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Hirsch KG, Abella BS, Amorim E, Bader MK, Barletta JF, Berg K, Callaway CW, Friberg H, Gilmore EJ, Greer DM, Kern KB, Livesay S, May TL, Neumar RW, Nolan JP, Oddo M, Peberdy MA, Poloyac SM, Seder D, Taccone FS, Uzendu A, Walsh B, Zimmerman JL, Geocadin RG. Critical Care Management of Patients After Cardiac Arrest: A Scientific Statement from the American Heart Association and Neurocritical Care Society. Neurocrit Care 2024; 40:1-37. [PMID: 38040992 PMCID: PMC10861627 DOI: 10.1007/s12028-023-01871-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 06/08/2023] [Indexed: 12/03/2023]
Abstract
The critical care management of patients after cardiac arrest is burdened by a lack of high-quality clinical studies and the resultant lack of high-certainty evidence. This results in limited practice guideline recommendations, which may lead to uncertainty and variability in management. Critical care management is crucial in patients after cardiac arrest and affects outcome. Although guidelines address some relevant topics (including temperature control and neurological prognostication of comatose survivors, 2 topics for which there are more robust clinical studies), many important subject areas have limited or nonexistent clinical studies, leading to the absence of guidelines or low-certainty evidence. The American Heart Association Emergency Cardiovascular Care Committee and the Neurocritical Care Society collaborated to address this gap by organizing an expert consensus panel and conference. Twenty-four experienced practitioners (including physicians, nurses, pharmacists, and a respiratory therapist) from multiple medical specialties, levels, institutions, and countries made up the panel. Topics were identified and prioritized by the panel and arranged by organ system to facilitate discussion, debate, and consensus building. Statements related to postarrest management were generated, and 80% agreement was required to approve a statement. Voting was anonymous and web based. Topics addressed include neurological, cardiac, pulmonary, hematological, infectious, gastrointestinal, endocrine, and general critical care management. Areas of uncertainty, areas for which no consensus was reached, and future research directions are also included. Until high-quality studies that inform practice guidelines in these areas are available, the expert panel consensus statements that are provided can advise clinicians on the critical care management of patients after cardiac arrest.
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Affiliation(s)
| | | | - Edilberto Amorim
- San Francisco-Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Mary Kay Bader
- Providence Mission Hospital Nursing Center of Excellence/Critical Care Services, Mission Viejo, USA
| | | | | | | | | | | | | | - Karl B Kern
- Sarver Heart Center, University of Arizona, Tucson, USA
| | | | | | | | - Jerry P Nolan
- Warwick Medical School, University of Warwick, Coventry, UK
- Royal United Hospital, Bath, UK
| | - Mauro Oddo
- CHUV-Lausanne University Hospital, Lausanne, Switzerland
| | | | | | | | | | - Anezi Uzendu
- St. Luke's Mid America Heart Institute, Kansas City, USA
| | - Brian Walsh
- University of Texas Medical Branch School of Health Sciences, Galveston, USA
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2
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Hirsch KG, Abella BS, Amorim E, Bader MK, Barletta JF, Berg K, Callaway CW, Friberg H, Gilmore EJ, Greer DM, Kern KB, Livesay S, May TL, Neumar RW, Nolan JP, Oddo M, Peberdy MA, Poloyac SM, Seder D, Taccone FS, Uzendu A, Walsh B, Zimmerman JL, Geocadin RG. Critical Care Management of Patients After Cardiac Arrest: A Scientific Statement From the American Heart Association and Neurocritical Care Society. Circulation 2024; 149:e168-e200. [PMID: 38014539 PMCID: PMC10775969 DOI: 10.1161/cir.0000000000001163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The critical care management of patients after cardiac arrest is burdened by a lack of high-quality clinical studies and the resultant lack of high-certainty evidence. This results in limited practice guideline recommendations, which may lead to uncertainty and variability in management. Critical care management is crucial in patients after cardiac arrest and affects outcome. Although guidelines address some relevant topics (including temperature control and neurological prognostication of comatose survivors, 2 topics for which there are more robust clinical studies), many important subject areas have limited or nonexistent clinical studies, leading to the absence of guidelines or low-certainty evidence. The American Heart Association Emergency Cardiovascular Care Committee and the Neurocritical Care Society collaborated to address this gap by organizing an expert consensus panel and conference. Twenty-four experienced practitioners (including physicians, nurses, pharmacists, and a respiratory therapist) from multiple medical specialties, levels, institutions, and countries made up the panel. Topics were identified and prioritized by the panel and arranged by organ system to facilitate discussion, debate, and consensus building. Statements related to postarrest management were generated, and 80% agreement was required to approve a statement. Voting was anonymous and web based. Topics addressed include neurological, cardiac, pulmonary, hematological, infectious, gastrointestinal, endocrine, and general critical care management. Areas of uncertainty, areas for which no consensus was reached, and future research directions are also included. Until high-quality studies that inform practice guidelines in these areas are available, the expert panel consensus statements that are provided can advise clinicians on the critical care management of patients after cardiac arrest.
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3
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Carroll EE, Der-Nigoghossian C, Alkhachroum A, Appavu B, Gilmore E, Kromm J, Rohaut B, Rosanova M, Sitt JD, Claassen J. Common Data Elements for Disorders of Consciousness: Recommendations from the Electrophysiology Working Group. Neurocrit Care 2023; 39:578-585. [PMID: 37606737 DOI: 10.1007/s12028-023-01795-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 08/23/2023]
Abstract
BACKGROUND Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group. METHODS After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs. RESULTS After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group. CONCLUSIONS Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research.
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Affiliation(s)
- Elizabeth E Carroll
- Department of Neurology, Columbia University Medical Center, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA
- NewYork-Presbyterian Hospital, New York, NY, USA
| | | | | | - Brian Appavu
- Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ, USA
- University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA
| | - Emily Gilmore
- Divisions of Neurocritical Care and Emergency Neurology and Epilepsy, Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
- Yale New Haven Hospital, New Haven, CT, USA
| | - Julie Kromm
- Departments of Critical Care Medicine and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Benjamin Rohaut
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, Centre national de la recherche scientifique, Assistance Publique-Hôpitaux de Paris, Neurosciences, Hôpital de La Pitié Salpêtrière, Paris, France
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Jacobo Diego Sitt
- Paris Brain Institute (ICM), Centre national de la recherche scientifique, Paris, France
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA.
- NewYork-Presbyterian Hospital, New York, NY, USA.
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Guo Y, Gharibani P, Agarwal P, Cho S, Thakor NV, Geocadin RG. Hyperacute autonomic and cortical function recovery following cardiac arrest resuscitation in a rodent model. Ann Clin Transl Neurol 2023; 10:2223-2237. [PMID: 37776065 PMCID: PMC10723251 DOI: 10.1002/acn3.51907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 08/29/2023] [Accepted: 09/11/2023] [Indexed: 10/01/2023] Open
Abstract
OBJECTIVE There is a complex interaction between nervous and cardiovascular systems, but sparse data exist on brain-heart electrophysiological responses to cardiac arrest resuscitation. Our aim was to investigate dynamic changes in autonomic and cortical function during hyperacute stage post-resuscitation. METHODS Ten rats were resuscitated from 7-min cardiac arrest, as indicators of autonomic response, heart rate (HR), and its variability (HRV) were measured. HR was monitored through continuous electrocardiography, while HRV was assessed via spectral analysis, whereby the ratio of low-/high-frequency (LF/HF) power indicates the balance between sympathetic/parasympathetic activities. Cortical response was evaluated by continuous electroencephalography and quantitative analysis. Parameters were quantified at 5-min intervals over the first-hour post-resuscitation. Neurological outcome was assessed by Neurological Deficit Score (NDS, range 0-80, higher = better outcomes) at 4-h post-resuscitation. RESULTS A significant increase in HR was noted over 15-30 min post-resuscitation (p < 0.01 vs.15-min, respectively) and correlated with higher NDS (rs = 0.56, p < 0.01). LF/HF ratio over 15-20 min was positively correlated with NDS (rs = 0.75, p < 0.05). Gamma band power surged over 15-30 min post-resuscitation (p < 0.05 vs. 0-15 min, respectively), and gamma band fraction during this period was associated with NDS (rs ≥0.70, p < 0.05, respectively). Significant correlations were identified between increased HR and gamma band power during 15-30 min (rs ≥0.83, p < 0.01, respectively) and between gamma band fraction and LF/HF ratio over 15-20 min post-resuscitation (rs = 0.85, p < 0.01). INTERPRETATIONS Hyperacute recovery of autonomic and cortical function is associated with favorable functional outcomes. While this observation needs further validation, it presents a translational opportunity for better autonomic and neurologic monitoring during early periods post-resuscitation to develop novel interventions.
