described earlier, then specific antibiotics based on the pathogens).

Outcome The mortality of patients with brain abscess is between 20% and 30%9 and greater in those with a depressed level of consciousness or in coma at admission and distant metastatic focus of infection. Factors such as age, multiple abscesses, and steroid use do not appear to alter outcomes. Mortality in subdural empyema is between 10% and 40%. Younger age and early treatment is associated with better outcome.4,8 For example, Renaudin and Frazee observed that patients treated in less than 72 hours had less than 10% mortality, whereas 70% of patients died or were disabled when treated more than 72 hours after symptom onset.8 Outcome also is associated with neurologic status at presentation and whether sinus thrombophlebitis occurs and its extent. Outcome after spinal epidural abscess is associated with how quickly the diagnosis is made and surgical decompression is achieved and the severity of the spinal cord symptoms at the time of decompression. The more symptoms at the time of decompression, the worse the outcome, although compared with similar neurologic presentations in traumatic spinal cord injury, those with epidural abscess tend to do better.10

Bacterial Meningitis Epidemiology S. pneumoniae (or pneumococcus) and Neisseria meningitidis remain the most common etiology for communityacquired bacterial meningitis. With the widespread use of H. influenzae–conjugated vaccine in children, the incidence of H. influenzae meningitis has decreased.11 S. pneumoniae (or pneumococcus) is now the most common cause of meningitis in the United States, although its incidence too is decreasing with the use of the multivalent pneumococcal vaccine. Group B streptococcus is the most common cause of bacterial meningitis in newborns but rare after the neonatal period, N. meningitidis in children, teens, and young adults and pneumococcus is the most common cause of bacterial meningitis in adults.

Clinical Features The typical presenting signs and symptoms of bacterial meningitis are headache, fever, stiff neck, and altered mental status that each occur in 80% of patients. Kernig’s sign and Brudzinski’s sign are found in 50% of patients. In most cases of bacterial meningitis there also is associated inflammation of the underlying brain tissue (cerebritis). In addition, secondary venous sinus thrombosis, vasculitis, or cranial nerve inflammation may occur. Therefore focal neurologic deficits are seen in about 20% of patients and seizures in about 30% of patients. Papilledema at presentation is uncommon (15 cm H2O). CSF total WBC count is in the 1000 to 10,000 range, and almost all patients with bacterial meningitis have a predominance of neutrophils. CSF glucose is usually decreased, although the CSF-to-serum ratio is more accurate. The CSF protein is almost always elevated (>100 g/ dL). C-reactive protein (CRP), either in the serum or the CSF, or procalcitonin can help differentiate bacterial meningitis from viral meningitis. The specific diagnosis is made on CSF Gram stain and culture. The Gram stain, developed by Hans Christian Gram in Berlin in the late 19th century, colors bacteria by using a crystal violet stain to colorize what are referred to as grampositive organisms blue, namely streptococci and staphylococci. In a subsequent step the specimen is then decolorized with alcohol and counter-stained with the red dye, safranin. Gram-negative bacteria such as coliforms are unable to hold their crystal violet stain but take up the safranin stain, rendering these bacteria red. These procedures are now done exclusively in a microbiology laboratory. This procedure can guide antibiotic therapy until culture and sensitivity results are available. A head CT scan is typically not required and not needed to diagnosis bacterial meningitis. However, it can be useful to exclude mass lesions that are a contradiction to lumbar puncture (LP). The literature supporting the necessity of doing a CT scan of the brain prior to LP is minimal. Between 3% and 4% of patients with meningitis develop herniation syndromes12,13; about 1% of these patients herniate within several hours of the LP (1%). However, a normal CT scan does not eliminate the risk for herniation nor does an abnormal CT scan predict herniation after LP.14 In 2004 Tunkel et al.15 wrote the “Practice Guidelines for the Management of Bacterial Meningitis.” A head CT is recommended before LP in patients with suspected bacterial meningitis who (a) have a history of CNS disease, (b) are immunocompromised, (c) present with a seizure, or have (d) papilledema, (e) an abnormal level of consciousness, or (f) a focal neurologic deficit. Furthermore, in the setting of suspected bacterial meningitis the decision to begin antimicrobial therapy should be made expeditiously and independent of when and if a head CT is performed because earlier treatment is associated with better outcome.

Management Treatment of bacterial meningitis should not be delayed while waiting for a head CT scan. Empiric treatment of the patient should be provided based on the patient’s relative risk for specific organisms. Most immunocompetent adults are at highest risk for S. pneumoniae. Those greater than 50 years old are also at risk for Listeria monocytogenes. Teens and young adults are also susceptible to N. meningitidis (meningococcus). Empiric antibiotics should be administered based on these likely causes. Beta-lactam–resistant pneumococcus is becoming more prevalent in the community (up to 15% in some metropolitan areas in the United States) and so vancomycin should be used as an empiric treatment in the appropriate patient population. Once the Gram stain is obtained and organisms identified by morphology and staining

characteristics the antibiotics can be modified to be more specific. The antibiotics can be changed once again if necessary once the organism has been grown and identified in culture and sensitivities have been obtained. Antibiotic treatment durations are based on the organism found. Both meningococcus and H. influenzae can be treated successfully for 7 days. S. pneumoniae requires 2 weeks of treatment, whereas Listeria and other gram-negative organisms require at least 3 weeks of treatment. In addition, an infectious disease consultant should guide antibiotic therapy. The role of beta corticosteroids has been controversial since the early 1990s. A randomized clinical trial of dexamethasone (10 mg of dexamethasone every 6 hours for 4 days) that included 301 patients with bacterial meningitis has been published.16 The first dose of steroid was given before antibiotic administration. Outcome was better in those who received dexamethasone. This improvement in outcome was almost exclusively in the patients who had S. pneumoniae meningitis; however, due to a small sample size, conclusions regarding the effectiveness of steroids in H. influenzae and meningococcal meningitis are unclear. Because at the time of presentation the offending organism is unknown, the dexamethasone can be started before antibiotics. If an organism other than S. pneumoniae is found to be the offending pathogen, clinical guidelines for treatment of bacterial meningitis recommend against continued routine use of corticosteroids.15 Good supportive intensive care medicine is important in these patients. In bacterial meningitis increased intracranial pressure does occur, yet it is unclear whether monitoring of intracranial pressure or treatment with hypertonic agents such as mannitol or hypertonic saline is useful in this patient population.

Herpes Simplex Encephalitis Epidemiology Herpes simplex viruses (HSVs) are distributed worldwide, and humans are the sole reservoir of this virus. Between 25% and 60% of humans are seropositive for herpes simplex virus by adulthood. Herpes simplex encephalitis (HSE) is the most common cause of sporadic fatal encephalitis in the United States. It is estimated to occur in 1/250,000 to 1/500,000 in the United States or approximately 250 to 500 cases per year.

Pathophysiology It is unclear whether herpes simplex encephalitis represents a primary or recurrent infection. The virus can lie dormant in neurons and ganglia once the patient has been infected. However, it has been demonstrated that patients with HSE and concomitant cutaneous herpes simplex may have two different strains of HSV. No specific triggers for HSE have been identified. Immunosuppression does not predispose patients to HSE. However, patients who are immunosuppressed are at risk for a more aggressive disease with a worse outcome. HSE is always a cortical infection, and no cases of HSE have been reported to involve the brainstem. The temporal lobe is the most commonly infected brain region, although other lobes can develop encephalitis. The virus causes a hemorrhagic and necrotizing encephalitis.

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Clinical Features The common clinical manifestations of HSE are a change in personality, seizures, and decreased level of consciousness. Fever is common, and focal or generalized seizures occur in two thirds of patients. Focal neurologic findings such aphasia or neglect associated with a cortical abnormality or dysphagia and hemiparesis associated with cortical dysfunction may be seen. Headache, nausea, vomiting, and papilledema also are common. The clinical presentation may be subtle and somewhat slow moving.

Diagnosis The diagnosis of HSE is made based on the clinical course, imaging (CT and MRI), and laboratory evaluation, in particular CSF analysis and CSF PCR. Electroencephalography and brain biopsy may be helpful in some patients, but brain biopsies are now infrequently performed in this setting. The CSF WBC count in patients with HSE is in the 10s to the 100s but values of 1000 to 2000 cell/mm3 may be observed. Most of the WBCs are lymphocytes. However, 10% to 25% of patients can have high numbers of neutrophils in their CSF early in the disease course. Red cells in the range of 10s to 1000s/mm3 are seen in the CSF of about 50% of patients and xanthochromia is common. CSF protein may be mild to moderately elevated in approximately 50% of patients. Glucose is usually normal but may be slightly reduced. Opening pressure is elevated in one third of patients. The CSF PCR for herpes simplex is now the test of choice for diagnosis and has a sensitivity of 96% and specificity of 99%.17 Very early in the disease (38o C), a chest x-ray is indicated. Modern ICU care of the intubated patient now includes careful mouth care using chlorhexidine-containing mouth products, inline suctioning, and elevation of the head of the bed to 30 degrees, all in an effort to minimize VAPs (see Chapter 6). In a patient destined for prolonged ventilator support, data now support early tracheotomy placement. In the presence of an unexplained fever, blood cultures also are essential to evaluate for a potential central venous catheter (CVC)–associated infection. Although CVCs often are silver impregnated to help reduce the incidence of catheter-related infections, these infections remain common and a threat to an ICU patient. Blood cultures should always be obtained in a febrile patient as soon as possible and preferably during the febrile episode to increase the yield of capturing the offending organism. Customary practice is to draw aerobic and anaerobic cultures both peripherally and through the central line. This method increases the yield, and, when a blood culture is positive from the central line source yet negative from the periphery, points toward a central line source and early removal of the offending line. Occasionally Candida bloodstream infections occur in an ICU patient (6.9 per 1000 patients), in particular in those whom have been on broad-spectrum antibiotics for prolonged periods, on steroids, or are receiving TPN.54 The source is most often from a central venous catheter (CVC) and responds to removal of the catheter followed by a 10-day course of an appropriate antifungal agent such as fluconazole or caspofungin. Antigen detection and PCR assays could provide an alternative to microscopy, culture, and serology to detect fungal infections, but further study and validation still are required. Other potential sources for fever are deep venous thrombosis with or without pulmonary emboli that can present with tachycardia, fever, hypotension, and a sepsis-like syndrome. Careful examination of the patient and his or her extremities can lead to a timely duplex ultrasound of the legs or arms if indicated. Numerous medications used in the NCCU patient can produce fever including phenytoin, carbamazepine, vancomycin, beta-lactam antibiotics, and blood products. Looking carefully for a new rash may assist in determining that the fever is indeed a medication-related problem. A careful review of the medication list is mandatory to evaluate a febrile postoperative or NCCU patient. Serum procalcitonin, and use of scores such as the Simplified Acute Physiology Score II (SAPS II), Acute Physiology and Chronic Health Evaluation (APACHE), or Sequential Organ Failure Assessment (SOFA)* may differentiate between infectious and noninfectious fever in the ICU.55 Clostridium difficile–induced colitis is an ever-expanding complication of hospitalization and primarily associated with antibiotic use but occasionally is associated with chemotherapeutic agents.56 Recently identified strains of hypervirulent C. difficile (PCR ribotype 027 or BI/NAP1/027) have entered *Note: SOFA also refers to Sepsis-Related Organ Failure Assessment.

the hospital environment, producing toxic megacolon, and occasional deaths are now being reported in increasing numbers particularly in the elderly.57 C. difficile colitis presents with a fever and diarrhea but with few other clinical signs and symptoms. The diarrhea often has a unique odor. The diagnosis of C. difficile requires identification of C. difficile toxin A or B in diarrheal stool. However, the accuracy of these diagnostic tests is limited and the optimal diagnostic testing algorithm is still being elucidated; for example, it is difficult to predict and prevent development of severe or relapsing C. difficile infection in patients who initially present with mild symptoms.58 The use of probiotics such as Lactobacillus plantarum 299/299v plus fiber (LAB), to prevent and or help with treatment of C. difficile is conflicting.59 Urinary tract infections (UTIs) and in particular catheterassociated UTIs, remain a common source of HAIs and account for 20% to 50% of all HAIs in the ICU.60 Longer duration of Foley catheterization (>5 days) and poor urinary catheter management, specifically disconnection of the closed system, are significant factors associated with hospitalacquired UTIs.61 In a patient with an indwelling Foley catheter (FC), simple evaluation of the urine may be confusing. Furthermore, nearly all patients with an FC in place for more than 4 weeks have pyuria and bacteriuria. In the febrile patient with cloudy urine and a fever, it is incumbent on the team of physicians to rule out other potential sources of fever before attributing the fever to the urine. Treatment of UTIs with antibiotics is more likely to clear bacteriuria and relieve symptoms but also selects for resistant uropathogens and commensal bacteria and can adversely affect the gut and vaginal microbiota. Uropathogens are increasingly becoming resistant to currently available antibiotics and the case-fatality rate of hospitalacquired UTIs remains high.62 Consequently, alternative strategies including avoidance of inappropriate FC use, removal of a Foley, intermittent catheterization, and condom catheters are necessary to manage UTIs.63

Sepsis Sepsis is associated with increased morbidity, mortality, and costs of care64 and remains the leading cause of death in critically ill patients.65 The definition of sepsis is provided in Table 17.2. The initial stage of sepsis is referred to as systemic inflammatory response syndrome (SIRS) and is defined as a temperature greater than 38o C or less than 36o C, pulse more than 90 beats per minute, respiratory rate greater than 20 per minute, and a WBC more than 12,000 or less than 4000. However, there are no specific laboratory studies at present to help guide practitioners in defining an early septic patient although serum procalcitonin levels may provide some insight into severe infections.66,67 Instead careful attention to the patient is the bedrock of early detection and treatment of an infected patient, including a postoperative neurosurgical patient in the NCCU. Table 17.3 lists common laboratory findings in septic patients. In addition, PCR testing provides increased sensitivity for bloodstream infections.68 The Surviving Sepsis Campaign (SSC) was launched in 2002 as a collaborative initiative between the European Society of Intensive Care Medicine (ESICM), the International Sepsis Forum (ISF), and the Society of Critical Care Medicine (SCCM) to address the poor outcome associated with sepsis. The SSC developed evidence-based

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management guidelines that were published in 2004 and updated in 200869 with the goal of improving outcomes in sepsis and septic shock. Since the development of these guidelines, more than 20,000 patients have been entered into the SSC database; analysis of this showed that participation in the SSC was associated with continuous quality improvement in sepsis care and a 5.4% absolute survival benefit.70,71 Compliance with the overall sepsis bundle and its individual elements is important. This can be facilitated by weekly feedback sessions.72 In addition, a variety of potential measures of quality of care for septic patients—vancomycin administration and its timing, steroid administration, blood culture collection, activated protein C administration, and broadspectrum antibiotic administration and its timing, among

Table 17.2  Consensus Definition of SIRS and Sepsis by the American College of Chest Physicians and the Society of Critical Care Medicine SIRS

Two or more of the following criteria: —Temperature 38° C —HR >90 —RR >20 or PaCO2 12,000 10% immature (band) forms

Sepsis

Documented infection together with 2 or more SIRS criteria above

Severe sepsis

Sepsis associated with organ dysfunction

Septic shock

Sepsis with refractory hypotension or hypoperfusion abnormalities in spite of adequate fluid resuscitation

Modified from: Bone RC, Balk RA, Cerra FB, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest 1992;101(6):1644–55 HR, Heart rate; RR, respiratory rate; SIRS, Systemic inflammatory response syndrome; WBC, white blood cell.

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others—have been identified to help evaluate quality of sepsis care and improve delivery of evidence-based care in the ICU.73 Finally, ICU patients may be followed for disease progression using a number of techniques, for example, the SOFA system (Table 17.4) that originally was developed by the ESICM to describe organ failure in sepsis.74,75 The SOFA is a six-organ dysfunction/failure score that measures multiple organ failure daily. Each organ is graded from 0 (normal) to 4 (the most abnormal), providing a daily score of 0 to 24 points. Sequential assessment of organ dysfunction during the first few days of ICU care is a good indicator of prognosis. The mean and highest SOFA scores are associated with outcome. In addition an increase in SOFA score during the first 48 hours in the ICU predicts a mortality rate of at least 50%.74-77 SOFA use has been validated in the NCCU and traumatic brain injury (TBI).78

Infection Prevention in the Intensive Care Unit HAIs are common (about 5% of all hospitalized patients), and in particular catheter-related bloodstream infection, VAP, surgical site infection, and catheter-associated urinary tract infections increase the cost of care and patient length of stay and adversely affect outcome.79-81 In patients with acute neurologic disorders (e.g., TBI or stroke) or those admitted to the ICU the incidence of HAIs is greater—30%.82-84 For example, Westendorp et al. in a meta-analysis of 87 studies (8 of which were restricted to patients admitted to the ICU) that included 137,817 patients after stroke observed that infection complicated 30% of these patients.83 In ICUs today multiresistant gram-negative bacteria are becoming more frequent as the cause of HAIs.85 However, several lines of evidence demonstrate that hand hygiene, isolation, antibiotic control measures, and compliance with protocols designed to prevent specific infections are associated with a reduction in HAIs including central line–associated bloodstream infections and

Table 17.3  Common Laboratory Findings in Sepsis Laboratory Test

Findings

Comments

White blood cell count

Leukocytosis or leukopenia

Endotoxemia may cause early leukopenia.