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Affiliation(s)
- Yu Guo
- Department of Biomedical EngineeringJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Payam Gharibani
- Division of Neuroimmunology, Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Prachi Agarwal
- Department of Electrical and Computer EngineeringJohns Hopkins Whiting School of EngineeringBaltimoreMarylandUSA
| | - Sung‐Min Cho
- Departments of Neurology, Anesthesiology‐Critical Care Medicine and NeurosurgeryJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Nitish V. Thakor
- Department of Biomedical EngineeringJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Romergryko G. Geocadin
- Departments of Neurology, Anesthesiology‐Critical Care Medicine and NeurosurgeryJohns Hopkins University School of MedicineBaltimoreMarylandUSA
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Candia-Rivera D, Machado C. Reduced Heartbeat-Evoked Responses in a Near-Death Case Report. J Clin Neurol 2023; 19:581-588. [PMID: 37455508 PMCID: PMC10622722 DOI: 10.3988/jcn.2022.0415] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/30/2022] [Accepted: 01/25/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND AND PURPOSE Whether brain-heart communication continues under ventricular fibrillation (VF) remains to be determined. There is weak evidence of physiological changes in cortical activity under VF. Moreover, brain-heart communication has not previously been studied in this condition. We aimed to measure parallel changes in heart-rate variability (HRV), cortical activity, and brain-heart interactions in a patient who experienced VF. METHODS The EEG and EKG signals for the case report were acquired for approximately 20 h. We selected different 1-min-long segments based on the changes in the EKG waveform. We present the changes in heartbeat-evoked responses (HERs), HRV, and EEG power for each selected segment. RESULTS The overall physiological activity appeared to deteriorate as VF proceeded. Brain-heart interactions measured using HERs disappeared, with a few aberrant amplitudes appearing occasionally. The parallel changes in EEG and HRV were not pronounced, suggesting the absence of bidirectional neural control. CONCLUSIONS Our measurements of brain-heart interactions suggested that the evolving VF impairs communication between the central and autonomic nervous systems. These results may support that reduced brain-heart interactions reflect loss of consciousness and deterioration in the overall health state.
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Affiliation(s)
| | - Calixto Machado
- Department of Clinical Neurophysiology, Institute of Neurology and Neurosurgery, Havana, Cuba
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Rubinos C, Bruzzone MJ, Viswanathan V, Figueredo L, Maciel CB, LaRoche S. Electroencephalography as a Biomarker of Prognosis in Acute Brain Injury. Semin Neurol 2023; 43:675-688. [PMID: 37832589 DOI: 10.1055/s-0043-1775816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
Electroencephalography (EEG) is a noninvasive tool that allows the monitoring of cerebral brain function in critically ill patients, aiding with diagnosis, management, and prognostication. Specific EEG features have shown utility in the prediction of outcomes in critically ill patients with status epilepticus, acute brain injury (ischemic stroke, intracranial hemorrhage, subarachnoid hemorrhage, and traumatic brain injury), anoxic brain injury, and toxic-metabolic encephalopathy. Studies have also found an association between particular EEG patterns and long-term functional and cognitive outcomes as well as prediction of recovery of consciousness following acute brain injury. This review summarizes these findings and demonstrates the value of utilizing EEG findings in the determination of prognosis.
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Affiliation(s)
- Clio Rubinos
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina
| | | | - Vyas Viswanathan
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina
| | - Lorena Figueredo
- Department of Neurology, University of Florida, Gainesville, Florida
| | - Carolina B Maciel
- Department of Neurology, University of Florida, Gainesville, Florida
| | - Suzette LaRoche
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina
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7
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Zheng J, Storad Z, Al-Chalabi M, Gharaibeh K, Saleem S, Sheikh A, Mahfooz N. Lance-Adams Syndrome: Case series and literature review. Clin Neurophysiol Pract 2023; 8:187-193. [PMID: 37822592 PMCID: PMC10562981 DOI: 10.1016/j.cnp.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 07/04/2023] [Accepted: 08/01/2023] [Indexed: 10/13/2023] Open
Abstract
Background Lance-Adams Syndrome (LAS) is a rare complication of successful cardiopulmonary resuscitation (CPR). It is a form of posthypoxic myoclonus characterized by action or intention myoclonus developing days to months after an hypoxic insult to the brain. LAS, especially early in a patient's clinical course, can be challenging to diagnose. Electroencephalogram (EEG) pattern of midline spike-wave discharge associated with favorable prognosis. There is no consensus in treatment of LAS but use of various anti-epileptic medications has been documented in literature. Case Presentation In this case series, all of the patients presented after achieving return of spontaneous circulation (ROSC) and subsequently developed myoclonus. EEG findings beyond the initial hospitalization continued to show later showed changes consistent with LAS in three of the four patients. Different combinations of AEDs were used in the management of LAS with variable success and adverse effects. Conclusion Our cases highlight that the characteristic EEG pattern can be useful in the diagnosis of LAS and allow for better prognostication and management in patients with posthypoxic myoclonus. We reviewed the available literature to better understand the prevalence, mechanism, clinical presentation, diagnosis, and management of LAS.
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Affiliation(s)
- Judy Zheng
- Department of Neurology, University of Toledo, Toledo, OH, USA
| | - Zachary Storad
- College of Medicine and Life Sciences, University of Toledo, Toledo, OH, USA
| | | | | | - Sidra Saleem
- Department of Neurology, University of Toledo, Toledo, OH, USA
| | - Ajaz Sheikh
- Department of Neurology, University of Toledo, Toledo, OH, USA
| | - Naeem Mahfooz
- Department of Neurology, University of Toledo, Toledo, OH, USA
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8
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Hoedemaekers C, Hofmeijer J, Horn J. Value of EEG in outcome prediction of hypoxic-ischemic brain injury in the ICU: A narrative review. Resuscitation 2023; 189:109900. [PMID: 37419237 DOI: 10.1016/j.resuscitation.2023.109900] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/26/2023] [Accepted: 06/29/2023] [Indexed: 07/09/2023]
Abstract
Prognostication of comatose patients after cardiac arrest aims to identify patients with a large probability of favourable or unfavouble outcome, usually within the first week after the event. Electroencephalography (EEG) is a technique that is increasingly used for this purpose and has many advantages, such as its non-invasive nature and the possibility to monitor the evolution of brain function over time. At the same time, use of EEG in a critical care environment faces a number of challenges. This narrative review describes the current role and future applications of EEG for outcome prediction of comatose patients with postanoxic encephalopathy.
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Affiliation(s)
- Cornelia Hoedemaekers
- Department of Critical Care, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands.
| | - Jeannette Hofmeijer
- Department of Clinical Neurophysiology, Technical Medical Center, University of Twente, Enschede, the Netherlands; Department of Neurology, Rijnstate Hospital, Arnhem, the Netherlands
| | - Janneke Horn
- Department of Critical Care, Amsterdam University Medical Center, Location AMC, Amsterdam, the Netherlands
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9
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Jones KG, Lybbert C, Euler MJ, Huang J, Lunt S, Richards SV, Jessop JE, Larson A, Odell DH, Kuck K, Tadler SC, Mickey BJ. Diversity of electroencephalographic patterns during propofol-induced burst suppression. Front Syst Neurosci 2023; 17:1172856. [PMID: 37397237 PMCID: PMC10309040 DOI: 10.3389/fnsys.2023.1172856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/23/2023] [Indexed: 07/04/2023] Open
Abstract
Burst suppression is a brain state consisting of high-amplitude electrical activity alternating with periods of quieter suppression that can be brought about by disease or by certain anesthetics. Although burst suppression has been studied for decades, few studies have investigated the diverse manifestations of this state within and between human subjects. As part of a clinical trial examining the antidepressant effects of propofol, we gathered burst suppression electroencephalographic (EEG) data from 114 propofol infusions across 21 human subjects with treatment-resistant depression. This data was examined with the objective of describing and quantifying electrical signal diversity. We observed three types of EEG burst activity: canonical broadband bursts (as frequently described in the literature), spindles (narrow-band oscillations reminiscent of sleep spindles), and a new feature that we call low-frequency bursts (LFBs), which are brief deflections of mainly sub-3-Hz power. These three features were distinct in both the time and frequency domains and their occurrence differed significantly across subjects, with some subjects showing many LFBs or spindles and others showing very few. Spectral-power makeup of each feature was also significantly different across subjects. In a subset of nine participants with high-density EEG recordings, we noted that each feature had a unique spatial pattern of amplitude and polarity when measured across the scalp. Finally, we observed that the Bispectral Index Monitor, a commonly used clinical EEG monitor, does not account for the diversity of EEG features when processing the burst suppression state. Overall, this study describes and quantifies variation in the burst suppression EEG state across subjects and repeated infusions of propofol. These findings have implications for the understanding of brain activity under anesthesia and for individualized dosing of anesthetic drugs.
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Affiliation(s)
- Keith G. Jones
- Interdepartmental Program in Neuroscience, The University of Utah, Salt Lake City, UT, United States
- Department of Psychiatry, Huntsman Mental Health Institute, The University of Utah, Salt Lake City, UT, United States
| | - Carter Lybbert
- Department of Biomedical Engineering, The University of Utah, Salt Lake City, UT, United States
- Department of Anesthesiology, The University of Utah, Salt Lake City, UT, United States
| | - Matthew J. Euler
- Department of Psychology, The University of Utah, Salt Lake City, UT, United States
| | - Jason Huang
- Department of Biomedical Engineering, The University of Utah, Salt Lake City, UT, United States
| | - Seth Lunt
- Department of Psychiatry, Huntsman Mental Health Institute, The University of Utah, Salt Lake City, UT, United States
| | - Sindhu V. Richards
- Department of Neurology, The University of Utah, Salt Lake City, UT, United States
| | - Jacob E. Jessop
- Department of Anesthesiology, The University of Utah, Salt Lake City, UT, United States
| | - Adam Larson
- Department of Anesthesiology, The University of Utah, Salt Lake City, UT, United States
| | - David H. Odell
- Department of Psychiatry, Huntsman Mental Health Institute, The University of Utah, Salt Lake City, UT, United States
- Department of Anesthesiology, The University of Utah, Salt Lake City, UT, United States
| | - Kai Kuck
- Department of Biomedical Engineering, The University of Utah, Salt Lake City, UT, United States
- Department of Anesthesiology, The University of Utah, Salt Lake City, UT, United States
| | - Scott C. Tadler
- Department of Psychiatry, Huntsman Mental Health Institute, The University of Utah, Salt Lake City, UT, United States
- Department of Anesthesiology, The University of Utah, Salt Lake City, UT, United States
| | - Brian J. Mickey
- Interdepartmental Program in Neuroscience, The University of Utah, Salt Lake City, UT, United States
- Department of Psychiatry, Huntsman Mental Health Institute, The University of Utah, Salt Lake City, UT, United States
- Department of Biomedical Engineering, The University of Utah, Salt Lake City, UT, United States
- Department of Anesthesiology, The University of Utah, Salt Lake City, UT, United States
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10
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Siddiqi AZ, Froese L, Gomez A, Sainbhi AS, Stein K, Park K, Vakitbilir N, Zeiler FA. The effect of burst suppression on cerebral blood flow and autoregulation: a scoping review of the human and animal literature. Front Physiol 2023; 14:1204874. [PMID: 37351255 PMCID: PMC10282505 DOI: 10.3389/fphys.2023.1204874] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 05/25/2023] [Indexed: 06/24/2023] Open
Abstract
Background: Burst suppression (BS) is an electroencephalography (EEG) pattern in which there are isoelectric periods interspersed with bursts of cortical activity. Targeting BS through anaesthetic administration is used as a tool in the neuro-intensive care unit but its relationship with cerebral blood flow (CBF) and cerebral autoregulation (CA) is unclear. We performed a systematic scoping review investigating the effect of BS on CBF and CA in animals and humans. Methods: We searched MEDLINE, BIOSIS, EMBASE, SCOPUS and Cochrane library from inception to August 2022. The data that were collected included study population, methods to induce and measure BS, and the effect on CBF and CA. Results: Overall, there were 66 studies that were included in the final results, 41 of which examined animals, 24 of which examined humans, and 1 of which examined both. In almost all the studies, BS was induced using an anaesthetic. In most of the animal and human studies, BS was associated with a decrease in CBF and cerebral metabolism, even if the mean arterial pressure remained constant. The effect on CA during periods of stress (hypercapnia, hypothermia, etc.) was variable. Discussion: BS is associated with a reduction in cerebral metabolic demand and CBF, which may explain its usefulness in patients with brain injury. More evidence is needed to elucidate the connection between BS and CA.
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Affiliation(s)
- A. Zohaib Siddiqi
- Department of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Logan Froese
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Alwyn Gomez
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Amanjyot Singh Sainbhi
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Kevin Stein
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Kangyun Park
- Undergraduate Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Nuray Vakitbilir
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Frederick A. Zeiler
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, United Kingdom
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11
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Rajajee V, Muehlschlegel S, Wartenberg KE, Alexander SA, Busl KM, Chou SHY, Creutzfeldt CJ, Fontaine GV, Fried H, Hocker SE, Hwang DY, Kim KS, Madzar D, Mahanes D, Mainali S, Meixensberger J, Montellano F, Sakowitz OW, Weimar C, Westermaier T, Varelas PN. Guidelines for Neuroprognostication in Comatose Adult Survivors of Cardiac Arrest. Neurocrit Care 2023; 38:533-563. [PMID: 36949360 PMCID: PMC10241762 DOI: 10.1007/s12028-023-01688-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 01/30/2023] [Indexed: 03/24/2023]
Abstract
BACKGROUND Among cardiac arrest survivors, about half remain comatose 72 h following return of spontaneous circulation (ROSC). Prognostication of poor neurological outcome in this population may result in withdrawal of life-sustaining therapy and death. The objective of this article is to provide recommendations on the reliability of select clinical predictors that serve as the basis of neuroprognostication and provide guidance to clinicians counseling surrogates of comatose cardiac arrest survivors. METHODS A narrative systematic review was completed using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Candidate predictors, which included clinical variables and prediction models, were selected based on clinical relevance and the presence of an appropriate body of evidence. The Population, Intervention, Comparator, Outcome, Timing, Setting (PICOTS) question was framed as follows: "When counseling surrogates of comatose adult survivors of cardiac arrest, should [predictor, with time of assessment if appropriate] be considered a reliable predictor of poor functional outcome assessed at 3 months or later?" Additional full-text screening criteria were used to exclude small and lower-quality studies. Following construction of the evidence profile and summary of findings, recommendations were based on four GRADE criteria: quality of evidence, balance of desirable and undesirable consequences, values and preferences, and resource use. In addition, good practice recommendations addressed essential principles of neuroprognostication that could not be framed in PICOTS format. RESULTS Eleven candidate clinical variables and three prediction models were selected based on clinical relevance and the presence of an appropriate body of literature. A total of 72 articles met our eligibility criteria to guide recommendations. Good practice recommendations include waiting 72 h following ROSC/rewarming prior to neuroprognostication, avoiding sedation or other confounders, the use of multimodal assessment, and an extended period of observation for awakening in patients with an indeterminate prognosis, if consistent with goals of care. The bilateral absence of pupillary light response > 72 h from ROSC and the bilateral absence of N20 response on somatosensory evoked potential testing were identified as reliable predictors. Computed tomography or magnetic resonance imaging of the brain > 48 h from ROSC and electroencephalography > 72 h from ROSC were identified as moderately reliable predictors. CONCLUSIONS These guidelines provide recommendations on the reliability of predictors of poor outcome in the context of counseling surrogates of comatose survivors of cardiac arrest and suggest broad principles of neuroprognostication. Few predictors were considered reliable or moderately reliable based on the available body of evidence.
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Affiliation(s)
- Venkatakrishna Rajajee
- Departments of Neurology and Neurosurgery, 3552 Taubman Health Care Center, SPC 5338, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5338, USA.
| | - Susanne Muehlschlegel
- Departments of Neurology, Anesthesiology, and Surgery, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | | | - Katharina M Busl
- Departments of Neurology and Neurosurgery, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Sherry H Y Chou
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Gabriel V Fontaine
- Departments of Pharmacy and Neurosciences, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Herbert Fried
- Department of Neurosurgery, Denver Health Medical Center, Denver, CO, USA
| | - Sara E Hocker
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - David Y Hwang
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Keri S Kim
- Pharmacy Practice, University of Illinois, Chicago, IL, USA
| | - Dominik Madzar
- Department of Neurology, University of Erlangen, Erlangen, Germany
| | - Dea Mahanes
- Departments of Neurology and Neurosurgery, University of Virginia Health, Charlottesville, VA, USA
| | - Shraddha Mainali
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | | | | | - Oliver W Sakowitz
- Department of Neurosurgery, Neurosurgery Center Ludwigsburg-Heilbronn, Ludwigsburg, Germany
| | - Christian Weimar
- Institute of Medical Informatics, Biometry, and Epidemiology, University Hospital Essen, Essen, Germany
- BDH-Clinic Elzach, Elzach, Germany
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12
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Morris NA, Sarwal A. Neurologic Complications of Critical Medical Illness. Continuum (Minneap Minn) 2023; 29:848-886. [PMID: 37341333 DOI: 10.1212/con.0000000000001278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
OBJECTIVE This article reviews the neurologic complications encountered in patients admitted to non-neurologic intensive care units, outlines various scenarios in which a neurologic consultation can add to the diagnosis or management of a critically ill patient, and provides advice on the best diagnostic approach in the evaluation of these patients. LATEST DEVELOPMENTS Increasing recognition of neurologic complications and their adverse impact on long-term outcomes has led to increased neurology involvement in non-neurologic intensive care units. The COVID-19 pandemic has highlighted the importance of having a structured clinical approach to neurologic complications of critical illness as well as the critical care management of patients with chronic neurologic disabilities. ESSENTIAL POINTS Critical illness is often accompanied by neurologic complications. Neurologists need to be aware of the unique needs of critically ill patients, especially the nuances of the neurologic examination, challenges in diagnostic testing, and neuropharmacologic aspects of commonly used medications.