Platelet count

Thrombocytosis or thrombocytopenia

Early in the disease course a high platelet count may be observed as an acute-phase response. Low platelet counts found in DIC.

Coagulation

Protein C deficiency Antithrombin deficiency Elevated D-dimer level Prolonged INR (PT) and PTT

Coagulation abnormalities may be identified before onset of organ failure and without frank bleeding.

Creatinine

Increase from baseline

Doubling indicates acute renal injury.

Lactic acid

>4 mmol/L (36 mg/dL)

Consistent with tissue hypoxia

Liver function and enzymes

Elevated bilirubin, alkaline phosphatase, AST, and ALT

Hypoperfusion can contribute to acute hepatocellular injury.

Serum phosphate

Hypophosphatemia

Inversely correlated with proinflammatory cytokine levels

CRP

Elevated

Acute-phase response

Procalcitonin

Elevated

May help differentiate infectious from noninfectious SIRS

ALT, Alanine aminotransferase; AST, aspartate transaminase; CRP, C-reactive protein; DIC, disseminated intravascular coagulation; INR, international normalized ratio; PT, prothrombin time; PTT, partial thromboplastin time; SIRS, systemic inflammatory response syndrome.

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Table 17.4  The SOFA (Sepsis-Related Organ Failure Assessment)* Score to Describe Organ Dysfunction or Failure Organ

 0

 1

2

3

4

Respiration PaO2/FiO2 (mm Hg) SaO2/FiO2

>400

350

≈300

Urine/plasma osmolality

>1.5

1.0

FENa

1%

FE urea

50%

AKI, Acute kidney injury; ATN, acute tubular necrosis; BUN, blood urea nitrogen; FE, fractional excretion; FENa, fractional excretion of sodium; SC, serum creatinine

increase of BUN compared with creatinine with a BUNto-SC ratio of greater than 10 : 1 to 15 : 1. As tubular function is preserved, there is a high urine osmolality, greater than 350 mOsm/L. Of the tests available (see Table 22.3), the fractional excretion of sodium (FENa) may be the preferred screening test to differentiate between prerenal AKI and ATN (Table 22.4). FENa = (urine Na × serum creatinine)/ (serum Na × urine creatinine) ×100 Classically, a FENa less than 1% is characteristic of prerenal AKI, whereas a FENa greater than 1% to 2% signifies ATN. However, a low FENa is not unique to prerenal disease. It can occur in disorders associated with normal tubular function but a low GFR such as acute glomerulonephritis (GN), vasculitis, and acute urinary tract obstruction. It also can be seen when ATN is superimposed on a chronic sodium-retaining state as may occur with aminoglycoside therapy, congestive heart failure (CHF), or cirrhosis.29 The confounding effects of diuretics may be obviated by the use of the fractional excretion of urea, which when less than 35% accurately indicates prerenal azotemia.30

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Table 22.4  Interpretation of the Fractional Excretion of Sodium FENa 1%-2% ATN Prerenal AKI with: Glucosuria Diuretics Acute on chronic disease Mannitol AKI, Acute kidney injury; ATN, acute tubular necrosis; CHF, congestive heart failure; FENa, fractional excretion of sodium; GFR, glomerular filtration rate.

Fig. 22.7  Urine sediment showing free red cells and a red cell cast that is tightly packed with red cells. Red cell casts are virtually diagnostic of glomerulonephritis or vasculitis. (Courtesy Harvard Medical School.)

Glomerular Disease in AKI Acute glomerulonephritis may be the cause of AKI in the ICU due to bacterial endocarditis, staphylococcal sepsis, visceral abscesses, hepatitis B, systemic lupus erythematosus (SLE), Goodpasture syndrome, or rapidly progressive glomerulonephritis (RPGN). Red cells and red blood cell casts, and proteinuria are seen on urinalysis31 (Fig. 22.7). An alteration of glomerular hemodynamics also may contribute to AKI. Afferent vasoconstriction may be seen in hepatorenal syndrome and efferent vasodilation from ACE inhibitors. Vasodilators such as nitroprusside and nifedipine may contribute to AKI by altering intrarenal hemodynamics without systemic hypotension.39

Interstitial Disease in AKI Fig. 22.6  Urine sediment on urinalysis showing multiple muddy brown granular casts that suggest acute tubular necrosis. (Courtesy Harvard Medical School.)

The urinalysis in prerenal disease is normal (this may include granular casts), whereas ATN has muddy brown casts31 (Fig. 22.6). Pathologically, tubular necrosis is usually not seen with ATN, and there is often limited histologic evidence of injury despite marked functional impairment.32 ATN may be induced by those factors that cause prerenal AKI as well as by drugs, rhabdomyolysis, tumor lysis, and vascular insults. Diuretics may convert ATN from an oliguric to a nonoliguric state and may be tried for volume control, but they have no effect on renal recovery or survival.33,34 Loop diuretics work by inhibition of a Na+−K+−2Cl− transporter in the loop of Henle. A secretory isoform of this transporter is present in the inner ear endolymph, and thus high-dose diuretics may lead to permanent hearing loss.35 Dopamine does not provide protection in early ATN and may cause harm by reducing renal blood flow in postischemic ATN.36-38 Prevention of ATN by optimizing volume status and avoiding nephrotoxic agents remain the mainstay of management.

Drugs most often induce acute interstitial nephritis, but infections such as from Legionella, Leptospira, and streptococcal organisms, and autoimmune disorders may also be responsible. The most commonly implicated drugs are beta-lactam antibiotics, sulfonamides, rifampin, and nonsteroidal antiinflammatory drugs (NSAIDs). The complete clinical spectrum presents as fever, rash, arthralgias, and eosinophilia, and a urine analysis shows sterile pyuria with white blood cell casts, and eosinophiluria (except NSAIDs). Hematuria and proteinuria also are common. The FENa usually is greater than 1%, indicating tubular damage, but lower values may be seen in mild disease.40

AKI in Cirrhosis Patients with cirrhosis or acute hepatitis can develop renal failure without proteinuria and with a reduced urinary sodium. The hallmark is intense renal vasoconstriction with peripheral vasodilation. The kidneys in patients with hepatorenal syndrome (HRS) are normal on autopsy and functioned normally when transplanted into patients without cirrhosis. Moreover, HRS can be reversed following liver transplantation.41-43 In 1996 the International Ascites Club published a consensus paper that subdivided HRS into two

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types. Type 1 HRS is characterized by a rapid decline in renal function with a doubling of SC to more than 2.5 mg/dL or having a creatinine clearance to less than 20 mL/min within 2 weeks. In type 2 HRS the presentation is of stable renal failure in a patient with refractory ascites in which the SC increases to more than 1.5 mg/dL or a creatinine clearance of less than 40 mL/min.44 Untreated type 1 has mortality as high as 80% in 2 weeks, whereas type 2 has a median survival of approximately 6 months. The precipitating factors for HRS have been identified as bacterial infection (48%), gastrointestinal (GI) bleeding (33%), aggressive paracentesis (27%), and drugs (diuretics, aminoglycosides, nonsteroidal anti-inflammatory drugs [NSAIDs], and angiotensin-converting enzyme inhibitors [ACEIs]/angiotensin II receptor blockers [ARBs]). However, 24% develop type 1 HRS without an obvious precipitating factor.45 A high index of suspicion is needed to assess AKI in the context of advanced liver disease because reduction in muscle may render a SC within the normal range even in the context of a decreased GFR, and GI bleeding and the amount of protein in the diet may affect the BUN. Sepsis should be suspected in any cirrhotic patient with AKI even in the absence of leukocytosis and fever. Clinically the syndrome presents with prerenal physiology (i.e., oliguria, a benign urine sediment, and low urine sodium). Treatment may include midodrine (an alpha agonist) and octreotide (a long-acting form of somatostatin that inhibits endogenous vasodilator release), with albumin, and terlipressin (a vasopressin analog used in Europe).46,47 Dialysis should be offered only if there is a chance for liver transplantation in the short term. Transjugular intrahepatic portosystemic shunt (TIPS) involves placing a stent between the hepatic vein and the intrahepatic portion of the portal vein. It is primarily designed to treat bleeding varices, but it has been used for HRS, though it may worsen encephalopathy. It may serve as a bridge to liver transplantation, which is the only effective treatment.48,49

Vascular Diseases Causing AKI A number of vascular disorders of both the large and small vessels may give a prerenal picture of AKI. Large vessel disease may arise from operative arterial cross-clamping, renal artery thrombosis or embolism, or renal artery stenosis. Renal infarction may present with fever, hematuria, acute flank pain, ileus, and leukocytosis that may mimic an acute abdomen. Hypertensive crises may disrupt the vascular endothelium and be associated with thrombocytopenia and microangiopathy, retinopathy, and AKI. Systemic vasculitis such as Wegener’s granulomatosis, polyarteritis nodosa, hypersensitivity vasculitis, and Henoch-Schönlein purpura often cause AKI. Cholesterol emboli syndrome (CES) arises following aortic manipulation from percutaneous intervention, surgery, or systemic anticoagulation. The crystals incite an inflammatory reaction and adventitial fibrosis may obliterate the vessel lumen. Hypocomplementemia and eosinophilia are seen, and any organ may be affected including the kidney, the GI tract with bleeding from microinfarcts, the skin, and the central nervous system (CNS) with stroke. The cutaneous manifestations may include a blue toe or livedo reticularis that results from a superficial infarct and compensatory dilation of the surrounding vessels to give a livedo or “lacelike” pattern (Fig.

Fig. 22.8  Cutaneous manifestations of cholesterol emboli syndrome.

22.8). Anticoagulation is dangerous in patients with CES but may be necessary in patients with a thrombotic event.50

Abdominal Compartment Syndrome Abdominal compartment syndrome (ACS) refers to symptomatic organ dysfunction arising from an increase in intraabdominal pressure (IAP; See also Chapter 23). A pressure of 20 with organ dysfunction is the operational definition used in studies, but in clinical practice a single IAP cannot predictably diagnose ACS in all patients. ACS arises from tissue edema or third-spaced fluid and may occur in diverse clinical states such as abdominal surgery, pancreatitis, and bleeding. Hypotension may arise from the ensuing inferior vena cava (IVC) obstruction, and be accompanied by a high pulmonary artery occlusion pressure or elevated femoral vein pressure despite a reduced venous return. Clinically the kidney dysfunction looks similar to prerenal kidney disease with a low urinary sodium, and an increase in plasma renin, aldosterone, and ADH level. Oliguria may develop at an IAP of 15 mm Hg and anuria at 30 mm Hg.51 A high index of suspicion is needed because this condition may look like evolution of the underlying disease process with hypotension, acute respiratory distress syndrome (ARDS), and AKI from multiorgan failure.52

Drugs and AKI Many medications can induce kidney failure and may lead to a picture of prerenal AKI, ATN, or acute interstitial nephritis. A complete discussion is beyond the scope of this chapter, but some common drugs are discussed.



NSAIDs and Acetaminophen-Induced AKI Prostacyclin and prostaglandin E2 preserve renal blood flow and glomerular filtration and inhibition of prostaglandin synthesis with a NSAID can lead to a reversible AKI with an SC increase within the first 3 to 7 days.53,54 This hemodynamically mediated injury may be less with aspirin because there is only partial inhibition of glomerular cyclooxygenase.55 Acute interstitial nephritis and the nephritic syndrome also may occur with NSAIDs and it presents with hematuria, pyuria, white cell casts,31 and proteinuria along with an acute rise in SC (Fig. 22.9). The complete syndrome of fever, rash, eosinophilia, and eosinophiluria may be absent. Spontaneous recovery usually occurs within weeks to months after discontinuation of therapy.56 Membranous nephropathy with proteinuria has been reported to occur with diclofenac, but probably any NSAID may be involved.57 Acetaminophen-induced acute renal failure may occur with an overdose, but some alcoholics are at increased risk from therapeutic doses. The pathologic changes reveal ATN, and the uric acid shows granular and epithelial cell casts31 (Fig. 22.10).

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217

Recovery to baseline generally occurs spontaneously within 1 to 4 weeks, and acetylcysteine has no protective effect on the kidney as it does with the liver.58 Drugs that increase cytochrome P450 activity such as phenytoin, phenobarbital, rifampin, and carbamazepine enhance the risk of acetaminophen nephrotoxicity.59

Radiocontrast Media–Induced AKI Radiocontrast media (RCM) are either ionic or nonionic and are of variable osmolality. Risk factors for RCM–induced AKI include underlying renal insufficiency (SC >1.5 mg/dL), diabetic nephropathy, heart failure, volume depletion, PCI (promotes the development of atheroemboli), and the dose and tonicity of the RCM agent. Renal injury is observed within the first 12 to 24 hours with recovery typically beginning within 3 to 5 days.60,61 Patients with diabetes and heart failure are at increased risk of AKI from RCM, possibly due to impaired nitric oxide (NO) generation.62 Many of the commonly used RCM agents induce a false-positive result when either a dipstick or sulfosalicylic acid is used to detect proteinuria, and this should not be tested for at least 24 hours after a contrast study.63 ATN may result; however, the FENa is often less than 1%. Prevention is best accomplished with hydration, often with sodium bicarbonate. N-acetylcysteine may also have protective benefit.64

Aminoglycosides These are concentrated in the proximal tubular cells, and AKI can become evident several days after the drug has been stopped. Distal tubular damage also occurs with a loss in renal concentrating ability resulting in polyuria and hypomagnesemia. Risk factors include volume contraction, age, hypokalemia, and a short dosing interval. The routine monitoring of peak and tough levels does not decrease the likelihood of nephrotoxicity. Fig. 22.9  White cell cast in which blue-stained white cells (arrow) are contained within a granular cast. (Courtesy Frances Andrus, BA, Victoria Hospital, London, Ontario, Canada.)

Lithium Lithium may cause a nephrogenic DI by causing ADH resistance in up to 20% of patients. Some data suggest lithium levels may increase with concomitant ACE inhibitors.65,66

ACE Inhibitors

Fig. 22.10  Epithelial cell cast with free epithelial cells (arrow) in the urine sediment. Renal tubular epithelial cells are larger than white cells and have a single, large central nucleus. (Courtesy Frances Andrus, BA, Victoria Hospital, London, Ontario, Canada.)

The primary side effects occur by one of two mechanisms. A reduction in angiotensin II formation may cause hypotension, AKI, hyperkalemia, and problems during pregnancy. Cough, edema, and anaphylactoid reactions are related to increased kinins because ACE is also a kininase. The side effects related to reduced angiotensin II, but not those related to kinins, are also seen with the angiotensin receptor blockers. AKI is seen predominantly in patients with bilateral renal artery stenosis, hypertensive nephrosclerosis, CHF, polycystic kidney disease, or chronic renal failure. In each of these the GFR is partially maintained by efferent arteriolar vasoconstriction mediated by angiotensin II.67 The rise in SC usually occurs in 3 to 5 days. Hyperkalemia may result from ACEI/ARBs because angiotensin II increases aldosterone that is the major hormonal stimulus to urinary potassium excretion.

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Fig. 22.11  Skin involvement is characteristic with scleromyxedema-like fibrosis in nephrogenic systemic fibrosis (NSF) that can complicate Gadolinium administration.

Table 22.5  Causes of Rhabdomyolysis

Fig. 22.12  Uric acid crystals seen on the urinalysis. These crystals are pleomorphic, most often appearing as rhombic plates or rosettes. They are yellow or reddish-brown and form only in an acid urine. (Courtesy

• Trauma and compartment syndromes • Seizures, dystonic reactions • Impaired energy supply—carbon monoxide poisoning, mitochondrial myopathies • Malignant hyperthermia and neuroleptic malignant syndrome • Near-drowning with hypothermia • Drugs Anticholinergics due to the loss of impaired sweating Statins, colchicine—direct myotoxins Macrolides, cyclosporine, gemfibrozil, and protease inhibitors interfere with statin clearance and potentiate toxicity • Cocaine-induced hyperthermia • Carbon monoxide—insufficient energy production • Infections—ehrlichiosis, falciparum malaria • Electrolyte disorders—hypokalemia, hypophosphatemia (in alcoholics receiving total parenteral nutrition without phosphate supplementation)

Harvard Medical School.)

Amphotericin B Amphotericin B results in renal insufficiency with K+ and Mg++ wasting and metabolic acidosis due to a type 1 or distal RTA and polyuria due to a nephrogenic DI.