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13
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Admiraal MM, van Merkerk M, Horn J, Koelman JHTM, Hofmeijer J, Hoedemaekers CW, van Rootselaar AF. EEG in a four-electrode frontotemporal montage reliably predicts outcome after cardiac arrest. Resuscitation 2023; 188:109817. [PMID: 37164176 DOI: 10.1016/j.resuscitation.2023.109817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/20/2023] [Accepted: 04/24/2023] [Indexed: 05/12/2023]
Abstract
AIM To increase efficiency of continuous EEG monitoring for prognostication of neurological outcome in patients after cardiac arrest, we investigated the reliability of EEG in a four-electrode frontotemporal (4-FT) montage, compared to our standard nine-electrode (9-EL) montage. METHODS EEG recorded with Ag/AgCl cup-electrodes at 12 and/or 24h after cardiac arrest of 153 patients was available from a previous study. 220 EEG epochs of 5 minutes were reexamined in a 4-FT montage according to the ACNS criteria. Background classification was compared to the available 9-EL classification using Cohens kappa. Reliability for prognostication was assessed in 151 EEG epochs at 24h after CA using sensitivity and specificity for prediction of poor (cerebral performance categories (CPC) 3-5) and good (CPC 1-2) neurological outcome. RESULTS Agreement for EEG background classification between the two montages was substantial with a kappa of 0.85 (95%-CI 0.81-0.90). Specificity for prediction of poor outcome was 100% (95%-CI 95-100) for both montages, sensitivity was 31% (95%-CI 21-43) for the 4-FT montage and 35% (95%-CI 24-47) for the 9-EL montage. Good outcome was predicted with 65% specificity (95%-CI 53-76) and 81% sensitivity (95%-CI 71-89) for the 4-FT montage, similar to the 9-EL montage. CONCLUSION In this cohort, EEG background patterns determined in a four-electrode frontotemporal montage predict both poor and good outcome after CA with similar reliability. Our results may contribute to decreasing the workload of EEG monitoring in patients after CA without compromising reliability of outcome prediction. However, validation in a larger cohort is necessary, as is a multimodal approach.
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Affiliation(s)
- Marjolein M Admiraal
- Amsterdam UMC, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
| | - Myrthe van Merkerk
- Amsterdam UMC, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Janneke Horn
- Amsterdam UMC, University of Amsterdam, Department of Intensive Care, Amsterdam Neuroscience Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, The Netherlands
| | - J H T M Koelman
- Amsterdam UMC, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - J Hofmeijer
- Rijnstate Hospital, Department of Neurology, Arnhem, The Netherlands; University of Twente, Faculty of Science and Technology, Clinical Neurophysiology, Enschede, The Netherlands
| | - C W Hoedemaekers
- Radboud University Medical Center, Department of Intensive Care, Nijmegen, The Netherlands
| | - Anne-Fleur van Rootselaar
- Amsterdam UMC, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
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14
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Coppler PJ, Elmer J, Doshi A, Guyette FX, Okubo M, Ratay C, Frisch AN, Steinberg A, Weissman A, Arias V, Drumheller BC, Flickinger KL, Faro J, Schmidhofer M, Rhinehart ZJ, Hansra BS, Fong-Isariyawongse J, Barot N, Baldwin ME, Murat Kaynar A, Darby JM, Shutter LA, Mettenburg J, Callaway CW. Duration of cardiopulmonary resuscitation and phenotype of post-cardiac arrest brain injury. Resuscitation 2023; 188:109823. [PMID: 37164175 DOI: 10.1016/j.resuscitation.2023.109823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 04/17/2023] [Accepted: 05/01/2023] [Indexed: 05/12/2023]
Abstract
BACKGROUND Patients resuscitated from cardiac arrest have variable severity of primary hypoxic ischemic brain injury (HIBI). Signatures of primary HIBI on brain imaging and electroencephalography (EEG) include diffuse cerebral edema and burst suppression with identical bursts (BSIB). We hypothesize distinct phenotypes of primary HIBI are associated with increasing cardiopulmonary resuscitation (CPR) duration. METHODS We identified from our prospective registry of both in-and out-of-hospital CA patients treated between January 2010 to January 2020 for this cohort study. We abstracted CPR duration, neurological examination, initial brain computed tomography gray to white ratio (GWR), and initial EEG pattern. We considered four phenotypes on presentation: awake; comatose with neither BSIB nor cerebral edema (non-malignant coma); BSIB; and cerebral edema (GWR ≤ 1.20). BSIB and cerebral edema were considered as non-mutually exclusive outcomes. We generated predicted probabilities of brain injury phenotype using localized regression. RESULTS We included 2,440 patients, of whom 545 (23%) were awake, 1,065 (44%) had non-malignant coma, 548 (23%) had BSIB and 438 (18%) had cerebral edema. Only 92 (4%) had both BSIB and edema. Median CPR duration was 16 [IQR 8-28] minutes. Median CPR duration increased in a stepwise manner across groups: awake 6 [3-13] minutes; non-malignant coma 15 [8-25] minutes; BSIB 21 [13-31] minutes; cerebral edema 32 [22-46] minutes. Predicted probability of phenotype changes over time. CONCLUSIONS Brain injury phenotype is related to CPR duration, which is a surrogate for severity of HIBI. The sequence of most likely primary HIBI phenotype with progressively longer CPR duration is awake, coma without BSIB or edema, BSIB, and finally cerebral edema.
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Affiliation(s)
- Patrick J Coppler
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jonathan Elmer
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ankur Doshi
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Francis X Guyette
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Masashi Okubo
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Cecelia Ratay
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Adam N Frisch
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexis Steinberg
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexandra Weissman
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Valerie Arias
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Byron C Drumheller
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - John Faro
- Department of Medicine, Soin Medical Center - Kettering Health, Beavercreek, OH, USA
| | - Mark Schmidhofer
- Department of Medicine, Division of Cardiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zachary J Rhinehart
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Barinder S Hansra
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Medicine, Division of Cardiology, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Niravkumar Barot
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria E Baldwin
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - A Murat Kaynar
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joseph M Darby
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lori A Shutter
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joseph Mettenburg
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Clifton W Callaway
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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15
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Elmer J, Kurz MC, Coppler PJ, Steinberg A, DeMasi S, De-Arteaga M, Simon N, Zadorozny VI, Flickinger KL, Callaway CW. Time to Awakening and Self-Fulfilling Prophecies After Cardiac Arrest. Crit Care Med 2023; 51:503-512. [PMID: 36752628 PMCID: PMC10023349 DOI: 10.1097/ccm.0000000000005790] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
OBJECTIVES Withdrawal of life-sustaining therapies for perceived poor neurologic prognosis (WLST-N) is common after resuscitation from cardiac arrest and may bias outcome estimates from models trained using observational data. We compared several approaches to outcome prediction with the goal of identifying strategies to quantify and reduce this bias. DESIGN Retrospective observational cohort study. SETTING Two academic medical centers ("UPMC" and "University of Alabama Birmingham" [UAB]). PATIENTS Comatose adults resuscitated from cardiac arrest. INTERVENTION None. MEASUREMENTS AND MAIN RESULTS As potential predictors, we considered clinical, laboratory, imaging, and quantitative electroencephalography data available early after hospital arrival. We followed patients until death, discharge, or awakening from coma. We used penalized Cox regression with a least absolute shrinkage and selection operator penalty and five-fold cross-validation to predict time to awakening in UPMC patients and then externally validated the model in UAB patients. This model censored patients after WLST-N, considering subsequent potential for awakening to be unknown. Next, we developed a penalized logistic model predicting awakening, which treated failure to awaken after WLST-N as a true observed outcome, and a separate logistic model predicting WLST-N. We scaled and centered individual patients' Cox and logistic predictions for awakening to allow direct comparison and then explored the difference in predictions across probabilities of WLST-N. Overall, 1,254 patients were included, and 29% awakened. Cox models performed well (mean area under the curve was 0.93 in the UPMC test sets and 0.83 in external validation). Logistic predictions of awakening were systematically more pessimistic than Cox-based predictions for patients at higher risk of WLST-N, suggesting potential for self-fulfilling prophecies to arise when failure to awaken after WLST-N is considered as the ground truth outcome. CONCLUSIONS Compared with traditional binary outcome prediction, censoring outcomes after WLST-N may reduce potential for bias and self-fulfilling prophecies.