Gadolinium Gadolinium may be contraindicated in patients with a GFR less than 30 mL/min or any degree of renal insufficiency in patients with hepatorenal syndrome because its use is associated with nephrogenic systemic fibrosis (NSF). The latency of NSF is usually 2 to 4 weeks, but may be between 2 days and 18 months. Skin involvement is characteristic with scleromyxedema-like fibrosis that may lead to disabling joint contractures (Fig. 22.11). Systemic involvement may include the lungs, pleura, myocardium, pericardium, and dura. Scleral plaques are common.68

Acute Tumor Lysis Syndrome, Acute Uric Acid Nephropathy, and AKI Acute tumor lysis syndrome consists of hyperphosphatemia (>8 mg/dL), hypocalcemia, hyperkalemia, and hyperuricemia

(>15 mg/dL) in patients with tumors associated with high cell turnover or with chemotherapy (e.g., after treatment of leukemias and lymphoma, or other malignancies including medulloblastomas). AKI results from tubular obstruction by precipitated uric acid crystals or depiction of calcium phosphate complexes in the tubular lumen and interstitium.69 Patients have decreased urine output with uric acid crystals seen on the urinalysis31 (Fig. 22.12). Treatment includes adequate hydration and allopurinol. The role of urinary alkalinization is controversial.70

Pigment-Induced AKI Myoglobin from rhabdomyolysis and hemoglobin from intravascular hemolysis are heme pigments that may induce AKI. Hemolysis leading to AKI is uncommon and usually arises from a transfusion reaction due to ABO incompatible blood. Rhabdomyolysis is more common and may arise from a variety of causes (Table 22.5). Patients with rhabdomyolysis present with the triad of pigmented granular casts, elevated creatine kinase (CK), and myoglobinuria—a red to brown urine sediment that tests positive for heme but without red blood cells. Myoglobin is rapidly cleared, so one may see

elevated CK levels without myoglobinuria. The plasma is normal color unless its excretion is impaired from renal insufficiency. Patients with hemolysis have a similar finding in their urine but have a reduced haptoglobin and abnormal peripheral smear with red plasma.71 The renal injury results from obstruction of the tubules from heme pigment casts, tubular injury from free chelatable iron, and volume depletion. In contrast to other forms of ATN, the FENa is often less than 1%. In rhabdomyolysis, abnormalities in serum electrolytes are common and include metabolic acidosis, hyperuricemia, hyperkalemia, and hyperphosphatemia. Initial hypocalcemia, caused from the deposition of calcium in damaged muscle and decreased bone responsiveness to parathyroid hormone (PTH), may subsequently be followed by hypercalcemia during recovery when this calcium is released and secondary hyperparathyroidism from AKI.72 Treatment is with saline, potentially up to 1 to 2 L/hr to maintain a urine output of 200 to 300 mL/hr. After diuresis is established, urinary alkalinization with 75 mmol of sodium bicarbonate in 1 L 0.45 NS with a goal of a urine pH above 6.5 can be initiated. This may mitigate some of the deleterious effect of myoglobin (or hemoglobin), but it may induce hypocalcemia by precipitating calcium phosphate with ensuing tetany, seizures, or arrhythmias. Close monitoring of serum bicarbonate, calcium, potassium, and urine pH is required. A loop diuretic or mannitol may be added if diuresis is not established after volume repletion. Mannitol may be beneficial with a CK greater than 20,000 to 30,000 U/L, but it is recommended that the plasma osmolality and osmolal gap be measured every 4 to 6 hours. Therapy is continued until the urine discoloration clears and the plasma CK is less than 5000 to 10,000 U/L or if the urine pH does not increase above 6.5 after 4 hours or the osmolal gap rises above 55 mosmol/kg.73

AKI in Pregnancy AKI may occur in association with microangiopathic hemolytic anemia and thrombocytopenia in late pregnancy. Two entities of principal concern are thrombotic thrombocytopenic purpura and hemolytic uremic syndrome (TTP-HUS) and severe preeclampsia, usually with the HELLP syndrome (hemolysis, elevated liver enzymes, low platelets). TTP-HUS probably exists as a continuum, but TTP is usually seen antepartum and is diagnosed when neurologic abnormalities predominate, whereas HUS is characterized by more severe renal failure and is seen postpartum. These distinctions are frequently unclear and may not be important for management.74 The therapy of TTP-HUS in pregnancy is plasma infusion with or without plasma exchange as in the nonpregnant patient. Delivery is indicated for the HELLP variant of preeclampsia. Acute fatty liver of pregnancy results from fatty infiltration of hepatocytes with inflammation and is associated with AKI in 60% of cases. Patients have elevated liver function tests (LFTs) with disseminated intravascular coagulation (DIC) and delivery is indicated. Bilateral renal cortical necrosis is a complication of pregnancy caused by abruptio placentae, placenta previa, intrauterine fetal death, or amniotic fluid embolism. Patients present with a triad of anuria, gross hematuria, and flank pain. There is no specific therapy.

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Table 22.6  Causes of Postrenal Failure Bladder outlet obstruction Prostate enlargement Pelvic pathology Crystalluria Acyclovir Indinavir Uric acid Papillary tip necrosis Diabetes mellitus with pyelonephritis Analgesic abuse Sickle cell disease

Postrenal AKI Although an uncommon cause of AKI in the ICU, postrenal obstruction represents a reversible form of renal injury. Imaging of the renal system is required for proper management of AKI as well as measuring postvoid residuals (>50 mL is abnormal). As intratubular pressure increases, glomerular filtration pressure decreases. Postrenal AKI can be divided into renal and extrarenal causes (Table 22.6). Intrarenal causes include crystal deposition that may occur with ethylene glycol, uric acid nephropathy that may occur in tumor lysis syndrome, or tubular obstruction from light chain casts that may occur with multiple myeloma. Extrarenal causes may include prostate disease, pelvic malignancy, and retroperitoneal disorders.75 It is important to recognize that patients with a partial obstruction may have a normal or increased urine output due to a secondary concentrating defect. The commonly discussed “postobstructive” diuresis is usually a physiologic response to excrete the fluid retained during the obstruction, and assiduous replacement of this can lead to volume overload. There may be the need for some fluid above baseline due to a mild sodium-wasting tendency and a mild concentrating defect due to the down-regulation of water channels. Half normal saline at 75 mL/hr, with attention to volume status, is suggested as an appropriate initial therapy.76

Renal Replacement Therapy in AKI The acute indications for RRT include volume overload, lifethreatening metabolic abnormalities such as hyperkalemia and acidosis, acute pericarditis, and encephalopathy. A detailed description of RRT is beyond the scope of this chapter; the reader is referred to recent reviews for further information.10,12,77-80 The objectives of RRT are to remove fluid by ultrafiltration and control azotemia by removing excess solute. Although peritoneal dialysis is still used, RRT is almost always accomplished by intravascular access in the ICU. Intermittent hemodialysis (IHD) is the most frequently used form of RRT in the ICU and is accomplished by a central venous doublelumen catheter that passes the blood through a dialysis membrane. Studies have demonstrated improved clinical outcomes with the use of synthetic biocompatible membranes (polysulfone, polyamide, polyacrylonitrile, and polymethyl methacrylate) compared to cellulose-based membranes (cellulose acetate, cuprophane.) Hypoxemia with a PaO2 decrease of 10 torr may occur, but the major complication of IHD is hypotension that may prompt consideration for different continuous renal replacement therapy (CRRT) strategies.

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However, there is no survival advantage with CRRT compared with IHD, and the RRT choice may depend on a variety of factors. When rapid solute control is necessary such as hyperkalemia, IHD is most suitable. Slow continuous ultrafiltration (SCUF) may be preferred if volume overload without azotemia is present. Continuous veno-venous hemofiltration (CVVH) is indicated with hepatic failure, head trauma, or septic shock.19 Neurologic complications can be common in patients undergoing hemodialysis. The dialysis disequilibrium syndrome refers to headache, nausea, delirium, and asterixis that may progress to seizures, coma, or death. It is thought to result from cerebral edema, and risk factors include older age, severe acidosis, and new hemodialysis patients with markedly elevated BUN. Milder symptoms such as muscle cramps and anorexia are part of this syndrome. Erythropoietin may cause a rapid increase in blood pressure and result in encephalopathy and seizures. Other medications may precipitate seizures in the hemodialysis population including beta-lactam antibiotics, meperidine, metoclopramide, and acyclovir. Hypotension or a reactive hypertension from a reactive vasoconstriction from a reactive hypotension may precipitate seizures. Dialysis patients are at increased risk for intracerebral hemorrhage (ICH) and SAH, and subdural hematoma and ischemic strokes.81 CRRT may affect the dosing of antibiotics, and Table 22.7 reflects the changes that may be needed.

Table 22.7  Antibiotic Dosing Recommendations in CRRT85 Drug

CVVH

CVVHD (HDF)

Amikacin

7.5 mg/kg q24h

Same

Amphotericin   Deoxycholate   Lipid complex   Liposomal

0.4-1 mg/kg q24h 3-5 mg/kg q24h 3-5 mg/kg q24h

Same Same Same

Acyclovir

5-7.5 mg/kg q24h

Same

Ampicillin-sulbactam

3 g q12h

3 g q8h

Aztreonam

1-2 g q12h

2 g q12h

Cefazolin

1-2 g q12h

2 g q12h

Cefepime

1-2 g q12h

2 g q12r

Cefotaxime

1-2 g q12h

2 g q12h

Ceftazidime

1-2 g q12 h

2 g q12h

Ceftriaxone

2 g q12-24h

Same

Cefuroxime

1.5 g q8-12h

1.5 g q8h

Clindamycin

600-900 mg q8h

Same

Ciprofloxacin

200 mg q12h

200-400 mg q12h

Colistin

2.5 mg/kg q48h

Same

Daptomycin

4 or 6 mg/kg q48h

Same

Doxycycline

100-200 mg q12h

Same

Prognosis in AKI

Fluconazole

200-400 mg q24h

400-800 mg q24h

Nonoliguric AKI, as well as AKI that is associated with aminoglycosides and RCM, may have a mortality of 25% to 30%. AKI occurring in the context of septic shock and burns has a mortality rate of 70% to 90%, usually as a result of infection.50 If the patient survives, oliguria averages 10 to 14 days. Over the next 3 to 7 days is an increase in urinary volume, but a sustained rise in the BUN and creatinine. Fluid administration is often needed, and dialysis can usually be discontinued. Most survivors regain function within 30 days, although rarely recovery may extend to 90 days.19

Imipenem-cilastatin

250 mg q6h or 500 mg q8h

250 mg q6h or 500 mg q8h 500 mg q6h

Itraconazole

No change

No change

Levofloxacin

250 mg q24h

Same

Linezolid

600 mg q12h

Same

Meropenem

1 g q12h

Same

Metronidazole

500 mg q6-8h

Same

Moxifloxacin

400 mg q24h

Same

Nafcillin or oxacillin

2 g q4-6h

Same

Piperacillintazobactam

2.25 g q6h

2.25-3.375 g q6h

Rifampin

300-600 mg q12h

Same

Ticarcillin-clavulanate

2 g q6-8h

3.1 g q6h

Tobramycin and gentamicin

Load 2 mg/kg then 1.5-2 mg/kg q24h and check levels

Vancomycin

1 g q48h (check levels)

1 g q24h (check levels)

Voriconazole

4 mg/kg PO q12h

Same

Acid-Base Balance in Critical Care A number of rules should be learned, but an important principle is that all acid-base assessment must be accompanied by a clinical history because this will help elucidate which of several possible patterns reflect clinical reality.7,82,83 An approach to analysis of acid-base disorders is provided in Table 22.8. Also, because an arterial blood gas (ABG) is obtained in the evaluation of these disorders, a brief statement is made about normal gas exchange. Monitoring ventilation and pulmonary function is discussed in Chapter 20.

Normal Gas Exchange Respiration is a complex process involving integration between the pons, medulla, spinal cord, carotid body, and muscles. Increases in PaCO2 are sensed in the medulla, causing stimulation of respiration. Hypoxemia is detected in the carotid body (located at the bifurcation of the internal and external carotid artery). In chronic respiratory acidosis the pH is nearly normal, despite a high PaCO2, and the medulla is no longer sensitive to elevations in PaCO2. This makes hypoxemia the

CRRT, Continuous renal replacement therapy; CVVH, continuous veno-venous hemofiltration; CVVHD, continuous veno-venous hemodialysis.

primary stimulus for respiration. Delivering high concentrations of oxygen to these patients may suppress the hypoxic respiratory drive. The alveolar-arterial gradient (A-a gradient) is important in evaluating disorders of respiration (Table 22.9). The A-a gradient tells us that the presence of carbon dioxide (CO2) in the alveoli reduces the alveolar oxygen content. Traditionally, when a clinician is confronted with

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221

Table 22.8  An Approach to Acid-Base Disorders (59) STAGE 1: IDENTIFY THE PRIMARY ACID-BASE DISORDER

Rule 1 Examine the pHa and PaCO2. If either is abnormal, an acid-base abnormality is present. Rule 2 If they are both abnormal, a primary disorder is present. If they are abnormal in the same direction, the primary disorder is metabolic. If they are abnormal in opposite directions, the primary disorder is respiratory. Example: 7.23/23 Both are decreased, so this is a primary metabolic acidosis. Rule 3 If only one is abnormal, a mixed disorder is present. Example: 7.37/55 Because the PaCO2 is elevated and there is a normal pH, a mixed disorder is present: a respiratory acidosis with a metabolic alkalosis. Compensatory processes do not normalize the pH. STAGE 2: EVALUATE THE COMPENSATORY RESPONSE

If only one of either the PaCO2 or pH is abnormal, a mixed disorder is present; skip to stage 3 for further analysis. When the pH and PaCO2 are both abnormal and a primary disorder is present, evaluate the degree of compensation to determine if another process is present. Rule 4 If the pH and PaCO2 change in the same direction, a metabolic process is present, and the HCO3 is used to determine the appropriate PaCO2. Compensation for metabolic acidosis:  PaCO2 = (1.5 × HCO3) + 8 ± 2 Compensation for metabolic alkalosis  PaCO2 = (0.7 × HCO3) + 20 ± 5 If the PaCO2 is greater than expected, a concomitant respiratory acidosis is present, whereas if it is lower than predicted, a respiratory alkalosis exists. Example: pH = 7.23, PaCO2 = 23, HCO3 = 15 mEq/L When the pH and PaCO2 are both abnormal in the same lower direction, this indicates a primary metabolic acidosis. The expected PaCO2 would be 30.5 ± 2. Because the PaCO2 is lower than this expected value, a superimposed respiratory alkalosis is present. Rule 5 If the pH and PaCO2 change in opposite directions, a respiratory disorder is present. Using the history and the equations for the expected pH and HCO3, determine if the condition is acute, partially compensated, or fully compensated. Example: pH = 7.54, PaCO2 = 23 If the history suggests an acute process, the equation for the expected change in pH is: Expected pH = 7.40 + (0.008 × [ΔPaCO2]) The calculated value, 7.54, is the same as the measured value, so this represents an acute respiratory alkalosis. If the pH were higher, a metabolic alkalosis would also be present. If the pH were lower, a metabolic acidosis would be present. STAGE 3: CHECK THE ANION GAP AND GAP–GAP TO EVALUATE METABOLIC ACIDOSIS

An anion gap (AG) acidosis may be accompanied by a normal AG acidosis or a metabolic alkalosis. This is called the gap–gap and is detected by examining the ratio: AG excess/HCO3 deficit = (AG-12)/(24-HCO3) If the increase in the AG due to added H+ is balanced by the decrease in HCO3, the ratio is 1, and only an AG acidosis exists. However, if a hyperchloremic acidosis also is present, the decrease in HCO3 will be greater than the increase in the AG, and the ratio will be 1. Interpretation of gap–gap: 2: Additional metabolic alkalosis, or perhaps a coexisting chronic respiratory acidosis, which has resulted in a compensatory elevation of HCO3

Table 22.9  Alveolar Gas Equation PAO2 = PiO2 − (PaCO2/R), where PiO2 = FiO2 (PB − PH2O) or using common values: PAO2 = (FiO2 × [760 − 47]) − (PaCO2/0.8) = 150 − PaCO2/0.8 Abbreviations: PiO2 = partial pressure of O2 in the central airways; FiO2 (fraction of inspired oxygen); FiO2 on room air = 0.21, PaCO2 (value from your arterial blood gas [ABG]); PB = barometric pressure (760 mm Hg at sea level, PB = PN2 + PO2 + PaCO2 + PH2O); PH2O = water vapor pressure (47 mm Hg at 37° C); R = respiratory quotient (ratio of carbon dioxide production to oxygen consumption) = VCO2/VO2 = 0.8 (usual).

hypoxemia, the A-a gradient is calculated. If it is normal, the low arterial oxygen tension (PaO2) is caused by hypoventilation. If it is increased, it may be the result of ventilationperfusion (V/Q) mismatching (PaO2 increases with application of 100% oxygen) or of shunting (PaO2 does not increase with

the application of 100% oxygen). The A-a gradient increases with age according to the following formula: Normal A-a gradient = (Age + 10) / 4.

Respiratory Acid-Base Disorders Acute Respiratory Acidosis Respiratory acidosis normally is buffered by an increase in HCO3−. In an acute respiratory acidosis, the HCO3 will increase by 1 mEq/L for each 10 mm Hg elevation in PaCO2 greater than 40 mm Hg. The expected HCO3 is described by the following equation: HCO3 = 24 + ([ΔPaCO2]/10) If the PaCO2 increases from 40 to 60 mm Hg, the HCO3 therefore will increase from 24 to 26 mm Hg. An increase

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greater than this suggests the concomitant presence of a metabolic alkalosis. The expected change in pH during this process is expressed by the following equation: Expected pH = 7.40 − (0.008 × [ ∆PaCO2 ]) Hence if the PaCO2 increases acutely from 40 to 60 mm Hg, the pH will decrease to 7.24 (7.40 − [0.008 × 20]).

Cerebral blood flow can be partially regulated by CO2induced changes in the pH. An alkalosis causes cerebral vasoconstriction and there may be a 40% decrease in cerebral blood flow with a decrease in the PaCO2 from 40 to 20 mm Hg. This technique to decrease intracranial pressure (ICP) is modulated by pH and not the PaCO2.

Chronic Respiratory Acidosis

Metabolic Acid-Base Disorders

In a chronic respiratory acidosis that develops over 2 to 3 days, the HCO3− will increase by 4 mEq/L for every 10 mm Hg change in PaCO2 described by the following equation:

The physiology underlying acid-base disorders is discussed below but the equations for compensation are summarized first. In metabolic disorders, compensation results in an elevated PaCO2 for a metabolic alkalosis and a lower PaCO2 in a metabolic acidosis. The expected changes can be calculated by the following equations: Metabolic alkalosis: Expected PaCO2 = (0.7 × HCO3) + 20 ± 5 Metabolic acidosis: Expected PaCO2 = (1.5 × HCO3) + 8 ± 2

Expected HCO3− = 24 + 4([ΔPaCO2]/10) If the PaCO2 increases from 40 to 60 mm Hg, the HCO3− will increase from 24 to 32 mm Hg. The pH is similarly affected, changing 0.003 unit for each 1 mm Hg change in PaCO2 according to the following equation: Expected pH = 7.40 − (0.003 × [ΔPaCO2]) In a patient who has chronic obstructive pulmonary disease (COPD) with a PaCO2 that equals 60 mm Hg, the expected pH is 7.34. In addition to the elevated HCO3−, there may also be a lower chloride level. As new HCO3− is generated in the collecting duct from hydrolysis, hydrogen is secreted into the tubular lumen. Na+ flows in to maintain electrical neutrality. This influx leaves less Na+ available to be resorbed with Cl− and so Cl− excretion is increased.

Acute Respiratory Alkalosis Respiratory alkalosis is buffered by a decrease in HCO3−. In an acute respiratory alkalosis the HCO3− decreases by 2 mEq/L for each 10 mm Hg decrease in PaCO2 less than 40 mm Hg according to the following equation: Expected HCO3− = 24 − 2(ΔPaCO2/10) If the PaCO2 decreases from 40 to 20 mm Hg, the HCO3 will decrease from 24 to 20 mm Hg. In practice, a HCO3− of less than 18 mEq/L indicates a coexisting metabolic acidosis. The expected change in pH during this process is expressed by the following equation: Expected pH = 7.40 + (0.008 × [ΔPaCO2]) If the PaCO2 acutely decreases from 40 to 15 mm Hg, the pH will rise to 7.56.

Chronic Respiratory Alkalosis In chronic respiratory alkalosis the HCO3− will decrease by 5  mEq/L for every 10  mm  Hg decrease in PaCO2 Described by the equation: Expected HCO3− = 24 − 5(ΔPaCO2/10) Thus if the PaCO2 decreases from 40 to 20 mmHg, the HCO3− will decrease from 24 to approximately 14 mm Hg. The HCO3 generally does not fall below 12 for compensation. The change in pH can be expressed by: Expected pH = 7.40 + (0.003 × [ΔPaCO2])

Metabolic Alkalosis Metabolic alkalosis can result from nasogastric (NG) suctioning or diuretics from the loss of chloride. For every molecule of Cl− that is excreted, one molecule of HCO3− is reabsorbed. Though there is a loss of both H+ and Cl−, it is chloride depletion, stimulating HCO3− reabsorption, which is the major contributing factor to the alkalosis. Thiazide and loop diuretics promote natriuresis and Cl− is excreted with the sodium. Additionally, volume depletion promotes metabolic alkalosis in two ways. The increase in Na+ resorption is accompanied by an increase in bicarbonate reabsorption. Volume depletion also stimulates renin, promoting the formation of aldosterone, which causes H+ excretion in the distal tubules. Volume resuscitation is not effective in reversing the alkalosis unless Cl− is also replaced. Hypokalemia is associated with alkalosis and a shift of H+ into the cells and an increase in H+ secretion in the distal tubules. Aldosterone and other mineralocorticoids act on the collecting tubule to stimulate the resorption of Na+, accompanied by the excretion of H+ and K+, which gives rise to hypokalemia, hypertension, and hypernatremia. Metabolic alkalosis also may result from the administration of exogenous HCO3 such as HCO3 infusions, from acetate in TPN, or from the administration of antacids in renal failure. Citrate in banked blood may produce a metabolic alkalosis, but a minimum of 8 units must be transfused. Clinically, metabolic alkalosis can be divided into two categories: (1) saline-responsive, associated with volume depletion; and (2) saline-resistant, associated with excess mineralocorticoid activity. In saline-responsive metabolic alkalosis, volume depletion stimulates the resorption of Na+ that also causes the retention of Cl− and HCO3−. However, some extra HCO3− is excreted with Na+ to maintain electrical neutrality, so a urinary Cl− less than 20 mEq/L is a better indicator of volume depletion in metabolic alkalosis.

Anion Gap A normal anion-gap acidosis occurs because the lost HCO3− is replaced by a Cl−. Causes for this are listed in Table 22.10. The anion gap (AG) is defined as:

Section II—Clinical and Laboratory Assessment



Table 22.10  Causes for Normal Anion-Gap Acidosis • Gastrointestinal loss—secretions from below the stomach are rich in bicarbonate because they neutralize the acid from the stomach. • Renal loss of HCO3−—proximal RTA • Early renal failure of a distal RTA • Ingestions—HCO3−—acetate in TPN • Carbonic anhydrase inhibitors—acetazolamide • Recovery of ketoacidosis when given normal saline RTA, Renal tubular acidosis; TPN, total parenteral nutrition.

Table 22.11  Causes of an AnionGap Acidosis Propylene glycol Lactic acidosis Uremia Methanol Salicylate

Ethanol Ethylene glycol Diabetic ketoacidosis (DKA) Starvation Isoniazid

AG = Na+ − (Cl− + HCO3−) An anion gap exists because there are anions such as sulfate, phosphate, organic anions, and proteins that are not measured on the routine chemistry panel, where there are very few unmeasured cations. The normal AG is between 7 and 13 mEq/L, but newer autoanalyzers report a higher Cl−, so the normal may be between 3 and 11 mEq/L. Hypoalbuminemia may spuriously lower the AG and mask an underlying aniongap acidosis. Causes of an anion-gap acidosis are listed in Table 22.11 and each is briefly described.

Propylene Glycol Propylene glycol is an alcohol used to increase the water solubility of lorazepam, diazepam, esmolol, nitroglycerin, and phenytoin, and it is metabolized in the liver to lactate and pyruvate. Signs of toxicity are agitation, seizures, coma, tachycardia, and hypotension. The lactate may exceed 10 mEq/L and clinically mimic sepsis.

Lactic Acidosis A normal AG may accompany lactic acidosis. Iberti et al. observed that 50% of patients with a lactate level between 5 and 9.9 mmol/L had AG less than 12 mEq/L.84 Lactic acidosis results from mitochondrial dysfunction and has three forms. (1) Type A arises from tissue hypoxia—septic, cardiogenic, or hemorrhagic shock, or respiratory failure. (2) Type B is caused by impaired mitochondrial oxygen utilization, such as from toxins; that is, there is no systemic hypoperfusion. These toxins can include: metformin (Glucophage); cyanide poisoning, for example, a nitroprusside infusion; thiamine (B1) deficiency that can be associated with loss of body stores, increased excretion by furosemide (Lasix), or magnesium depletion that results in a functional form of thiamine deficiency; malignancies, alcoholism, or AZT (zidovudine). (3) Type D occurs in patients with jejunoileal bypass or in patients with short bowel syndrome. The shortened small intestine is unable to

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absorb dietary sugar, leaving carbohydrates to be metabolized by bacteria in the colon. Lactobacilli metabolism of carbohydrate produces D lactic acid. It presents with neurologic changes (confusion, ataxia, slurred speech, memory loss) simulating intoxication without alcohol ingestion after a highcarbohydrate meal.

Ketoacidosis Glucose and ketones are the two fuels available for the body. In the fed state, glucose is the primary fuel source; ketones assume this role in the fasting state. Ketones are produced in the liver from triglycerides, and there are three types: (1) B-hydroxybutyrate, the predominant ketone of diabetic ketoacidosis (DKA) and alcoholic ketoacidosis (AKA), but not measured by the standard urine assay; (2) acetoacetate, measured by the lab, but accounts for only 25% or less of the total ketone load; and (3) acetone, which does not cause an acidosis. Ketoacidosis becomes clinically significant when insulin activity is reduced in the following conditions: (1) DKA, the body is unable to produce or release insulin; (2) AKA, alcohol induces lipolysis (increases the supply of fatty acids for ketone production) and consumes nicotinamide adenine dinucleotide (NAD+) (decreasing gluconeogenesis, forcing the liver to produce ketones); and (3) starvation-insulin release is suppressed. In AKA and starvation ketoacidosis, the treatment is glucose, which stimulates endogenous insulin production to suppress ketogenesis. In DKA are insulin deficiency, hyperglycemia, ketosis (causing AG), and hyponatremia (often pseudohyponatremia), and treatment with insulin and fluids is needed. Hyperglycemic hyperosmolar nonketotic (HHNK) coma is seen in people with type 2 diabetes and is characterized by extremely high blood sugar (≈1000 mg/dL) but without ketosis (or acidosis) because insulin is present. The primary treatment is volume replacement. Uremia causes an anion gap acidosis from an impaired ability to clear the daily acid load of daily metabolism, but the GFR is usually less than 40 mL/ min before this occurs.

Alcohols The metabolites of alcohols, generated by alcohol and aldehyde dehydrogenase are responsible for the toxicity associated with alcohol ingestion. Thus it can take 12 to 24 hours for acidosis and organ failure to occur, and this may be delayed further when there also is ethanol ingestion. Consequently, management is to prevent metabolite formation until the parent compound can be excreted or dialyzed. Methanol and ethylene glycol intoxication present with a high anion gap acidosis, but the measurements of these may be off-site and will not be available to assist immediate clinical decision making. The osmolal gap defined as the difference between the calculated osmolality (osmolality = 2 × Na+[mmol/L] + BUN [mg/dL]/2.8 + [glucose mg/dL]/18) and the measured osmolality may help clinical decisions. The normal osmolal gap is 10 mOsm/kg H2O or less. Causes of an elevated osmolal gap are listed in Table 22.12. As one integrates the history and laboratory findings, it is important to remember that the alcohols contribute to the osmolal gap and the toxic metabolites contribute to the acidosis. Thus toxicity is not excluded on a gap less than

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Table 22.12  Causes of an Elevated Osmolal Gap with an Anion-Gap Acidosis Ethylene glycol Methanol Formaldehyde ESRD without dialysis Paraldehyde DKA AKA Lactic acidosis

Elevated osmolal gap without acidosis Ethanol Isopropanol Diethyl ether Mannitol Severe hyperproteinemia Severe hyperlipidemia

AKA, Alcoholic ketoacidosis; DKA, diabetic ketoacidosis; ESRD, end-stage renal disease.

10 mOsm/kg. A small elevation isn’t necessarily from a toxic metabolite, but a gap greater than 25 is presumptive evidence in the appropriate setting. 100 mg/dL of ethanol (MW = 46) adds 22 mOsm/kg. Isopropyl alcohol does not cause an acidosis, but its primary metabolite, acetone, manifests by positive serum and urinary ketones.

Methanol Methanol poisoning occurs with the ingestion of shellac, varnish, wiper fluids and deicing solutions, or denatured gelled alcohol (Sterno). It is converted by alcohol dehydrogenase into the toxic formaldehyde and then formic acid.

A

B

C

D

Fig. 22.13  Brain MRI obtained on day 15 after methanol intoxication. A, T2-weighted image showed high signal abnormalities in bilateral basal ganglia (arrows), frontal, and occipital subcortical white matter (arrowheads), consistent with edematous change. B, T2-weighted image showed edematous change involving bilateral optic tracts and optic radiations (arrows). High signal edematous change was also noted in the optic disc of the left eye (arrowheads). C, T1-weighted image showed slightly high signal component in bilateral basal ganglia, indicating the hemorrhage (arrows). D, T1-weighted image with gadolinium administration showed marginal enhancement in bilateral putamen, indicating breakdown of the blood-brain barrier.

Section II—Clinical and Laboratory Assessment

Malaise, nausea, and headache occur within 12 to 24 hours of ingestion, followed by acidosis, visual disturbances (formaldehyde’s retinal toxicity), seizures, and coma. Serious toxicity occurs with one teaspoon—50 mL may be lethal. Optic nerve edema and basal ganglia infarcts can be observed (Fig. 22.13).

Ethylene Glycol Ethylene glycol is found in antifreeze and solvents, and ingestion manifests initially by neurologic symptoms, including cranial nerve palsies and tetany (from oxalate-induced hypocalcemia) and later by pulmonary edema. Renal failure is a late finding due to the effects of oxalate crystals. Lactic acidosis can be seen with ethylene glycol, but it is insufficient to account for the degree of acidosis.

Treatment of Alcohol or Methanol Toxicity For each of these disorders time is crucial, and important decisions may need to be made without all the data. Therapy includes sodium bicarbonate and fomepizole. Fomepizole (or ethanol) inhibits alcohol dehydrogenase and blocks metabolite production, but early treatment is crucial because it does not prevent toxicity if metabolism to an acid species has already occurred. It is useful for both methanol and ethylene glycol poisoning. Hemodialysis should be used if metabolic acidosis is present or there is evidence of end-organ damage. All methanol intoxications should also receive cofactor therapy: either folinic acid (50 mg IV) or folic acid (50 mg every 6 hours IV) and probably thiamine (100 mg IV).

Salicylate Aspirin overdose is characterized by the accumulation of salicylic acid, the active metabolite of acetylsalicylic acid toxicity is characterized by two primary acid-base disorders. Respiratory alkalosis initially ensues from direct CNS stimulation and is followed by a metabolic acidosis. Salicylic acid itself contributes little to the anion gap (due to its high molecular weight), but the anion gap results from the buildup of lactic acid and ketones by unclear mechanisms. The treatment is alkalinization of the urine. Increasing the pH from 7.2 to 7.5 halves the tissue level of salicylic acid. Dialysis is indicated for patients in coma or with levels 80 mg/dL or greater.

Conclusion Electrolyte and acid-base abnormalities and acute and chronic kidney injury are ubiquitous in neurocritical care. An understanding of basic renal physiology assists in providing a framework for understanding these disorders and a context for their management.

References 1. Piccinni P, Cruz DN, Gramaticopolo S, et al. Prospective multicenter study on epidemiology of acute kidney injury in the ICU: a critical care nephrology Italian collaborative effort (NEFROINT). Minerva Anestesiol 2011;77(11):1072–83. Epub 2011, May 11. 2. Clec’h C, Gonzalez F, Lautrette A, et al. Multiple-center evaluation of mortality associated with acute kidney injury in critically ill patients: a competing risks analysis. Crit Care 2011;15(3):R128. Epub 2011, May 17.