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Affiliation(s)
- Jonathan Elmer
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Michael C. Kurz
- Department of Emergency Medicine, University of Alabama-Birmingham Birmingham Alabama USA
- Department of Surgery, Division of Acute Care Surgery, University of Alabama-Birmingham Birmingham Alabama USA
- Center for Injury Science, University of Alabama-Birmingham Birmingham Alabama USA
| | - Patrick J Coppler
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Alexis Steinberg
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Stephanie DeMasi
- Department of Emergency Medicine, Virginia Comonwealth University, Richmond, Virginia, USA
| | - Maria De-Arteaga
- Information, Risk and Operations Management Department, McCombs School of Business, University of Texas at Austin, Austin, TX USA
| | - Noah Simon
- Department of Biostatistics, University of Washington School of Public Health, Seattle, WA USA
| | | | - Katharyn L. Flickinger
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Clifton W Callaway
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
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16
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Iannucci C, Hoehne SN, Murthy VD, Dutil G, Maiolini A. Successful resuscitation and neurological monitoring of a dog with out-of-hospital cardiopulmonary arrest due to pentobarbital overdose. J Vet Emerg Crit Care (San Antonio) 2023; 33:393-400. [PMID: 36815742 DOI: 10.1111/vec.13283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 02/12/2022] [Accepted: 03/28/2022] [Indexed: 02/24/2023]
Abstract
OBJECTIVE To describe the clinical signs, electroencephalographic (EEG) findings, treatment, and outcome in a dog after successful resuscitation from out-of-hospital cardiopulmonary arrest (OHCA) induced by pentobarbital intoxication. CASE SUMMARY A 10-year-old, male intact Jack Russell Terrier was referred for management of refractory status epilepticus and presented dead on arrival. After 7 minutes of cardiopulmonary resuscitation, return of spontaneous circulation was achieved, but the dog remained comatose, apneic, and lacked brainstem reflexes on neurological examination 6 hours following resuscitation. Magnetic resonance imaging showed polioencephalomalacia consistent with prolonged epileptiform activity, and EEG was initially concerning for electrocerebral inactivity. Following supportive care that included short-term mechanical ventilation, the dog made a full recovery and was discharged from the hospital alive 7 days postresuscitation. It was later revealed that the dog had been administered an unknown amount of pentobarbital during transportation, which likely contributed to the OHCA, clinical, and EEG findings. NEW INFORMATION PROVIDED This is the first report to describe the full recovery and hospital discharge of a dog suffering OHCA and the first description of EEG findings in a clinical veterinary patient following cardiopulmonary arrest and successful resuscitation. Factors likely contributing to successful patient outcome and potential benefits and limitations of EEG in monitoring postcardiac arrest patients are discussed.
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Affiliation(s)
- Claudia Iannucci
- Department of Clinical Veterinary Medicine, Division of Small Animal Emergency and Critical Care, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
| | - Sabrina N Hoehne
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA
| | - Vishal D Murthy
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA
| | - Guillaume Dutil
- Department of Clinical Veterinary Medicine, Division of Neurology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Arianna Maiolini
- Department of Clinical Veterinary Medicine, Division of Neurology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
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17
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Elmashala A, Busl KM, Maciel CB. Will shifting the lens let us see more clearly when prognosticating after cardiac arrest, or do we need new glasses? Resuscitation 2023; 182:109667. [PMID: 36565947 DOI: 10.1016/j.resuscitation.2022.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 12/11/2022] [Indexed: 12/24/2022]
Affiliation(s)
- Amjad Elmashala
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA
| | - Katharina M Busl
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA; Department of Neurosurgery, University of Florida College of Medicine, Gainesville, FL 32611, USA
| | - Carolina B Maciel
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA; Department of Neurosurgery, University of Florida College of Medicine, Gainesville, FL 32611, USA; Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Neurology, University of Utah, Salt Lake City, UT 84132, USA.
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18
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Fisch U, Jünger AL, Hert L, Rüegg S, Sutter R. Therapeutically induced EEG burst-suppression pattern to treat refractory status epilepticus—what is the evidence? ZEITSCHRIFT FÜR EPILEPTOLOGIE 2022. [DOI: 10.1007/s10309-022-00539-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
AbstractCurrent guidelines advocate to treat refractory status epilepticus (RSE) with continuously administered anesthetics to induce an artificial coma if first- and second-line antiseizure drugs have failed to stop seizure activity. A common surrogate for monitoring the depth of the artificial coma is the appearance of a burst-suppression pattern (BS) in the EEG. This review summarizes the current knowledge on the origin and neurophysiology of the BS phenomenon as well as the evidence from the literature for the presumed benefit of BS as therapy in adult patients with RSE.
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19
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A Simplified Electroencephalography Montage and Interpretation for Evaluation of Comatose Patients in the ICU. Crit Care Explor 2022; 4:e0781. [DOI: 10.1097/cce.0000000000000781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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20
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Repetitive Electroencephalography as Biomarker for the Prediction of Survival in Patients with Post-Hypoxic Encephalopathy. J Clin Med 2022; 11:jcm11216253. [DOI: 10.3390/jcm11216253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 11/07/2022] Open
Abstract
Predicting survival in patients with post-hypoxic encephalopathy (HE) after cardiopulmonary resuscitation is a challenging aspect of modern neurocritical care. Here, continuous electroencephalography (cEEG) has been established as the gold standard for neurophysiological outcome prediction. Unfortunately, cEEG is not comprehensively available, especially in rural regions and developing countries. The objective of this monocentric study was to investigate the predictive properties of repetitive EEGs (rEEGs) with respect to 12-month survival based on data for 199 adult patients with HE, using log-rank and multivariate Cox regression analysis (MCRA). A total number of 59 patients (29.6%) received more than one EEG during the first 14 days of acute neurocritical care. These patients were analyzed for the presence of and changes in specific EEG patterns that have been shown to be associated with favorable or poor outcomes in HE. Based on MCRA, an initially normal amplitude with secondary low-voltage EEG remained as the only significant predictor for an unfavorable outcome, whereas all other relevant parameters identified by univariate analysis remained non-significant in the model. In conclusion, rEEG during early neurocritical care may help to assess the prognosis of HE patients if cEEG is not available.
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21
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Neurological Prognostication Using Raw EEG Patterns and Spectrograms of Frontal EEG in Cardiac Arrest Patients. J Clin Neurophysiol 2022; 39:427-433. [DOI: 10.1097/wnp.0000000000000787] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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22
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Grindegård L, Cronberg T, Backman S, Blennow K, Dankiewicz J, Friberg H, Hassager C, Horn J, Kjaer TW, Kjaergaard J, Kuiper M, Mattsson-Carlgren N, Nielsen N, van Rootselaar AF, Rossetti AO, Stammet P, Ullén S, Zetterberg H, Westhall E, Moseby-Knappe M. Association Between EEG Patterns and Serum Neurofilament Light After Cardiac Arrest. Neurology 2022; 98:e2487-e2498. [PMID: 35470143 PMCID: PMC9231840 DOI: 10.1212/wnl.0000000000200335] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 02/21/2022] [Indexed: 01/09/2023] Open
Abstract
Background and Objectives EEG is widely used for prediction of neurologic outcome after cardiac arrest. To better understand the relationship between EEG and neuronal injury, we explored the association between EEG and neurofilament light (NfL) as a marker of neuroaxonal injury, evaluated whether highly malignant EEG patterns are reflected by high NfL levels, and explored the association of EEG backgrounds and EEG discharges with NfL. Methods We performed a post hoc analysis of the Target Temperature Management After Out-of-Hospital Cardiac Arrest trial. Routine EEGs were prospectively performed after the temperature intervention ≥36 hours postarrest. Patients who awoke or died prior to 36 hours postarrest were excluded. EEG experts blinded to clinical information classified EEG background, amount of discharges, and highly malignant EEG patterns according to the standardized American Clinical Neurophysiology Society terminology. Prospectively collected serum samples were analyzed for NfL after trial completion. The highest available concentration at 48 or 72 hours postarrest was used. Results A total of 262/939 patients with EEG and NfL data were included. Patients with highly malignant EEG patterns had 2.9 times higher NfL levels than patients with malignant patterns and NfL levels were 13 times higher in patients with malignant patterns than those with benign patterns (95% CI 1.4–6.1 and 6.5–26.2, respectively; effect size 0.47; p < 0.001). Both background and the amount of discharges were independently strongly associated with NfL levels (p < 0.001). The EEG background had a stronger association with NfL levels than EEG discharges (R2 = 0.30 and R2 = 0.10, respectively). NfL levels in patients with a continuous background were lower than for any other background (95% CI for discontinuous, burst-suppression, and suppression, respectively: 2.26–18.06, 3.91–41.71, and 5.74–41.74; effect size 0.30; p < 0.001 for all). NfL levels did not differ between suppression and burst suppression. Superimposed discharges were only associated with higher NfL levels if the EEG background was continuous. Discussion Benign, malignant, and highly malignant EEG patterns reflect the extent of brain injury as measured by NfL in serum. The extent of brain injury is more strongly related to the EEG background than superimposed discharges. Combining EEG and NfL may be useful to better identify patients misclassified by single methods. Trial Registration Information ClinicalTrials.gov NCT01020916.
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Affiliation(s)
- Linnéa Grindegård
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China.
| | - Tobias Cronberg
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Sofia Backman
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Kaj Blennow
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Josef Dankiewicz
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Hans Friberg
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Christian Hassager
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Janneke Horn
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Troels W Kjaer
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Jesper Kjaergaard
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Michael Kuiper
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Niklas Mattsson-Carlgren
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Niklas Nielsen
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Anne-Fleur van Rootselaar
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Andrea O Rossetti
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Pascal Stammet
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Susann Ullén
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Henrik Zetterberg
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Erik Westhall
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Marion Moseby-Knappe
- From Neurology (L.G., T.C., N.M.-C., M.M.-K.), Clinical Neurophysiology (S.B., E.W.), Cardiology (J.D.), and Anaesthesia and Intensive Care (H.F.), Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Malmö; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Cardiology (C.H.), Rigshospitalet and Department of Clinical Medicine, University of Copenhagen, Denmark; Departments of Intensive Care (J.H.) and Neurology/Clinical Neurophysiology (A.-F-V.R.), Amsterdam Neuroscience, Amsterdam UMC, Academic Medical Center, University of Amsterdam, the Netherlands; Departments of Clinical Neurophysiology (T.W.K.) and Cardiology (J.K.), Rigshospitalet University Hospital, Copenhagen, Denmark; Department of Intensive Care (M.K.), Medical Center Leeuwarden, the Netherlands; Clinical Memory Research Unit, Faculty of Medicine (N.M.-C.), and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University; Anaesthesia and Intensive Care, Department of Clinical Sciences Lund (N.N.), Lund University, Helsingborg Hospital, Sweden; Department of Neurology (A.O.R.), CHUV and University of Lausanne, Switzerland; Department of Anesthesia and Intensive Care (P.S.), Centre Hospitalier de Luxembourg; Department of Life Sciences and Medicine (P.S.), Faculty of Science, Technology and Medicine, University of Luxembourg; Clinical Studies Sweden (S.U.), Skåne University Hospital, Lund; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology; UK Dementia Research Institute at UCL (H.Z.), London, UK; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
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23
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Curley WH, Comanducci A, Fecchio M. Conventional and Investigational Approaches Leveraging Clinical EEG for Prognosis in Acute Disorders of Consciousness. Semin Neurol 2022; 42:309-324. [PMID: 36100227 DOI: 10.1055/s-0042-1755220] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
Prediction of recovery of consciousness after severe brain injury is difficult and limited by a lack of reliable, standardized biomarkers. Multiple approaches for analysis of clinical electroencephalography (EEG) that shed light on prognosis in acute severe brain injury have emerged in recent years. These approaches fall into two major categories: conventional characterization of EEG background and quantitative measurement of resting state or stimulus-induced EEG activity. Additionally, a small number of studies have associated the presence of electrophysiologic sleep features with prognosis in the acute phase of severe brain injury. In this review, we focus on approaches for the analysis of clinical EEG that have prognostic significance and that could be readily implemented with minimal additional equipment in clinical settings, such as intensive care and intensive rehabilitation units, for patients with acute disorders of consciousness.
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Affiliation(s)
- William H Curley
- Harvard Medical School, Boston, Massachusetts.,Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts
| | - Angela Comanducci
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.,Università Campus Bio-Medico di Roma, Rome, Italy
| | - Matteo Fecchio
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts
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24
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Sirmpilatze N, Mylius J, Ortiz-Rios M, Baudewig J, Paasonen J, Golkowski D, Ranft A, Ilg R, Gröhn O, Boretius S. Spatial signatures of anesthesia-induced burst-suppression differ between primates and rodents. eLife 2022; 11:74813. [PMID: 35607889 PMCID: PMC9129882 DOI: 10.7554/elife.74813] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 05/01/2022] [Indexed: 01/19/2023] Open
Abstract
During deep anesthesia, the electroencephalographic (EEG) signal of the brain alternates between bursts of activity and periods of relative silence (suppressions). The origin of burst-suppression and its distribution across the brain remain matters of debate. In this work, we used functional magnetic resonance imaging (fMRI) to map the brain areas involved in anesthesia-induced burst-suppression across four mammalian species: humans, long-tailed macaques, common marmosets, and rats. At first, we determined the fMRI signatures of burst-suppression in human EEG-fMRI data. Applying this method to animal fMRI datasets, we found distinct burst-suppression signatures in all species. The burst-suppression maps revealed a marked inter-species difference: in rats, the entire neocortex engaged in burst-suppression, while in primates most sensory areas were excluded—predominantly the primary visual cortex. We anticipate that the identified species-specific fMRI signatures and whole-brain maps will guide future targeted studies investigating the cellular and molecular mechanisms of burst-suppression in unconscious states. The development of anesthesia was a significant advance in medicine. It allows individuals to undergo surgery without feeling pain or remembering the experience. But scientists still do not know how anesthesia works. During anesthesia, scientists have measured brain activity using electroencephalograms (EEG) and found that the brain appears to turn on and off. Comatose patients also have similar switches between bursts of electrical activity and periods of silence. This burst-suppression pattern may be related to unconsciousness. But scientists still have many questions about how anesthesia causes burst-suppression. One challenge is that while an EEG can tell scientists when the brain turns on and off, it does not show exactly where this occurs. Another imaging method called functional Magnetic Resonance Imaging (fMRI) may fill this gap by allowing scientists to map where the brain activity occurs. Sirmpilatze et al. have created detailed maps of burst-suppression in humans, primates, and rats under anesthesia by analyzing brain scans using fMRI. In rats, the entire outer layer or cortex of the brain underwent a synchronized pattern of burst-suppression. In humans and primates, areas of the brain like those responsible for eyesight did not follow the rest of the cortex in switching on and off. The experiments reveal crucial differences in how rats and humans and other primates respond to anesthesia. The fMRI mapping technique Sirmpilatze et al. created may help scientists learn more about these differences and why some parts of human brains do not undergo burst-suppression. This may help scientists learn more about unconsciousness and help improve anesthesia or the care of comatose patients.
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Affiliation(s)
- Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany.,Georg-August University of Göttingen, Göttingen, Germany.,International Max Planck Research School for Neurosciences, Göttingen, Germany
| | - Judith Mylius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Michael Ortiz-Rios
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Jaakko Paasonen
- A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Daniel Golkowski
- Department of Neurology, Klinikum Rechts der Isar der Technischen Universität München, Munich, Germany.,Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care Medicine, Klinikum Rechts der Isar der Technischen Universität München, Munich, Germany
| | - Rüdiger Ilg
- Department of Neurology, Klinikum Rechts der Isar der Technischen Universität München, Munich, Germany.,Department of Neurology, Asklepios Stadtklinik Bad Tölz, Bad Tölz, Germany
| | - Olli Gröhn
- A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany.,Georg-August University of Göttingen, Göttingen, Germany.,International Max Planck Research School for Neurosciences, Göttingen, Germany.,Leibniz Science Campus Primate Cognition, Göttingen, Germany
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25
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Nadjar Y, Levy P, Nguyen-Michel VH, Luyt CE, Puybasset L, Navarro V. Prognostic value of electroencephalographic paroxysms in post-anoxic coma: A new regularity EEG-based score. Neurophysiol Clin 2022; 52:223-231. [PMID: 35490145 DOI: 10.1016/j.neucli.2022.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 03/17/2022] [Accepted: 03/18/2022] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVES Several electroencephalographic (EEG) features -mainly the reactivity of background activity-have been suggested as reliable predictors of outcome for patients with post-anoxic coma (PAC). However, EEG in PAC often contains abundant EEG paroxysms (EP) that may hinder the detection of background EEG activity. We aimed to identify the features, among the different paroxysmal and non-paroxysmal EEG patterns, that may predict the outcome of patients with PAC. METHODS We retrospectively reviewed the clinical and EEG characteristics of 67 patients with PAC and selected those with abundant EP. We classified EP according to several features and assessed their prognostic value for survival at 15 days. We calculated a global regularity score, as the sum of the value (1 if regular, 0 if not) attributed to each of 4 features of EP (duration, morphology, amplitude, and frequency). RESULTS The 35 patient-group with abundant EP showed a higher mortality than the group without abundant EP. Among 12 features of EP, four regularity features (regularity of EP duration, morphology, amplitude, and global regularity score) had a poor prognostic value. A global regularity score ≥ 3 showed a positive predictive value of 100 % for a poor outcome and a negative predictive value of 54 %, with good interrater consistency (Cohen's kappa = .63). CONCLUSIONS The presence of EP and their regularity features in PAC patients are strongly associated with poor outcome. We propose a global regularity score, easily derived from visual EEG inspection, that may be a reliable prognostic tool for these patients. Prospective and larger studies are needed to confirm these findings.
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Affiliation(s)
- Yann Nadjar
- AP-HP, Epileptology Unit and Clinical Neurophysiology Department, Pitié-Salpêtrière Hospital, DMU Neuroscience, Paris 75013, France
| | - Pierre Levy
- AP-HP, Public Health Departement and Clinical Neurophysiology Unit, Tenon Hospital, Paris, France
| | - Vi-Huong Nguyen-Michel
- AP-HP, Epileptology Unit and Clinical Neurophysiology Department, Pitié-Salpêtrière Hospital, DMU Neuroscience, Paris 75013, France
| | - Charles-Edouard Luyt
- AP-HP, Medical Intensive Care Department, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Université, Paris, France
| | - Louis Puybasset
- AP-HP, Neurosurgical Intensive Care Department, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Université, Paris, France
| | - Vincent Navarro
- AP-HP, Epileptology Unit and Clinical Neurophysiology Department, Pitié-Salpêtrière Hospital, DMU Neuroscience, Paris 75013, France; Sorbonne Université, Paris, France; Center of Reference for Rare Epilepsies, Pitié-Salpêtrière Hospital, Paris, France; Paris Brain Institute, ICM, INSERM, CNRS, sorbonne Université, Paris, France.