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3. Bellomo R. Acute renal failure. Semin Respir Crit Care Med 2011;32(5):639– 50. Epub 2011, Oct 11. 4. Mandelbaum T, Scott DJ, Lee J, et al. Outcome of critically ill patients with acute kidney injury using the Acute Kidney Injury Network criteria. Crit Care Med 2011;39(12):2659–64. 5. Li N, Zhao WG, Zhang WF. Acute kidney injury in patients with severe traumatic brain injury: implementation of the acute kidney injury network stage system. Neurocrit Care 2011;14(3):377–81. 6. Rose BD, Post TW. Introduction to renal function. Available at www.upto date.com (accessed August 2009). 7. Rose BD, Post TW. Collecting tubules. Available at www.uptodate.com (accessed August 2009). 8. Rose BD. Urine osmolality versus specific gravity. Available at www.uptodate .com (accessed August 2009). 9. Pasticci F, Fantuzzi AL, Pegoraro M, et al. Nutritional management of stage 5 chronic kidney disease. J Ren Care 2012;38(1):50–8. 10. Patel P, Nandwani V, McCarthy PJ, et al. Continuous renal replacement therapies: a brief primer for the neurointensivist. Neurocrit Care 2010;13(2): 286–94. 11. Arulkumaran N, Montero RM, Singer M. Management of the dialysis patient in general intensive care. Br J Anaesth 2012;108(2):183–92. Epub 2012, Jan 4. 12. Basu RK, Wheeler DS, Goldstein S, et al. Acute renal replacement therapy in pediatrics. Int J Nephrol 2011;2011:785392. Epub 2011, Jun 1. 13. Chuasuwan A, Kellum JA. Acute kidney injury and its management. Contrib Nephrol 2011;171:218–25. Epub 2011, May 23. 14. Claure-Del Granado R, Mehta RL. Withholding and withdrawing renal support in acute kidney injury. Semin Dial 2011;24(2):208–14. doi:10.1111/ j.1525-139X.2011.00832.x. 15. Srisawat N, Kellum JA. Acute kidney injury: definition, epidemiology, and outcome. Curr Opin Crit Care 2011;17(6):548–55. 16. Singbartl K, Kellum JA. AKI in the ICU: definition, epidemiology, risk stratification, and outcomes. Kidney Int 2011;Oct 5. Epub ahead of print. 17. Liano F, Pascual J. Madrid Acute Renal Failure Study Group. Epidemiology of acute renal failure: a prospective, multicenter, community-based study. Kidney Int 1996;50:811. 18. Mehta RL, Pascual MT, Soroko S, et al. Spectrum of acute renal failure in the intensive care unit: the 1 PICARD experience. Kidney Int 2004;66:1613. 19. Muther RS. Acute renal failure in the critically ill. In: ACCP, editor. ACCP Critical Care Board Review 2007: Course Syllabus. Northbrook, Ill: American College of Chest Physicians; 2007. 20. Bellomo R, Ronco C, Kellum JA, et al. Acute renal failure-definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative ADQI. Group Crit Care 2004;8:R204–12. 21. Chertow GM, Burick E, Honour M, et al. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol 2005; 16:3365–70. 22. Palevsky PM. Definition of acute kidney injury (acute renal failure). Available at www.uptodate.com (accessed August 2009). 23. Waring WS, Moonie A. Earlier recognition of nephrotoxicity using novel biomarkers of acute kidney injury. Clin Toxicol (Phila) 2011;49(8): 720–8. 24. Payen D, Legrand M. Can we identify prerenal physiology and does it matter? Contrib Nephrol 2011;174:22–32. Epub 2011, Sep 9. 25. Srisawat N, Wen X, Lee M, et al. Urinary biomarkers and renal recovery in critically ill patients with renal support. Clin J Am Soc Nephrol 2011;6(8):1815–23. Epub 2011, Jul 14. 26. Doi K, Negishi K, Ishizu T, et al. Evaluation of new acute kidney injury biomarkers in a mixed intensive care unit. Crit Care Med 2011;39(11): 2464–9. 27. Panagiotou A, Garzotto F, Gramaticopolo S, et al. Continuous real-time urine output monitoring for early detection of acute kidney injury. Contrib Nephrol 2011;171:194–200. Epub 2011, May 23. 28. Bellomo R. Defining, quantifying, and classifying acute renal failure. Crit Care Clin 2005;21:223–7. 29. Muther RS. Drug interference with renal function tests. Am J Kidney Dis 1983;3:118–20. 30. Kaplan AA, Kohn OF. Fractional excretion of urea as a guide to renal dysfunction. Am J Nephrol 1992:12:54–9. 31. Post TW, Rose BD. Urinalysis in the diagnosis of renal disease. Available at www.uptodate.com (accessed August 2009). 32. Bohle A, Christensen J, Kokot F, et al. Acute renal failure in man: new aspects concerning pathogenesis. A morphometric study. Am J Nephrol 1990;10: 374–88. 33. Lameire N, Vanholder R, Van Biesen W. Loop diuretics for patients with acute renal failure: helpful or harmful. JAMA 2002;288:2599.

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34. Cantarovich F, Rangoonwala B, Lorenz H, et al. High-dose furosemide for established ARF: a prospective, randomized, double-blind, placebocontrolled, multicenter trial. Am J Kidney Dis 2004;44:402. 35. Delpire E, Lu J, England R, et al. Deafness and imbalance associated with inactivation of the secretory Na-K-2Cl co-transporter. Nat Genet 1999; 22:192. 36. Marik PE, Iglesias J. Low-dose dopamine does not prevent acute renal failure in patients with septic shock and oliguria. NORASEPT II Study Investigators. Am J Med 1999;107:387–90. 37. Bellomo R, Chapman M, Finfer S, et al. Low-dose dopamine in patients with early renal dysfunction: a placebo-controlled randomized trial. Lancet 2000;356:2139. 38. Lauschke A, Teichgraber UK, Frei U, et al. Low-dose dopamine worsens renal perfusion in patients with acute renal failure. Kidney Int 2006;69: 1669. 39. Reid GM, Muther RS. Nitroprusside-induced acute azotemia. Am J Nephrol 1987;7:313–15. 40. Rose B, Appel GB. Clinical manifestations and diagnosis of acute interstitial nephritis. Available at www.uptodate.com (accessed August 2009). 41. Hecker R, Sherlock S. Electrolyte and circulatory changes in terminal liver failure. Lancet 1956;2:1221–5. 42. Koppel MH, Coburn JN, Mims MM, et al. Transplantation of cadaveric kidneys from patients with hepatorenal syndrome. Evidence for the functional nature of renal failure in advanced liver disease. N Engl J Med 1969;280:1267–71.

43. Iwatsuke S, Popovtzer MM, Corman JI, et al. Recovery from hepatorenal syndrome after orthotopic liver transplantation. N Engl J Med 1973;289: 1155–9. 44. Arroyo V, Gines P, Gerbes AL, et al. Definition and diagnostic criteria of refractory ascites and hepatorenal syndrome in cirrhosis. Int Ascites Club Hepatol 1996;23:164. 45. Watt K, Uhanova J, Minuk GY. Hepatorenal syndrome: diagnostic accuracy, clinical features, and outcome in a tertiary care centre. Am J Gastroenterol 2002;97:2046–50. 46. Esrailian E, Pantangco ER, Kyulo NL, et al. Octreotide/Midodrine therapy significantly improves renal function and 30-day survival in patients with type 1 hepatorenal syndrome: a large retrospective series. Dig Dis Sci 2007;52:742. 47. Uriz J, Gines P, Cardenas A, et al. Terlipressin plus albumin infusion: an effective and safe therapy of hepatorenal syndrome. J Hepatol 2000;22:43–8. 48. Wong F, Pantea L, Sniderman K. Midodrine, octreotide, albumin, and TIPS in selected patients with cirrhosis and type 1 hepatorenal syndrome. Hepatology 2004;40:55–64. 49. Olson JC, Wendon JA, Kramer DJ, et al. Intensive care of the patient with cirrhosis. Hepatology 2011;54(5):1864–72. doi:10.1002/hep.24622. 50. McCarthy JT. Prognosis of patients with acute renal failure in the intensive care unit: a tale of two eras. Mayo Clin Proc 1996;7:117–26. A complete list of references for this chapter can be found online at www.expertconsult.com.



References 1. Piccinni P, Cruz DN, Gramaticopolo S, et al. Prospective multicenter study on epidemiology of acute kidney injury in the ICU: a critical care nephrology Italian collaborative effort (NEFROINT). Minerva Anestesiol 2011;77(11):1072–83. Epub 2011, May 11. 2. Clec’h C, Gonzalez F, Lautrette A, et al. Multiple-center evaluation of mortality associated with acute kidney injury in critically ill patients: a competing risks analysis. Crit Care 2011;15(3):R128. Epub 2011, May 17. 3. Bellomo R. Acute renal failure. Semin Respir Crit Care Med 2011;32(5):639– 50. Epub 2011, Oct 11. 4. Mandelbaum T, Scott DJ, Lee J, et al. Outcome of critically ill patients with acute kidney injury using the Acute Kidney Injury Network criteria. Crit Care Med 2011;39(12):2659–64. 5. Li N, Zhao WG, Zhang WF. Acute kidney injury in patients with severe traumatic brain injury: implementation of the acute kidney injury network stage system. Neurocrit Care 2011;14(3):377–81. 6. Rose BD, Post TW. Introduction to renal function. Available at www.uptodate.com (accessed August 2009). 7. Rose BD, Post TW. Collecting tubules. Available at www.uptodate.com (accessed August 2009). 8. Rose BD. Urine osmolality versus specific gravity. Available at www.uptodate. com (accessed August 2009). 9. Pasticci F, Fantuzzi AL, Pegoraro M, et al. Nutritional management of stage 5 chronic kidney disease. J Ren Care 2012;38(1):50–8. 10. Patel P, Nandwani V, McCarthy PJ, et al. Continuous renal replacement therapies: a brief primer for the neurointensivist. Neurocrit Care 2010;13(2):286–94. 11. Arulkumaran N, Montero RM, Singer M. Management of the dialysis patient in general intensive care. Br J Anaesth 2012;108(2):183–92. Epub 2012, Jan 4. 12. Basu RK, Wheeler DS, Goldstein S, et al. Acute renal replacement therapy in pediatrics. Int J Nephrol 2011;2011:785392. Epub 2011, Jun 1. 13. Chuasuwan A, Kellum JA. Acute kidney injury and its management. Contrib Nephrol 2011;171:218–25. Epub 2011, May 23. 14. Claure-Del Granado R, Mehta RL. Withholding and withdrawing renal support in acute kidney injury. Semin Dial 2011;24(2):208–14. doi:10.1111/j .1525-139X.2011.00832.x. 15. Srisawat N, Kellum JA. Acute kidney injury: definition, epidemiology, and outcome. Curr Opin Crit Care 2011;17(6):548–55. 16. Singbartl K, Kellum JA. AKI in the ICU: definition, epidemiology, risk stratification, and outcomes. Kidney Int 2011;Oct 5. Epub ahead of print. 17. Liano F, Pascual J, Madrid Acute Renal Failure Study Group. Epidemiology of acute renal failure: a prospective, multicenter, community-based study. Kidney Int 1996;50:811. 18. Mehta RL, Pascual MT, Soroko S, et al. Spectrum of acute renal failure in the intensive care unit: the 1 PICARD experience. Kidney Int 2004;66:1613. 19. Muther RS. Acute renal failure in the critically ill. In: ACCP, editor. ACCP Critical Care Board Review 2007: Course Syllabus. Northbrook, Ill: American College of Chest Physicians; 2007. 20. Bellomo R, Ronco C, Kellum JA, et al. Acute renal failure-definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative ADQI. Group Crit Care 2004;8:R204–12. 21. Chertow GM, Burick E, Honour M, et al. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol 2005; 16:3365–70. 22. Palevsky PM. Definition of acute kidney injury (acute renal failure). Available at www.uptodate.com (accessed August 2009). 23. Waring WS, Moonie A. Earlier recognition of nephrotoxicity using novel biomarkers of acute kidney injury. Clin Toxicol (Phila) 2011;49(8):720–8. 24. Payen D, Legrand M. Can we identify prerenal physiology and does it matter? Contrib Nephrol 2011;174:22–32. Epub 2011, Sep 9. 25. Srisawat N, Wen X, Lee M, et al. Urinary biomarkers and renal recovery in critically ill patients with renal support. Clin J Am Soc Nephrol 2011;6(8): 1815–23. Epub 2011, Jul 14. 26. Doi K, Negishi K, Ishizu T, et al. Evaluation of new acute kidney injury biomarkers in a mixed intensive care unit. Crit Care Med 2011;39(11):2464–9. 27. Panagiotou A, Garzotto F, Gramaticopolo S, et al. Continuous real-time urine output monitoring for early detection of acute kidney injury. Contrib Nephrol 2011;171:194–200. Epub 2011, May 23. 28. Bellomo R. Defining, quantifying, and classifying acute renal failure. Crit Care Clin 2005;21:223–7. 29. Muther RS. Drug interference with renal function tests. Am J Kidney Dis 1983;3:118–20. 30. Kaplan AA, Kohn OF. Fractional excretion of urea as a guide to renal dysfunction. Am J Nephrol 1992:12:54–9.

Section II—Clinical and Laboratory Assessment 226.e1 31. Post TW, Rose BD. Urinalysis in the diagnosis of renal disease. Available at www.uptodate.com (accessed August 2009). 32. Bohle A, Christensen J, Kokot F, et al. Acute renal failure in man: new aspects concerning pathogenesis. A morphometric study. Am J Nephrol 1990;10: 374–88. 33. Lameire N, Vanholder R, Van Biesen W. Loop diuretics for patients with acute renal failure: helpful or harmful. JAMA 2002;288:2599. 34. Cantarovich F, Rangoonwala B, Lorenz H, et al. High-dose furosemide for established ARF: a prospective, randomized, double-blind, placebocontrolled, multicenter trial. Am J Kidney Dis 2004;44:402. 35. Delpire E, Lu J, England R et al. Deafness and imbalance associated with inactivation of the secretory Na-K-2Cl co-transporter. Nat Genet 1999; 22:192. 36. Marik PE, Iglesias J. Low-dose dopamine does not prevent acute renal failure in patients with septic shock and oliguria. NORASEPT II Study Investigators. Am J Med 1999;107:387–90. 37. Bellomo R, Chapman M, Finfer S, et al. Low-dose dopamine in patients with early renal dysfunction: a placebo-controlled randomized trial. Lancet 2000;356:2139. 38. Lauschke A, Teichgraber UK, Frei U, et al. Low-dose dopamine worsens renal perfusion in patients with acute renal failure. Kidney Int 2006;69:1669. 39. Reid GM, Muther RS. Nitroprusside-induced acute azotemia. Am J Nephrol 1987;7:313–15. 40. Rose B, Appel GB. Clinical manifestations and diagnosis of acute interstitial nephritis. Available at www.uptodate.com (accessed August 2009). 41. Hecker R, Sherlock S. Electrolyte and circulatory changes in terminal liver failure. Lancet 1956;2:1221–5. 42. Koppel MH, Coburn JN, Mims MM, et al. Transplantation of cadaveric kidneys from patients with hepatorenal syndrome. Evidence for the functional nature of renal failure in advanced liver disease. N Engl J Med 1969;280:1267–71. 43. Iwatsuke S, Popovtzer MM, Corman JI, et al. Recovery from hepatorenal syndrome after orthotopic liver transplantation. N Engl J Med 1973;289: 1155–9. 44. Arroyo V, Gines P, Gerbes AL, et al. Definition and diagnostic criteria of refractory ascites and hepatorenal syndrome in cirrhosis. Int Ascites Club Hepatol 1996;23:164. 45. Watt K, Uhanova J, Minuk GY. Hepatorenal syndrome: diagnostic accuracy, clinical features, and outcome in a tertiary care centre. Am J Gastroenterol 2002;97:2046–50. 46. Esrailian E, Pantangco ER, Kyulo NL, et al. Octreotide/midodrine therapy significantly improves renal function and 30-day survival in patients with type 1 hepatorenal syndrome: a large retrospective series. Dig Dis Sci 2007;52:742. 47. Uriz J, Gines P, Cardenas A, et al. Terlipressin plus albumin infusion: an effective and safe therapy of hepatorenal syndrome. J Hepatol 2000;22: 43–8. 48. Wong F, Pantea L, Sniderman K. Midodrine, octreotide, albumin, and TIPS in selected patients with cirrhosis and type 1 hepatorenal syndrome. Hepatology 2004;40:55–64. 49. Olson JC, Wendon JA, Kramer DJ, et al. Intensive care of the patient with cirrhosis. Hepatology 2011;54(5):1864–72. doi:10.1002/hep.24622. 50. McCarthy JT. Prognosis of patients with acute renal failure in the intensive care unit: a tale of two eras. Mayo Clin Proc 1996;7:117–26. 51. Richards WO, Scovill W, Shin B, et al. Acute renal failure associate with increased intra-abdominal pressure. Ann Surg 1983;197:183. 52. Mohmand H, Goldfarb S. Renal dysfunction associated with intraabdominal hypertension and the abdominal compartment syndrome. J Am Soc Nephrol 2011;22(4):615–21. Epub 2011, Feb 10. 53. Oates JA, Fitzgerald GA, Branch RA, et al. Clinical implication of prostaglandin and thromboxane A2 formation. N Engl J Med 1988;319:761. 54. Huerta C, Castellsague J, Baras-Lorenzo C, et al. Nonsteroidal antiinflammatory drugs and risk of ARF in the general population. Am J Kidney Dis 2005;45:531. 55. Patrono C, Dunn MJ. The clinical significance of inhibition of renal prostaglandin synthesis. Kidney Int 1987;32:1. 56. Clive DM, Stoff JS. Renal syndromes associated with nonsteroidal anti-inflammatory drugs. N Engl J Med 1984;310:563. 57. Radford MG, Holley KE, Grande JP, et al. Reversible membranous nephropathy associated with the use of nonsteroidal anti-inflammatory drugs. JAMA 1996;276:466. 58. Kaysen GA, Pond SM, Roper MH, et al. Combined hepatic and renal injury in alcoholics during therapeutic use of acetaminophen. Arch Intern Med 1985;145:2019–23. 59. Blakely P, McDonald BR. Acute renal failure de to acetaminophen ingestion: A case report and review of the literature. J Am Soc Nephrol 1995;6:48.

226.e2 Section II—Clinical and Laboratory Assessment 60. Weisbord SD, Palevsky PM. Radiocontrast-induced acute renal failure. J Intensive Care Med 2005;20:63. 61. Lakhal K, Ehrmann S, Chaari A, et al. Acute Kidney Injury Network definition of contrast-induced nephropathy in the critically ill: incidence and outcome. J Crit Care 2011;26(6):593–9. Epub 2011, Jul 6. 62. Agmon Y, Peleg H, Greenfield A, et al. Nitric oxide and prostanoids protect the renal outer medulla from radiocontrast toxicity in the rat. J Clin Invest 1994;94:1069. 63. Morcos DK, El-Nahas AM, Broen P, et al. Effect of iodinated water soluble contrast media on urinary protein assays. BMJ 1992;305:29. 64. Tepel M, van der Giet M, Schwarzfeld C, et al. Prevention of radiographiccontrast-agent-induces reductions in renal function by acetylcysteine. N Engl J Med 2000;343:180–4. 65. Boton R, Gaviria M, Batlle DC. Prevalence, pathogenesis, and treatment of renal dysfunction associated with chronic lithium therapy. Am J Kidney Dis 1987;10:329. 66. Lehmann K, Ritz E. Angiotensin-converting enzyme inhibitors may cause renal dysfunction in patients on long-term lithium treatment. Am J Kidney Dis 1995;25:82. 67. Kaplan NM, Rose BD. Major side effects of ACI inhibitors. Available at www.uptodate.com (accessed August 2009). 68. Miskulin D, Gul A, Rudnick MR, et al. Nephrogenic systemic fibrosis/ nephrogenic fibrosing dermopathy in advanced renal failure. Available at www.uptodate.com (accessed August 2009). 69. Haas M, Ohler L, Watzke H, et al. The spectrum of acute renal failure in tumor lysis syndrome. Nephrol Dial Transplant 1999;13:776–9. 70. Fernandez PC, Larson RA, Agus ZS. Tumor lysis syndrome. Available at www.uptodate.com (accessed August 2009). 71. Gabow PA, Kaehny WD, Kelleher SP. The spectrum of rhabdomyolysis. Medicine (Baltimore) 1982;61:141. 72. Miller ML. Rhabdomyolysis. Available at www.uptodate.com (accessed August 2009). 73. Rose BD. Clinical features and prevention of heme pigment-induced acute tubular necrosis. Available at www.uptodate.com (accessed August 2009).

74. August P, George JN. Acute renal failure in pregnancy. www.uptodate. com (accessed August 2009). 75. Poole BD, Schrier RW. Acute renal failure. In Fink MP, Abraham E, et al. Textbook of critical care, ed 5. Elsevier, New York, 2005, p. 1139–50. 76. Rose BD. Urine output in urinary tract obstruction and postobstructive diuresis. Available at www.uptodate.com (accessed August 2009). 77. Negash DT, Dhingra VK, Copland M, et al. Intensity of continuous renal replacement therapy in acute kidney injury in the intensive care unit: a systematic review and meta-analysis. Vasc Endovascular Surg 2011;45(6):504–10. Epub 2011, Jun 5. 78. Graham P, Lischer E. Nursing issues in renal replacement therapy: organization, manpower assessment, competency evaluation and quality improvement processes. Semin Dial 2011;24(2):183–7. doi:10.1111/j.1525139X.2011.00835.x. 79. Prowle JR, Schneider A, Bellomo R. Clinical review: optimal dose of continuous renal replacement therapy in acute kidney injury. Crit Care 2011;15(2):207. Epub 2011, Mar 18. 80. Lines SW, Cherukuri A, Murdoch SD, et al. The outcomes of critically ill patients with acute kidney injury receiving renal replacement therapy. Int J Artif Organs 2011;34(1):2–9. 81. Barri YM, Golper TA, Seizures in patients undergoing hemodialysis. Available at www.uptodate.com (accessed August 2009). 82. Marino PL. The ICU book. 3rd ed. Lippincott Williams & Wilkins, Philadelphia, 2007. 83. Gauthier PM, Szerlip HM. Metabolic acidosis in the intensive care unit. Critical care clinics. Crit Care Clin 2002;18(2):289–308. 84. Iberti TJ, Leibowitz AB, Papadakos PJ. Low sensitivity of the anion gap as a screen to detect hyperlactatemia in critically ill patients. Crit Care Med 1990;18:275–7. 85. Trotman RL, Williamson JC, Shoemaker DM, Salzer WL. Antibiotic dosing in critically ill adult patients receiving continuous renal replacement therapy. Clin Infect Dis 2005;41(8):1159–66.

Chapter

23

 

II

Gastrointestinal and Hepatic Disorders Christiana E. Hall and Aashish R. Patel

Introduction Gastrointestinal (GI) issues and maladies and in particular GI bleeding, liver dysfunction, and pancreatitis can complicate the primary course of critically ill neurologic patients. In addition, patients with hepatic encephalopathy may be cared for in the neurocritical care unit (NCCU). The neurointensivist therefore must be prepared to recognize, coordinate specialty care, and provide local monitoring and support when these issues arise. This chapter reviews disorders of the GI system including the liver and pancreas that are of importance in the NCCU. A comprehensive review of GI and hepatic function is beyond the scope of this chapter. Nutrition is reviewed in Chapter 14.

Gastrointestinal Bleeding GI bleeding is relatively common in acutely ill hospitalized patients, and the risk may be augmented in the NCCU associated with severe sympathetic stress such as in acute subarachnoid hemorrhage (SAH) or neurotrauma patients, including both traumatic brain injury (TBI) and spinal cord injury (SCI) and in patients in whom steroids are administered. The bleeding source may be from the upper or lower GI tract. The ligament of Treitz is the landmark that distinguishes the upper from lower GI tract. Common causes for upper GI bleeding (UGIB) are peptic ulcer disease, including stress-induced ulcer bleeding,1 variceal hemorrhage, and esophagitis. Common causes for lower GI bleeding (LGIB) are diverticulitis, angiodysplasia, colitis that can have several causes, tumors, and local anorectal pathologies. UGIB presents with hematemesis, melena, hematochezia, and occasionally hypotension when more severe. In patients with a nasogastric tube in place, the bleeding may manifest in the drainage contents (e.g., coffeeground gastric contents). LGIB presents with hematochezia and melena, and can be a reason for anemia. When GI bleeding occurs the initial focus is to ensure hemodynamic stability with resuscitation using crystalloid or blood products as appropriate. Patient monitoring therefore is aimed at recognition and avoidance of hemorrhagic shock using reliable real-time continuous blood pressure and heart rate monitoring. In more severe GI bleeding, resuscitation can be facilitated using central venous pressure (CVP), mixed venous oxygen saturation (ScvO2), and newer noninvasive © Copyright 2013 Elsevier Inc. All rights reserved.

hemodynamic monitoring techniques.2 These noninvasive devices can provide data on cardiac performance, preload, and systemic vascular resistance, similar to that provided by SwanGanz catheterization (see Chapter 19). Laboratory assessment includes hemoglobin and hematocrit, and to exclude an occult bleeding diathesis platelet count, coagulation indices, and if necessary disseminated intravascular coagulation (DIC). The brain contains high levels of tissue factor (TF), and in severe injury or associated with a prolonged or complex surgery (e.g., for a large arteriovenous malformation [AVM]), significant TF release may occur and induce the DIC cascade. The optimal platelet count after an injury to or a disease of the nervous system may depend on pathology and time after the initial insult. There is general agreement that a platelet count greater than 100,000 is a reasonable goal after TBI, after neurosurgery, or for anticipated intervention or instrumentation of the central nervous system (CNS). This includes for placement of an intracranial monitor or external ventricular drain. By contrast for other patients without CNS disorders or likely surgery, a platelet count greater than 50,000 is reasonable perhaps even when there is GI bleeding. For the neurointensivist this means that platelet support may differ depending on whether GI bleeding occurs in a patient with a disorder such as myasthenia gravis or severe TBI or is a postoperative neurosurgical patient. The various laboratory indices should be repeated at intervals until they are stabilized. This typically includes assessment of complete blood count with platelets and if necessary coagulation studies every 6 hours. GI bleeding requires an assessment of the source of bleeding and should include an early consultation with a gastroenterology service. Endoscopy typically is the initial means to identify the source of UGIB, determine whether active bleeding still is present, and guide the frequency of monitoring, including repeat endoscopy or other diagnostic tests. In addition, the source of bleeding may be treated through endoscopic techniques. An intravenous bolus of proton pump inhibitors followed by an infusion is recommended to prepare the patient for endoscopy associated with nonvariceal bleeding.3,4 Somatostatin or octreotide can be considered for variceal bleeding. The Blatchford score, which is based on several factors including urea and hemoglobin levels, systolic blood pressure, heart rate, hepatic disease, cardiac failure, melena, 227

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and presentation with syncope, can be used to determine which patients require urgent endoscopy.5 Once endoscopy is complete the Rockall score, which includes the endoscopic diagnosis and evidence for hemorrhage among other variables, can be used to stratify patients into high or low risk for recurrent hemorrhage or mortality.6 Bedside colonoscopy is

feasible when LGIB is identified,7 but whether urgent colonoscopy is associated with better outcome than a standard care algorithm based on angiography and expectant colonoscopy is unclear.8 Current guidelines for evaluation, monitoring, and management of UGIB, variceal bleeding, and LGIB are provided in Table 23.19,10; Table 23.211; and Figure 23.1.12

Table 23.1  Summary of Recommendations from 2010 Guidelines of the International Consensus Upper Gastrointestinal Bleeding Conference Group* Resuscitation, risk assessment, and pre-endoscopy management: 1. Urgent/emergent evaluation and initiation of resuscitation 2. Use appropriate prognostic scales for mortality and rebleeding to stratify patients as low or high risk. 3. Consider nasogastric tube placement. 4. PRBC transfusion for Hgb 7 g/dL 5. Correct coagulopathy, but do not delay endoscopy. 6. Promotility agents are not recommended as routine for pre-endoscopy. 7. Selected patients determined at low risk for rebleed after acute ulcer bleeding may be considered for discharge after endoscopy. 8. Pre-endoscopic PPI therapy may be useful to downstage the lesion and decrease need for endoscopic management, but its administration should not delay endoscopic evaluation. Endoscopic management: 1. Institution-specific protocols for multidisciplinary UGIB are recommended; availability of an endoscopist trained in endoscopic hemostasis is recommended. 2. Urgent availability of endoscopic support staff 3. Endoscopy within 24 hours for most cases 4. Hemostatic treatment not indicated for low-risk lesions 5. Clots in the ulcer bed should be irrigated with the goal of revealing the underlying lesion for treatment. 6. Removing adherent clots is controversial; consider endoscopic therapy vs. intensive PPI therapy. 7. Hemostatic endoscopic treatment is indicated for high-risk lesions. 8. Epinephrine injection alone is suboptimal: best used as part of a combined therapy 9. Endoscopic coaptive therapy methods are equivalent. 10. Clips, thermocoagulation, or sclerosant injection should be used for high-risk lesions, alone or combined with epinephrine. 11. Second-look endoscopy as a routine is not recommended. 12. In case of rebleeding, a second endoscopic therapy attempt is generally recommended.

Pharmacologic management: 1. Histamine receptor antagonists are not recommended for treatment in acute UGIB. 2. Somatostatin and octreotide are not recommended for treatment in acute UGIB. 3. PPI infusion protocol (bolus plus continuous infusion) should be given post–successful endoscopic treatment to all high-risk lesion patients to reduce rebleeding and mortality. 4. Patients should be discharged on once-daily regimen of oral PPI for a duration appropriate to the treated etiology.

Nonendoscopic and nonpharmacologic in-hospital management: 1. Following endoscopy, patients at low risk may be fed within 24 hours. 2. Patients with high-risk lesions should remain hospitalized for 72 hours after endoscopy. 3. Surgical consultation is advised when endoscopic therapy has failed. 4. Percutaneous embolization may provide an alternative to surgery when endoscopic therapy has failed. 5. Patients with bleeding ulcers require testing for Helicobacter pylori and should receive eradication therapy if positive; eradication should be confirmed with a negative test result. 6. Negative acute testing for H. pylori should be repeated.

Postdischarge ASA and NSAIDs: 1. For patients with history of ulcer bleeding who require chronic treatment with NSAIDs, it must be recognized that whether treatment is with traditional NSAID plus PPI or with COX-2 inhibitor alone, the risk for recurrent ulcer bleeding remains clinically significant. 2. For patients with history of ulcer bleeding, the combination of a COX-2 antagonist plus PPI is recommended to reduce risk of rebleed compared with COX-2 agent alone. 3. For patients on low-dose ASA for cardiovascular risk who then develop UGIB, the ASA therapy should be resumed as soon as risk for cardiovascular complication is thought to outweigh risk for rebleed. 4. In patients who require cardiovascular prophylaxis after ulcer bleeding, it should be noted that clopidogrel alone has a higher risk for rebleeding than ASA plus PPI.

Adapted from Barkun AN, Bardou M, Kuipers EJ, et al. International consensus recommendations on the management of patients with nonvariceal upper gastrointestinal bleeding. Ann Intern Med 2010;152:101–13; Barkun A, Bardou M, Marshall JK, et al. Consensus recommendations for managing patients with nonvariceal upper gastrointestinal bleeding. Ann Intern Med 2003;139:843–57. *Nonvariceal UGIB. ASA, Acetylsalicylic acid; COX, cyclooxygenase; Hgb, hemoglobin; NSAIDs, nonsteroidal anti-inflammatory drugs; PRBC, packed red blood cell; PPI, proton pump inhibitor; UGIB, upper gastrointestinal bleeding.

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229

Table 23.2  Summary of Recommendations for Acute Variceal Hemorrhage from the Practice Parameters Committee of the American College of Gastroenterology HEMORRHAGE FROM ESOPHAGEAL VARICES

1. Acute UGIB in patients with cirrhosis requires prompt attention with judicious intravascular volume support and blood transfusion aimed at maintenance of Hgb at ≈8 g/dL. 2. Short, up to 1 week of antibiotic prophylaxis of SBP and other infections is recommended for all cirrhotic patients with gastrointestinal hemorrhage: oral norfloxacin 400 mg bid or intravenous (IV) ciprofloxacin or IV ceftriaxone 1 g/day in advanced cirrhotic patients or when quinolone resistance may be suspected. 3. Pharmacologic therapy using somatostatin or its analogs octreotide, vapreotide and terlipressin (latter not available in United States) should be initiated immediately on suspicion of variceal bleeding and continued 3 to 5 days after diagnosis. 4. Endoscopy should be performed within 12 hours to diagnose variceal hemorrhage and treat by endoscopic variceal ligation (EVL) or sclerotherapy. 5. Transjugular intrahepatic portosystemic shunt (TIPS) is indicated for patients with uncontrolled bleeding, or who have failed combined pharmacologic and endoscopic treatment. 6. Balloon tamponade should be used as a temporizing measure maximally for 24 hours in patients with uncontrollable bleeding while awaiting definitive endoscopic or TIPS treatment. HEMORRHAGE FROM GASTRIC VARICES

1. In patients bleeding from gastric fundal varices, endoscopic variceal obturation using tissue adhesives such as cyanoacrylate is preferred if available; EVL is an option. 2. TIPS is indicated for patients with uncontrolled bleeding or who have failed combined pharmacologic and endoscopic treatment. Adapted from Garcia-Tsao G, Sanyal AJ, Grace ND, et al. Prevention and management of gastroesophageal varices and variceal hemorrhage in cirrhosis. Am J Gastroenterol 2007;102:2086–102. Hgb, Hemoglobin; SBP, spontaneous bacterial peritonitis; UGIB, upper gastrointestinal bleeding.

Bloody diarrhea

Hematochezia

Evaluate, resuscitate consult GI endoscopist

• Stool culture • Stool E. coli O157:H7 • Stool C. diff toxin • Immunocompromised consider CMV • Consider IBD • Treat as appropriate to identified cause • If pain consider ischemia

NGT aspirate

No blood normal gastric/ duodenal fluids

Any blood or concern for UGIB, or hemodynamic instability

Bowel prep →

(–)

Colonoscopy

Source identified

No source identified

Treated as appropriate

Continued bleeding

No or lesser bleeding

EGD

(+)

Treated as appropriate

Technically impossible

Severe

Small bowel suspected

Small Bowel Studies Capsule enteroscopy Push enteroscopy Double balloon enteroscopy CT or MRI enterography techniques

Arteriography Nuclear scanning CT/CTA Surgical consult

Fig. 23.1  Algorithm for lower gastrointestinal bleeding (LGIB). C. diff, Clostridium difficile; CMV, cytomegalovirus; CT, computed tomography; CTA, computed tomography angiography; E. coli, Escherichia coli; EGD, esophagogastroduodenoscopy; GI, gastrointestinal; IBD, inflammatory bowel disease; MRI, magnetic resonance imaging; NGT, nasogastric tube; UGIB, upper gastrointestinal bleeding. (Modified from Barnert J, Messmann H. Diagnosis and management of lower gastrointestinal bleeding. Nat Rev Gastroenterol Hepatol 2009;6:637–46.)