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26
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Elmer J, Liu C, Pease M, Arefan D, Coppler PJ, Flickinger K, Mettenburg JM, Baldwin ME, Barot N, Wu S. Deep learning of early brain imaging to predict post-arrest electroencephalography. Resuscitation 2022; 172:17-23. [PMID: 35041875 PMCID: PMC8923981 DOI: 10.1016/j.resuscitation.2022.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 01/05/2022] [Accepted: 01/06/2022] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Guidelines recommend use of computerized tomography (CT) and electroencephalography (EEG) in post-arrest prognostication. Strong associations between CT and EEG might obviate the need to acquire both modalities. We quantified these associations via deep learning. METHODS We performed a single-center, retrospective study including comatose patients hospitalized after cardiac arrest. We extracted brain CT DICOMs, resized and registered each to a standard anatomical atlas, performed skull stripping and windowed images to optimize contrast of the gray-white junction. We classified initial EEG as generalized suppression, other highly pathological findings or benign activity. We extracted clinical information available on presentation from our prospective registry. We trained three machine learning (ML) models to predict EEG from clinical covariates. We used three state-of-the-art approaches to build multi-headed deep learning models using similar model architectures. Finally, we combined the best performing clinical and imaging models. We evaluated discrimination in test sets. RESULTS We included 500 patients, of whom 218 (44%) had benign EEG findings, 135 (27%) showed generalized suppression and 147 (29%) had other highly pathological findings that were most commonly (93%) burst suppression with identical bursts. Clinical ML models had moderate discrimination (test set AUCs 0.73-0.80). Image-based deep learning performed worse (test set AUCs 0.51-0.69), particularly discriminating benign from highly pathological findings. Adding image-based deep learning to clinical models improved prediction of generalized suppression due to accurate detection of severe cerebral edema. DISCUSSION CT and EEG provide complementary information about post-arrest brain injury. Our results do not support selective acquisition of only one of these modalities, except in the most severely injured patients.
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Affiliation(s)
- Jonathan Elmer
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Neurology Division, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Chang Liu
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Matthew Pease
- Department of Neurosurgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dooman Arefan
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Patrick J. Coppler
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Katharyn Flickinger
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Joseph M. Mettenburg
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Maria E. Baldwin
- Department of Neurology, Pittsburgh VA Medical Center, Pittsburgh, PA, USA
| | - Niravkumar Barot
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Shandong Wu
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA,Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA,Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA,Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA
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27
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Critical care EEG standardized nomenclature in clinical practice: Strengths, limitations, and outlook on the example of prognostication after cardiac arrest. Clin Neurophysiol Pract 2022; 6:149-154. [PMID: 35112033 PMCID: PMC8790140 DOI: 10.1016/j.cnp.2021.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 01/08/2021] [Accepted: 03/03/2021] [Indexed: 11/21/2022] Open
Abstract
Optimal use of the ACNS nomenclature implies integration of clinical information. Knowledge of pathophysiological mechanisms of EEG patterns may help interpretation. Standardized therapeutic procedures for critical care patients are needed.
We discuss the achievements of the ACNS critical care EEG nomenclature proposed in 2013 and, from a clinical angle, outline some limitations regarding translation into treatment implications. While the recently proposed updated 2021 version of the nomenclature will probable improve some uncertainty areas, a refined understanding of the mechanisms at the origin of the EEG patterns, and a multimodal integration of the nomenclature to the clinical context may help improving the rationale supporting therapeutic procedures. We illustrate these aspects on prognostication after cardiac arrest.
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Key Words
- ACNS, American Clinical Neurophysiology Society
- American Clinical Neurophysiology Society (ACNS) Standardized Terminology
- BIRD, Brief potentially ictal rhythmic discharge
- BS, Burst suppression
- Burst suppression
- CA, Cardiac arrest
- Cardiac arrest (CA)
- DWI, diffusion-weighted MRI
- ESI, electric source imaging
- GPD
- GPD, generalized periodic discharge
- GRDA, generalized rhythmic delta activity
- ICU, Intensive care unit
- ICU-EEG, intensive care unit-electroencephalography
- IIC, Ictal-Interictal Continuum
- Ictal-Interictal Continuum
- LPD, Lateralized periodic discharge
- MEG, Magneto-electroencephalography
- NCSE, Non-Convulsive Status Epilepticus
- NSE, Serum neuron-specific enolase
- PET, Positron emission tomography
- Prognostication assessment
- SE, Status epilepticus
- SPECT, Single Photon Emission Computed Tomography
- SSEP, Somatosensory evoked potentials
- WLST, Withdraw of life sustaining treatment
- fMRI, functional MRI
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28
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Nutma S, Tjepkema-Cloostermans MC, Ruijter BJ, Tromp SC, van den Bergh WM, Foudraine NA, H M Kornips F, Drost G, Scholten E, Strang A, Beishuizen A, J A M van Putten M, Hofmeijer J. Effects of targeted temperature management at 33°C vs. 36°C on comatose patients after cardiac arrest stratified by the severity of encephalopathy. Resuscitation 2022; 173:147-153. [PMID: 35122892 DOI: 10.1016/j.resuscitation.2022.01.026] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/24/2022] [Accepted: 01/25/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVES To assess neurological outcome after targeted temperature management (TTM) at 33°C vs. 36°C, stratified by the severity of encephalopathy based on EEG-patterns at 12 and 24h. DESIGN Post hoc analysis of prospective cohort study. SETTING Five Dutch Intensive Care units. PATIENTS 479 adult comatose post-cardiac arrest patients. INTERVENTIONS TTM at 33°C (n=270) or 36°C (n=209) and continuous EEG monitoring. MEASUREMENTS AND MAIN RESULTS Outcome according to the cerebral performance category (CPC) score at 6 months post-cardiac arrest was similar after 33°C and 36°C. However, when stratified by the severity of encephalopathy based on EEG-patterns at 12 and 24h after cardiac arrest, the proportion of good outcome (CPC 1-2) in patients with moderate encephalopathy was significantly larger after TTM at 33°C (66% vs. 45%; Odds Ratios 2.38, 95% CI=1.32-4.30; p=0.004). In contrast, with mild encephalopathy, there was no statistically significant difference in the proportion of patients with good outcome between 33°C and 36°C (88% vs. 81%; OR 1.68, 95% CI=0.65-4.38; p=0.282). Ordinal regression analysis showed a shift towards higher CPC scores when treated with TTM 33°C as compared with 36°C in moderate encephalopathy (cOR 2.39; 95% CI=1.40-4.08; p=0.001), but not in mild encephalopathy (cOR 0.81 95% CI=0.41-1.59; p=0.537). Adjustment for initial cardiac rhythm and cause of arrest did not change this relationship. CONCLUSIONS Effects of TTM probably depend on the severity of encephalopathy in comatose patients after cardiac arrest. These results support inclusion of predefined subgroup analyses based on EEG measures of the severity of encephalopathy in future clinical trials.
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Affiliation(s)
- Sjoukje Nutma
- Departments of Neurology and Clinical Neurophysiology, Medical Spectrum Twente, Enschede; Department of Clinical Neurophysiology, Technical Medical Center, University of Twente, Enschede.
| | | | - Barry J Ruijter
- Department of Clinical Neurophysiology, Technical Medical Center, University of Twente, Enschede
| | - Selma C Tromp
- Departments of Neurology and Clinical Neurophysiology, St Antonius Hospital, Nieuwegein
| | - Walter M van den Bergh
- Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen
| | | | | | - Gea Drost
- Departments of Neurology and Neurosurgery, University Medical Center Groningen, University of Groningen, Groningen
| | - Erik Scholten
- Department of Intensive Care, St Antonius Hospital, Nieuwegein
| | - Aart Strang
- Department of Intensive Care, Rijnstate Hospital, Arnhem
| | | | - Michel J A M van Putten
- Departments of Neurology and Clinical Neurophysiology, Medical Spectrum Twente, Enschede; Department of Clinical Neurophysiology, Technical Medical Center, University of Twente, Enschede
| | - Jeannette Hofmeijer
- Department of Clinical Neurophysiology, Technical Medical Center, University of Twente, Enschede; Department of Neurology, Rijnstate Hospital, Arnhem, the Netherlands
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29
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Bronder J, Cho SM, Geocadin RG, Ritzl EK. Revisiting EEG as part of the multidisciplinary approach to post-cardiac arrest care and prognostication: A review. Resusc Plus 2022; 9:100189. [PMID: 34988537 PMCID: PMC8693464 DOI: 10.1016/j.resplu.2021.100189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/24/2021] [Accepted: 11/26/2021] [Indexed: 11/01/2022] Open
Abstract
Since the 1960s, EEG has been used to assess the neurologic function of patients in the hours and days after cardiac arrest. Accurate and reliable prognostication after cardiac arrest is vital for tailoring aggressive patient care for those with a high likelihood of recovery and setting appropriate goals of care for those who have a high likelihood of a poor outcome. Attempts to define EEG's role in this process has evolved over the years. In this review, we provide important historical context about EEG's use, it's perceived unreliability in the post-cardiac arrest patient in the past and provide a detailed analysis of how this role has changed recently. A review of the 71 most recent and highest quality studies demonstrates that the introduction of a uniform classification and a timed approach to EEG analysis have positioned EEG as a complementary tool in the multimodal approach for prognostication. The review was created and intended for medical staff in the intensive care units and emphasizes EEG patterns and timing which portend both favorable and poor prognoses. Also, the review addresses the overall quality of the existing studies and discusses future directions to address the knowledge gaps in this field.