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Hepatic Failure Few patients with hepatic failure are cared for in the NCCU. However, patients with hepatic encephalopathy and cerebral edema frequently require the expertise of neurointensivists and neurosurgeons and management in the NCCU, for example, when therapeutic hypothermia is used for increased intracranial pressure (ICP) associated with hepatic encephalopathy.13,14 The pathology of hepatic encephalopathy is incompletely understood but appears to be associated with nitrogenous GI products and in particular ammonia that bypass liver metabolism in acute liver failure (ALF). These substances cross the blood-brain barrier, where they are thought to increase gama-aminobutyric acid (GABAergic) transmission and injure astrocytes that subsequently swell (i.e., cytotoxic edema). For this reason, corticosteroids are of no use. On the other hand, several lines of evidence suggest that proinflammatory mechanisms are involved in the pathogenesis of brain edema in ALF; this proposed mechanism provides a basis for using induced hypothermia to bridge patients with hepatic encephalopathy to transplant.15,16 ALF, also know as fulminant liver failure, is the abrupt loss of liver function in a patient without previous liver disease. It typically is associated with coagulopathy (international normalized ratio [INR] >0.5) and encephalopathy. In the United States, acetaminophen accounts for approximately 50% of ALF cases: other causes include hepatitis, drug-induced liver injury, and viral or autoimmune hepatitis. Initial evaluation includes a liver function panel, prothrombin time [PT]/INR, complete blood count, fibrinogen, D-dimer, acetaminophen level, toxicology screen, electrolytes, and creatinine. In addition, a search for an etiology is necessary; this may include alpha-fetoprotein, ceruloplasmin, serum protein electrophoresis, virology (cytomegalovirus; Epstein-Barr virus; hepatitis A, B, or C virus antigens; or antibodies), or antinuclear antibody among others. An abdominal computed tomography (CT) scan to evaluate liver volume is useful, but if not feasible bedside ultrasound may be obtained. A head CT scan is necessary for patients with grade III or IV encephalopathy (see following text). During an ICU stay, patient follow-up evaluation may include arterial blood gas, arterial lactate, arterial blood oxygen (ABO) analysis (two separate tests), and every6-hour PT/INR, transaminase level, total and direct bilirubin, and serum sodium. Frequent assessment of serum osmolarity or osmolality gap (when mannitol is used), and coagulation status also is required. There are two important approaches to classification of ALF patients: (1) grading of hepatic encephalopathy and (2) determining whether a patient is eligible for transplant and whether transplant is needed to prevent death. There are several classification scales for hepatic encephalopathy, but the West Haven Simplified Criteria17 (Table 23.3) is used most frequently. The severity of encephalopathy is the main barometer of disease severity and grades III and IV often mark the threshold for escalation of therapies. Determining who requires a liver transplant to prevent death is complex and requires consideration of ethical factors and an anticipation of future needs to ensure that definitive therapy is available in time to rescue the patient. The King’s College Criteria18 and the Model for End-Stage Liver Disease (MELD)19 are widely used scales to predict mortality in ALF and to help triage patients with severe liver disease for transplant (Table 23.4).

Table 23.3  West Haven Criteria for Semiquantitative Grading of Mental State in Acute Liver Failure GRADE I

• Trivial lack of awareness • Euphoria or anxiety • Shortened attention span • Impaired performance of addition GRADE II

• Lethargy or apathy • Minimal disorientation for time or place • Subtle personality change • Inappropriate behavior • Impaired performance of subtraction GRADE III

• Somnolence to semistupor, but responsive to verbal stimuli • Confusion • Gross disorientation GRADE IV

• Coma (unresponsive to verbal or noxious stimuli) Adapted from Atterbury CE, Maddrey WC, Conn HO. Neomycin-sorbitol and lactulose in the treatment of acute portal-systemic encephalopathy: a controlled, double-blind clinical trial. Am J Dig Dis 1978;23:398–406.

The Acute Physiology and Chronic Health Evaluation (APACHE) II score or Sequential Organ Failure Assessment (SOFA) score also can help predict outcome in acetaminopheninduced ALF.20,21 These scores (SOFA, MELD) and Simplified Acute Physiology Score (SAPS) II also can be used to predict outcome among patients with chronic liver insufficiency and cirrhosis who require ICU admission.22 Some studies suggest that ICU prognostic models such as SOFA may perform better than liver specific scores such as Child-Turcotte-Pugh (CTP) or MELD for outcome prediction among cirrhotic patients who are admitted to the ICU.23 The average overall mortality in ALF is 80%. By contrast, 60% to 80% survive after transplant. Thus once a patient is considered eligible for a transplant, the goals of care are to provide a bridge until this occurs. In 2007, the U.S. Acute Liver Failure Study Group (ALFSG) published guidelines to codify ICU management of ALF patients in their participating centers.24 Key points associated with the neurologic aspects and in particular patient monitoring of fulminant liver failure is summarized later in this chapter.14 Other aspects of ICU care—hemodynamic support, mechanical ventilation, renal support, prevention of infection, and nutrition and management of end-stage liver disease—are discussed elsewhere.25-27

Hepatic Encephalopathy and Hyperammonemia Hepatic encephalopathy (HE) is a feature of ALF. However, patients with chronic liver failure who acutely deteriorate (acute on chronic liver failure) may also experience HE.28 In these patients HE manifests by confusion, poor judgment, or personality change among other clinical features that may be exacerbated by the disease that requires ICU admission or the admission itself. The terminology associated with HE is

Section II—Clinical and Laboratory Assessment



231

Table 23.4  Common Prognostic Scales for Mortality Risk Assessment in Acute Liver Failure King’s College Criteria18

Modified King’s College18

Non-APAP all cause prothrombin time (PT) >100 seconds (INR >6.5) Or Any three of the following: Age 40 years Etiology: non-A, non-B hepatitis, halothane hepatitis, idiosyncratic drug reactions Duration of jaundice before onset of encephalopathy >7 days PT >50 seconds Serum bilirubin >18 mg/dL (all of scale is irrespective of the grade of encephalopathy)

Acetaminophen-induced disease Arterial pH 100 seconds (INR >6.5) and Serum creatinine >3.4 mg/dL

PPV mortality = 98% NPV mortality = 82%

PPV mortality = 84% NPV mortality = 86%

Model for End-Stage Liver Disease (MELD)19 MELD score = 3.78 [Ln serum bilirubin mg/dL] + 11.2 [Ln INR] + 9.57 [Ln serum creatinine mg/dL] + 6.43 ____________________________ Interpretation: 40 or more → 71.3% mortality 30-39 → 52.6% mortality 20-29 → 19.6% mortality 10-19 → 6.0% mortality 55 years WBC >16,000/mm3 Glucose >200 mg/dL LDH >350 IU/L SGOT >250 SF units

Fall in Hct >10% Calcium 5 mg/dL Third space losses >6 L

Prognosis for Mortality 7 signs = 100%

From Ranson JH, Rifkind KM, Roses DF, et al. Prognostic signs and the role of operative management in acute pancreatitis. Surgery, Gynecology & Obstetrics 1974;139(1):69-81 BUN, Blood urea nitrogen; Hct, hematocrit; LDH, lactate dehydrogenase; PaO2, arterial oxygen tension; SGOT, serum glutamic-oxaloacetic transaminase; WBC, white blood cell.

pancreatitis the median prevalence for organ failure is about 50%. Overall mortality for pancreatitis is 5% with a range between 3% for interstitial and 17% for necrotizing pancreatitis. In the absence of organ failure, mortality is zero but increases to 3% for single-organ failure and up to 50% for multiple-organ failure.41 In patients with pancreatitis initial laboratory evaluation should include complete blood count (CBC) with differential, complete serum chemistry including calcium, liver function, lactate dehydrogenase, amylase, lipase, and triglycerides. The Ranson Criteria, particularly those based on 48-hour laboratory data can be used to estimate mortality risk and for risk stratification (Table 23.5). In addition, APACHE II scores are useful: scores that increase during the first 48 hours are associated with worse course, whereas improving scores are associated with a benign course. Hemoconcentration at admission may be a poor prognostic indicator and particularly if the hematocrit then increases. In the absence of hemoconcentration, pancreatic necrosis is unlikely. Serum C-reactive protein (CRP) levels tend to peak at 36 to 72 hours, and when greater than 150 mg/L may suggest pancreatic necrosis. Except where there is need to evaluate for alternative diagnostic considerations, a CT of the abdomen is more useful when obtained after a delay of 2 to 4 days than at admission. By that time a more severe clinical course has declared itself, and the CT then can distinguish between simple interstitial disease or the presence of necrosis and microcirculation disruption. This distinction requires contrast administration, and the study is often called a dynamic CT of the pancreas or contrast-enhanced multidetector CT (MDCT). The timing of this study should be considered carefully to avoid contrast with a rising serum creatinine and evolving renal failure. When findings of necrotizing pancreatitis are present, intermittent serial CT examinations may be required to monitor for secondary intra-abdominal complications, pseudocyst development, organized necrosis, and vascular complications such as thrombosis or pseudoaneurysms. However, the cumulative dose of radiation with serial CT scans needs to be considered.42 The Balthazar CT criteria for acute pancreatitis43 divide the severity of pancreatitis into five grades, A through E: normal, enlarged pancreas, inflamed and or peripancreatic fat, single fluid collection, and two or more fluid collections. Grade A indicates the least and grade E the most severe form

of pancreatitis. Most patients with severe pancreatitis have one or several pancreatic fluid collections (grades D and E). Increasing grade is associated with increasing morbidity and mortality. The CT severity grade is an attempt to improve the prognostic accuracy of CT. In each grade patients are assigned points for the amount of necrosis; higher numerical scores indicate greater extent of necrosis and worse prognosis.44,45 In general, CT grading scales more accurately diagnose clinically severe disease and better identify pancreatic infection or the need for intervention than do clinical criteria.46 Patients with more severe pancreatitis or those with altered vital signs, diminishing urine output (UOP), increasing volume requirements, tachypnea or tachycardia, encephalopathy, or any indication of early organ failure require ICU care. Initial care focuses on adequate fluid resuscitation and avoidance of hypoxemia. In more severe cases third spacing can be profound, and aggressive fluid support may be required. Emesis, diaphoresis, and vascular permeability all contribute to the volume challenges, and the development of hypovolemia increases the risk of a necrotizing process if the microcirculation is inadequately supplied. Fluid status therefore should be monitored closely using continuous monitoring of blood pressure, heart rate, and urine output. In more severe cases, management may be best guided by CVP and ScvO2 monitoring and noninvasive monitoring techniques of cardiac function that provide data on cardiac performance, preload, and systemic vascular resistance (see Chapter 19). Infected pancreatic necrosis occurs in about one third of patients with necrotizing pancreatitis and generally develops after the first week. Clinically, patients with or without infected necrotizing pancreatitis appear similar. An abdominal CT may help make the diagnosis because air bubbles may be observed in the retroperitoneum with infection but not in sterile necrosis. Diagnosis is made by CT-guided percutaneous aspiration that if negative may be repeated every 5 to 7 days when systemic toxicity persists. Surgical debridement, often repeated, is the gold standard for treatment.

Abdominal Compartment Syndrome Increased abdominal pressure may arise in many disorders, but some more common conditions include cirrhosis with ascites, following major trauma, pancreatitis, after massive resuscitation or massive transfusion, sepsis, acidosis, or respiratory failure that requires high positive end-expiratory pressure (PEEP) levels for treatment. A high index of clinical suspicion in the appropriate circumstances, and willingness to initiate IAP monitoring, usually by bladder pressure measurement, is needed to diagnose dangerous, but often externally occult, elevations in intra-abdominal pressure (IAP).47,48 Failure to recognize this condition and failure to monitor it can compromise respiratory function and intra-abdominal organ function and lead to multiorgan failure and death.49 IAP is the steady-state pressure inside the abdominal cavity. It is measured in millimeters of mercury (mm Hg). The usual method to measure IAP is through fluid column pressure transduction from the port of a Foley catheter into which 25 mL of sterile saline are instilled into the bladder with the Foley catheter clamped just distal to the measurement port. Steady-state pressure is obtained at end expiration in a relaxed patient with the transducer zeroed at the midaxillary line. Continuous measurement protocols are described, but

Section II—Clinical and Laboratory Assessment

233

intermittent pressure transduction—every hour in the at-risk population—is used most frequently.50,51 Abdominal perfusion pressure (APP) is described by: APP = MAP − IAP Abdominal compartment syndrome and organ function compromise occur when IAP approaches MAP and visceral perfusion is compromised. The optimal target APP is greater than or equal to 60 mm Hg. Normal IAP in critically ill patients is thought to be 5 to 7 mm Hg. It may be near zero in the healthy population. IAP is graded according to severity50,51: grade I, 12-15 mm Hg; grade II, 16 to 20 mm Hg; grade III, 21 to 25 mm Hg; grade IV, greater than 25 mm Hg. There is no single pressure threshold at which reductions in microcirculatory blood flow sufficient to initiate organ dysfunction, are certain to occur. Oliguria is one of the first outward signs of organ compromise.52-54 Critical IAP levels seem to begin in the range of 10 to 15 mm Hg. Abdominal compartment syndrome therefore should not defined by a single number but rather as sustained IAP greater than 20 mm Hg (with or without APP 130 msec) can help identify patients likely to have a poor outcome.34 However, false positives are common (between 4% and 15%) and make it impractical to base treatment decisions on this finding. Late components may be better associated with long-term cognitive outcome than short-latency components35 but are not routinely used for patients with cardiac arrest. The role of BAEPs after cardiac arrest is less well studied. However, middle-latency auditory evoked responses are absent in patients who die or remain in a persistent vegetative state.22 Finally, EPs can be used to guide care in neonatal encephalopathy or childhood asphyxia.36

Traumatic Brain Injury Following TBI, SSEPs can help predict short-term mortality and long-term outcome.34,35,37-44 Bilaterally absent cortical SSEP responses with preserved peripheral and spinal potentials are associated with poor outcome.37-40 In general, SSEPs more accurately predict poor outcome than good outcome.41 For example, in a review of 44 studies, Carter and Butt41 observed that 71% of patients with normal SSEPs (N = 553) have a favorable outcome (normal or moderate disability; Fig. 24.5). By contrast when SSEPs are absent bilaterally (n = 777), 99% have an unfavorable outcome (severe disability, vegetative state, or death). The positive predictive value and sensitivity are 71% and 59%, respectively, for normal SSEP and a favorable outcome; and 99% and 46.2%, respectively, for bilaterally absent SSEP and an unfavorable outcome. Patients who have a favorable outcome despite bilaterally absent SSEPs (N = 12) are more commonly children, have

focal lesions, have subdural or extradural fluid collections, or have undergone decompressive craniotomy in the 48 hours before the recording. Overall, SSEPs perform favorably when compared with other TBI outcome predictors such as the GCS, pupillary or motor responses, computed tomography (CT), and EEG findings,42 and the the false-positive rate of bilaterally absent SSEPs after TBI is less than 0.5%. Repeated SSEPs can help detect secondary injury (e.g., hematoma enlargement or increased intracranial presure [ICP]), brainstem herniation, or cerebral ischemia.38,45,46 In some patients a change in SSEPs may precede an ICP increase.46 Serial SSEPs also may suggest recovery6,43 (Fig. 24.6). For example, reduction of latency and normalization of amplitude may occur earlier than recovery in the clinical examination.43 Poor long-term functional outcome (death or vegetative state at 2 years) is seen in comatose patients with traumatic brainstem lesions and absent N20s that do not recover within 48 hours of the injury. However, recovery of the N20 does not necessarily mean recovery of brain function.47 Prolongation or absent CCT is associated with poor 1-year cognitive and behavioral function.48 Although rare, reappearance of previously absent bilateral SSEPs may occur after TBI. This is described in some patients with good outcome after infratentorial hemorrhage or following hemicraniectomy.49-51 In addition, circumscribed bilateral sensory tract contusions in the brainstem may mimic bilateral SSEP loss from supratentorial injury. This may not necessarily mean a fatal prognosis.50 Finally, marked attenuation of the cortical N20-P25 must be distinguished from persistent loss of these signals.43 BAEPs are used less frequently than SSEPs for TBI outcome prediction,52-54 but when performed, BAEP abnormalities are more frequently seen in TBI patients with poor outcome.52,55

Acute Ischemic Stroke Diagnosis of acute ischemic stroke (AIS), is done by neurologic examination and neuroimaging. EPs, however, may be used in a patient with infratentorial ischemia if MRI is not available or in a patient with a pacemaker who cannot have

Section III—Electrophysiology



A

241

B C3-C4 C4-C3 C4-left Erbs

C4-right Erbs

C3-left Erbs

C3-right Erbs

0.5 uV

CS6-left Erbs

5 msec CS5-right Erbs

Left-right Erbs

C

Right-left Erbs 0.5 uV

D

5 msec

Fig. 24.5  Somatosensory evoked potential (SSEPs) in a comatose 76-year-old man with a traumatic right subdural hematoma (A) and contralateral parietal contusion (B). Symmetric bilateral median nerve cortical and subcortial SSEPs are present. The left median nerve SSEP (C) (Erb’s 11 msec, P14 15 msec, N20 22 msec) and the right median nerve SSEP (D) (Erb’s 11 msec, P14 16 msec, N20 23 msec) are present.

an MRI, and can be used for continuous monitoring in select patients at risk for herniation (e.g., a large cerebellar stroke). Ischemia of the pontine tegmentum results in both BAEP (loss of wave V) and SSEP abnormalities (absent N20). Ischemia restricted to the cerebellar peduncles only affects the BAEPs.56 False-negative EP results may occur—brainstem strokes may have normal SSEPs with medial or lateral strokes in up to 60% and 75% patients, respectively.57 EPs may be useful in patients with locked-in syndrome to provide objective evidence of brainstem involvement although there is no specific pattern to the abnormalities,58,59 and depending on the affected structures, BAEP and SSEP findings may vary from unilaterally normal to bilaterally absent.58-60 Finally, BAEP obtained within 24 hours of large middle cerebral artery infarction may help identify patients at risk for malignant edema61 and thus the need for a hemicraniectomy. The role of EPs in outcome prediction after AIS is less well studied than TBI or anoxia and is mainly limited to case series of patients with posterior fossa or massive hemispheric infarction. Bilateral BAEP and SSEP abnormalities are seen in patients with poor outcome after pontine and mesencephalic

infarction,62 and those with basilar thrombosis63 and can be particularly helpful when making decisions about prognosis when consciousness is impaired. Good outcome (moderate disability or better) is more likely when BAEPs and SSEPs are normal.63 EP abnormalities are of indeterminate predictive value in patients with locked-in syndrome.60 Cerebellar infarcts associated with coma may be accompanied by prolongation of the I to V interpeak latencies,64 although this abnormality may persist despite clinical improvement. There are conflicting data on the association between EP findings and outcome after supratentorial AIS. On the one hand, normal BAEPs but not SSEPs obtained before a hemicraniectomy are associated with survival and good functional outcome (Barthel Index ≥60) after large hemispheric strokes.65 On the other hand, SSEP findings after small internal capsule or corona radiate strokes66 do not correlate with 3-month outcome (Barthel Index). Others have found that serial SSEPs and BAEPs are associated with 30-day Glasgow Outcome Scale independent of stroke type and location, with the exception that BAEPs are not associated with outcome in those with infratentorial lesions.67 In part these differences in

242

Section III—Electrophysiology Vertebra 7

Left cortical response

Vertebra 7

Right cortical response Day 1

Day 1 N13

N13

N20 1 µV

1 µV

Day 10

N13

P25

N13

Day 10 N20 P25

N20 P25

N13

Day 304

N13

Day 304 N20

N20

P25 10 20

30 40 msec

10 20

30 40 msec

10 20

30 40 msec

10 20

30 40 msec

Fig. 24.6  Recovery of somatosensory evoked potential (SSEP) after traumatic brain injury (TBI). This 14-year-old boy was admitted in coma (Glasgow Coma Scale score 3). He developed elevated intracranial pressure, and a clinical improvement was first seen on day 13 after the injury. He did not move his left side purposefully until day 26. The initial median nerve SSEP is abnormal. Left cortical recordings were absent, and right hemispheric responses were prolonged with a severely decreased amplitude. For the left cortical projections, the first indication of recovery was observed with SSEPs on day 10. Over the next few days, these SSEP findings improved. Twenty-three days after injury, latencies of the right cortical projection were within normal limits, whereas amplitudes remained reduced. One year after the accident, he had a minimal residual speech impairment but had returned to his former activities. (Reprinted with permission from Claassen J, Hansen HC. Early recovery after closed traumatic head injury: somatosensory evoked potentials and clinical findings. Crit Care Med 2001;29:494–502.)

results may stem from differences in study design and small sample size. Several EP observations are associated with stroke location. AIS of the ventroposterior thalamus leads to an absent response, decrease in amplitude, delay in peak latency, or attenuation of median N20-P25 and tibial P40 components.68 Lateral ventroposterior lesions preferentially affect tibial SSEPs, whereas medial lesions affect median SSEPs. Strokes that affect the thalamocortical pathways lead to less consistent SSEP abnormalities. Although large strokes of the corona radiate may lead to similar SSEP abnormalities as thalamic strokes,68 smaller lesions of the corona radiate or internal capsule often have an inconsistent relationship between EP findings and sensory symptoms.66 This inconsistency is likely from incomplete involvement of the thalamocortical pathways in small strokes.

ICH in the putamen or thalamus generally parallels the normalization of SSEP components.69 SSEPs and BAEPs can provide prognostic information in patients with an ICH located in the brainstem, particularly in the pons70,71 or in deep supratentorial structures including the putamen72,73 and thalamus.72 In particular, prolongation of I to V interpeak latencies in the BAEP and bilaterally absent N20s in the SSEP are are associated with poor prognosis.70,74 SSEPs may have a lower false-negative rate for poor outcome than BAEPs after putaminal ICHs.73 Good functional outcome is likely when BAEPs are normal and SSEPs are normal after putaminal ICH.72 Following a pontine ICH, good outcome may be seen if normal amplitudes and latencies of waves I to V in BAEPs are at least unilaterally present.70

Intracerebral Hemorrhage

There is an unclear relationship between the severity of subarachnoid hemorrhage (SAH) and EP findings; some studies suggest an association between CCT prolongation75 or absence of SSEP and BAEP responses76 and the Hunt Hess grade, whereas others found no association between CCT abnormalities and clinical severity.77,78 Xenon single photon emission computed tomography (SPECT)79,80 studies suggest CCT prolongation is associated with impaired cerebral blood flow (CBF) after SAH, particularly when CBF is less than 30 mL/100 g/min.81 However, EP studies do not have a role in vasospasm diagnosis in clinical practice.

Evoked potentials (EPs) have little if any role in the diagnosis of an intracerebral hemorrhage (ICH). In addition EP localization value is lim­ited after thalamic or putaminal ICH.69 However, BAEP abnormalities may provide information about small posterior circulation bleeds, particularly when tegmental structures are affected.70 Serial SSEPs may provide an alternative to frequent brain imaging to examine potential for neurologic recovery, particularly for ICHs in the posterior circulation. Recovery of motor function after

Subarachnoid Hemorrhage

Studies in the 1970s did not find an association between EP findings and outcome.82 Subsequent studies describe an association between BAEP and SSEP abnormalities including bilateral CCT prolongation (>6 msec) or bilaterally absent cortical responses and poor outcome or death after SAH.77,83,84 Tibial rather than median nerve SSEP may be more robust in outcome prediction.84 Patients with normal SSEPs have the potential for a good outcome.77 These differences may be associated with advances in SAH management particularly for poor-grade SAH patients.

Spinal Cord Injury EPs have an established role during spinal surgery but are not frequently used to monitor patients with spinal cord injury (SCI) in the ICU.85 Although EP abnormalities after SCI, including spinal cord ischemia, are associated with long-term outcome,86-88 they do not appear to add any prognostic accuracy to the neurologic examination but can be used to supplement it.86,89,90 SSEPs may have a role in injury assessment for comatose patients with suspected SCI.88 In these patients the extent of neurologic deficits is associated with the degree of SSEP abnormalities: N9 and N20 latencies for the upper limbs and P40 and P60 for the lower limbs.91

Brain Death There is no single method to confirm brain death, the diagnosis of which depends in large part on the clinical examination (see Chapter 13) and strict protocols. However, Wijdicks in a review conducted a decade ago, found there was a lack of consensus on the exact criteria in many published practice parameters and guidelines and that 28 of 70 (40%) of the practice guidelines he studied mandated the use of confirmatory testing. Many of these recommended use of EPs.4 When repeat studies are performed, patients who progress to brain death lose subcortical SSEP and all BAEP responses.12,92 Loss of the median nerve SSEP noncephalic P14 and of its cephalic referenced reflection N14 and the N18 is seen in brain death.92,93 No specific BAEP pattern is seen in patients who progress to brain death.94,95 Diagnostic accuracy is improved by combining BAEPs and SSEPs.96 EPs can also be helpful in patients when there is doubt about the clinical findings or cardiopulmonary instability limits the ability to perform an apnea test.

Coma Associated with Metabolic or Toxic Encephalopathy The International Society for Hepatic Encephalopathy and Nitrogen Metabolism (ISHEN) published guidelines for the use of neurophysiologic investigations in hepatic encephalopathy.97 There are three main recommendations. First, the choice of neurophysiologic test depends in part on the severity of encephalopathy. Quantitative EEG may be used for mild forms, but SSEPs should be considered for more severe encephalopathy. Second, when N20 responses are bilaterally absent, further evaluation is recommended to determine the extent of irreversible brain injury before liver transplantation. Third, SSEPs and BAEPs may be used to help make decisions about ICP and its management, for example, when an ICP monitor is not feasible or to complement the information of

Section III—Electrophysiology

243

an ICP monitor (i.e., determining the consequence of an ICP increase).46

Outside the Intensive Care Unit A large body of literature describes the use of intraoperative neurophysiologic monitoring including use of SSEPs, BAEPs, transcranial motor evoked potentials (tcMEPs), and direct electromygraphy, and evidence-based guidelines were published on the use of intraoperative monitoring.98 The reader is referred to reviews on the topic.99-101 SSEPs can: (1) help identify cerebral ischemia during cerebrovascular surgery including carotid endarterectomy or aneurysm surgery,102 or during repair of the thoracic aorta,103 (2) identify spinal cord injury during spine surgery,104 or (3) help guide resection of epileptic foci,105 tumors,106 or arteriovenous malformations (AVMs)107 in select cortical areas or intramedullary spinal lesions,108 whereas BAEPs can be useful during posterior fossa surgery.109 In general, neurologic abnormalities such as paraplegia after spinal surgery never or very rarely occur if there are no changes in EPs during intraoperative monitoring. EPs also are used in studies of cognition and behavior and to evaluate conditions such as multiple sclerosis, Friedreich’s ataxia, and Alzheimer’s disease.

How to Use Evoked Potential Monitoring, and Troubleshooting Electrical Artifact Electrical artifact (“noise”) may frequently interfere with EP recordings in the ICU setting. This is of particular concern in SSEP recordings because notch filters are discouraged. The noise level influences the accuracy of the recording and thus interobserver agreement. This can limit the use of SSEPs in prognosis decisions.110 Therefore every effort should be made to minimize the artifact level (60 years). The majority of these events lasted less than 30 minutes and all responded to benzodiazepines and phenytoin. On the other hand, Amantini et al. observed far fewer seizures in TBI patients (3%). These differences may be associated with use of a much greater dose of medications such as midazolam, propofol, thiopental, or a combination, that can have antiseizure activity.73 EEG recordings have been used to predict outcome in TBI patients. Several factors are associated with outcome, including (1) an increase or decrease in the absolute and relative amplitudes in the alpha and theta bands in the EEG can help differentiate survivors from nonsurvivors74; (2) a delta EEG pattern is associated with death and poor functional outcome75; (3) a reduced percentage of alpha variability is associated with poor prognosis41; and (4) the presence of EEG reactivity to painful stimuli is associated with a good outcome.76 However, prognostic errors based on EEG may be observed in 20% of patients.74

Aneurysmal Subarachnoid Hemorrhage The incidence of seizures after aneurysmal SAH (aSAH) varies from 4% to 24%. Most cases occur at the time of aneurysm rupture or shortly after the initial hemorrhage.77 Risk factors for seizures include a history of epilepsy, middle cerebral artery aneurysms, a cerebral infarct, and an intracerebral hematoma.78 NCS also are identified after SAH. The incidence varies with the method of detection. For example, the incidence of NCS is 3%, when using repeated standard (i.e., iEEG).79 When using cEEG, and in particular for more than 24 hours, seizures are detected in 19% of patients, and the majority (95%) of them are NCS.34 Up to 8% of patients have NCSE, despite antiepileptic prophylaxis (fosphenytoin).80 Risk factors for NCSE include (1) older age, (2) female sex, (3) poor-grade SAH, (4) the amount of cisternal blood, (5) hydrocephalus, and (6) the presence of structural brain lesions including focal or global cerebral edema. NCSE can be refractory to therapy, and many of these patients have a poor outcome. In many of these series cEEG was used in patients

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Section III—Electrophysiology

Bilateral frontal ischemia — decrease in alpha variability Fig. 25.4  Decrease in alpha variability in subarachnoid hemorrhage (SAH) associated with bifrontal ischemia.

Table 25.2  Relationship Between Cerebral Blood Flow and Electroencephalogram Changes CBF mL/100 g/min

EEG Change

Reversibility

35-70

Normal

No injury

25-35

Loss of beta

Reversible

18-25

Theta slowing

Reversible

12-18

Delta slowing

Reversible

/=50% and 2 mL/ min)18 (Fig. 32.2).

Complications on Insertion The commonest complications are carotid artery puncture and hematoma formation, which occur in about 1% to 4% of insertions and are usually self-limiting. Pneumothorax, venous air embolism, and venous thrombosis are infrequent complications, as is damage to adjacent structures such as the carotid artery, vagus and phrenic nerves, and the thoracic duct. There

SjvO2 %

Measurement Obtained from Jugular Bulb Catheters

40

0 PaCO2 25 mm Hg

PaCO2 30 mm Hg 2 mL/min 4 mL/min 10 mL/min

Fig. 32.2  The speed of blood withdrawal from jugular bulb catheters affects accuracy of reading. Jugular venous oxygen saturation (SjvO2) values are higher with faster rates of blood withdrawal because of contamination with extracranial blood. Optimal rate appears to be 2 mL/min.

is an increased risk of local and systemic infection with longterm placement.

Interpretation of the Measurements Normal SjvO2 values range between 55% and 75%. In simple terms, SjvO2 levels less than 55% suggest cerebral oxygen demand exceeding supply, for example, as a consequence of hypoperfusion (ischemia), whereas levels greater than 75% indicate relative hyperemia (Tables 32.1 and 32.2). Microdialysis studies in traumatic brain injury (TBI) patients demonstrate that jugular oxygen desaturation is associated with elevated glutamate.19 Evidence for cellular dysfunction detected by microdialysis of metabolites such as glutamate, glycerol, lactate, and pyruvate consistently occurs when SjvO2 is less than 45%.20 However, SjvO2 is a global hemispheric measurement and hence regional ischemia cannot be detected. For example, Chieregato et al.21 suggest that jugular bulb oximetry, without ICP monitoring, is suboptimal to manage a patient with subarachnoid haemorrhage (SAH) and raised intracranial pressure.22 Therefore although a normal SjvO2 does not guarantee absence of regional ischemia, a low SjvO2 indicates either an increase in oxygen extraction or a reduction in oxygen delivery, which may be an early warning of cerebral ischemia.23 The volume of ischemic brain to cause a change in SjvO2 is large, however. For example, Coles et al.24 examined 15 TBI patients with positron emission tomography (PET) within 24 hours of head injury to map CBF, CMRO2, and oxygen extraction fraction (OEF). The SjvO2 correlated with the ischemic brain volume (measured by PET OEF) but SjvO2 values of 50% only occurred when ischemic brain volume was 170 plus or minus 63 mL (mean ± 95% coagulation index [CI]), that is, 13 plus or minus 5% of the brain. Finally in some patients, changes in SjvO2 associated with intracranial hypertension may only be observed after herniation.

Section V—Cerebral Blood Flow



Table 32.1  A Summary of the Main Causes and Treatment of Low and High Jugular Saturations High SjvO2

Abnormal autoregulation Increased oxygen supply Deceased oxygen consumption Extracerebral blood

Low SjvO2

Abnormal autoregulation Deceased oxygen supply

Increased oxygen consumption

Hyperemia Polycythemia Hypothermia Sedative drugs Anesthetic drugs Cerebral Infarction

Hypoxia Hypotension Intracranial hypertension Hyperventilation Low cardiac output Anemia Hyperthermia Seizures Sepsis

SjvO2, Jugular venous oxygen saturation.

Table 32.2  Arteriovenous Difference in Oxygen AVDO2 = CMRO2 / CBF (calculation − 1.39 (SaO2 −  SjvO2) × Hgb/100 Normal = 5-7.5 vol% (5.1 - 8.3 vol%) Narrow AVDO2 −  CMRO2) Wide AVDO2 − >7.5 vol% = low flow (CBF