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Affiliation(s)
- Jay Bronder
- Epilepsy Fellow, Department of Neurology, Johns Hopkins Hospital, 600 N. Wolfe St / Meyer 2-147, Baltimore, MD 21287-7247, USA
| | - Sung-Min Cho
- Neuroscience Critical Care Division, Departments of Neurology, Neurosurgery, and Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Baltimore, MD 21287, USA
| | - Romergryko G Geocadin
- Professor of Neurology, Anesthesiology-Critical Care, Neurosurgery, and Joint Appointment in Medicine, The Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Phipps 455, Baltimore, MD 21287, USA
| | - Eva Katharina Ritzl
- Department of Neurology and Anesthesia and Critical Care Medicine, Johns Hopkins Hospital, 1800 Orleans Street, Suite 3329, Baltimore, MD 21287, USA
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30
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Sandroni C, Cronberg T, Hofmeijer J. EEG monitoring after cardiac arrest. Intensive Care Med 2022; 48:1439-1442. [PMID: 35471582 PMCID: PMC9468095 DOI: 10.1007/s00134-022-06697-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 04/03/2022] [Indexed: 02/04/2023]
Affiliation(s)
- Claudio Sandroni
- Department of Intensive Care, Emergency Medicine and Anaesthesiology, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Rome, Italy.
- Institute of Anaesthesiology and Intensive Care Medicine, Università Cattolica del Sacro Cuore, Largo Francesco Vito, 1, 00168, Rome, Italy.
| | - Tobias Cronberg
- Department of Clinical Sciences Lund, Neurology, Lund University, Skane University Hospital, Lund, Sweden
| | - Jeannette Hofmeijer
- Department of Clinical Neurophysiology, Technical Medical Center, University of Twente, Enschede, The Netherlands
- Department of Neurology, Rijnstate Hospital, Arnhem, The Netherlands
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31
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Zheng WL, Amorim E, Jing J, Wu O, Ghassemi M, Lee JW, Sivaraju A, Pang T, Herman ST, Gaspard N, Ruijter BJ, Tjepkema-Cloostermans MC, Hofmeijer J, van Putten MJAM, Westover MB. Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning. IEEE Trans Biomed Eng 2021; 69:1813-1825. [PMID: 34962860 PMCID: PMC9087641 DOI: 10.1109/tbme.2021.3139007] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches largely rely on snapshots of the EEG, without taking advantage of temporal information. METHODS We present a recurrent deep neural network with the goal of capturing temporal dynamics from longitudinal EEG data to predict long-term neurological outcomes. We utilized a large international dataset of continuous EEG recordings from 1,038 cardiac arrest patients from seven hospitals in Europe and the US. Poor outcome was defined as a Cerebral Performance Category (CPC) score of 3-5, and good outcome as CPC score 0-2 at 3 to 6-months after cardiac arrest. Model performance is evaluated using 5-fold cross validation. RESULTS The proposed approach provides predictions which improve over time, beginning from an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% CI: 0.72-0.81) at 12 hours, and reaching 0.88 (95% CI: 0.85-0.91) by 66 h after cardiac arrest. At 66 h, (sensitivity, specificity) points of interest on the ROC curve for predicting poor outcomes were (32,99)%, (55,95)%, and (62,90)%, (99,23)%, (95,47)%, and (90,62)%; whereas for predicting good outcome, the corresponding operating points were (17,99)%, (47,95)%, (62,90)%, (99,19)%, (95,48)%, (70,90)%. Moreover, the model provides predicted probabilities that closely match the observed frequencies of good and poor outcomes (calibration error 0.04). CONCLUSIONS AND SIGNIFICANCE These findings suggest that accounting for EEG trend information can substantially improve prediction of neurologic outcomes for patients with coma following cardiac arrest.
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32
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Ma K, Bebawy JF. Electroencephalographic Burst-Suppression, Perioperative Neuroprotection, Postoperative Cognitive Function, and Mortality: A Focused Narrative Review of the Literature. Anesth Analg 2021; 135:79-90. [PMID: 34871183 DOI: 10.1213/ane.0000000000005806] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Burst-suppression is an electroencephalographic pattern that results from a diverse array of pathophysiological causes and/or metabolic neuronal suppression secondary to the administration of anesthetic medications. The purpose of this review is to provide an overview of the physiological mechanisms that underlie the burst-suppression pattern and to present in a comprehensive way the available evidence both supporting and in opposition to the clinical use of this electroencephalographic pattern as a therapeutic measure in various perioperative settings.
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Affiliation(s)
- Kan Ma
- From the *Department of Anesthesiology and Pain Medicine, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - John F Bebawy
- Department of Anesthesiology & Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois
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33
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EEG patterns and their correlations with short- and long-term mortality in patients with hypoxic encephalopathy. Clin Neurophysiol 2021; 132:2851-2860. [PMID: 34598037 DOI: 10.1016/j.clinph.2021.07.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 06/29/2021] [Accepted: 07/20/2021] [Indexed: 11/21/2022]
Abstract
OBJECTIVE To analyze the association between electroencephalographic (EEG) patterns and overall, short- and long-term mortality in patients with hypoxic encephalopathy (HE). METHODS Retrospective, mono-center analysis of 199 patients using univariate log-rank tests (LR) and multivariate cox regression (MCR). RESULTS Short-term mortality, defined as death within 30-days post-discharge was 54.8%. Long-term mortality rates were 69.8%, 71.9%, and 72.9%, at 12-, 24-, and 36-months post-HE, respectively. LR revealed a significant association between EEG suppression (SUP) and short-term mortality, and identified low voltage EEG (LV), burst suppression (BSP), periodic discharges (PD) and post-hypoxic status epilepticus (PSE) as well as missing (aBA) or non-reactive background activity (nrBA) as predictors for overall, short- and long-term mortality. MCR indicated SUP, LV, BSP, PD, aBA and nrBA as significantly associated with overall and short-term mortality to varying extents. LV and BSP were significant predictors for long-term mortality in short-term survivors. Rhythmic delta activity, stimulus induced rhythmic, periodic or ictal discharges and sharp waves were not significantly associated with a higher mortality. CONCLUSION The presence of several specific EEG patterns can help to predict overall, short- and long-term mortality in HE patients. SIGNIFICANCE The present findings may help to improve the challenging prognosis estimation in HE patients.
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34
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Rosenthal ES. Seizures, Status Epilepticus, and Continuous EEG in the Intensive Care Unit. Continuum (Minneap Minn) 2021; 27:1321-1343. [PMID: 34618762 DOI: 10.1212/con.0000000000001012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
PURPOSE OF REVIEW This article discusses the evolving definitions of seizures and status epilepticus in the critical care environment and the role of critical care EEG in both diagnosing seizure activity and serving as a predictive biomarker of clinical trajectory. RECENT FINDINGS Initial screening EEG has been validated as a tool to predict which patients are at risk of future seizures. However, accepted definitions of seizures and nonconvulsive status epilepticus encourage a treatment trial when the diagnosis on EEG is indeterminate because of periodic or rhythmic patterns or uncertain clinical correlation. Similarly, recent data have demonstrated the diagnostic utility of intracranial EEG in increasing the yield of seizure detection. EEG has additionally been validated as a diagnostic biomarker of covert consciousness, a predictive biomarker of cerebral ischemia and impending neurologic deterioration, and a prognostic biomarker of coma recovery and status epilepticus resolution. A recent randomized trial concluded that patients allocated to continuous EEG had no difference in mortality than those undergoing intermittent EEG but could not demonstrate whether this lack of difference was because of studying heterogeneous conditions, examining a monitoring tool rather than a therapeutic approach, or examining an outcome measure (mortality) perhaps more strongly associated with early withdrawal of life-sustaining therapy than to a sustained response to pharmacotherapy. SUMMARY Seizures and status epilepticus are events of synchronous hypermetabolic activity that are either discrete and intermittent or, alternatively, continuous. Seizures and status epilepticus represent the far end of a continuum of ictal-interictal patterns that include lateralized rhythmic delta activity and periodic discharges, which not only predict future seizures but may be further classified as status epilepticus on the basis of intracranial EEG monitoring or a diagnostic trial of antiseizure medication therapy. In particularly challenging cases, neuroimaging or multimodality neuromonitoring may be a useful adjunct documenting metabolic crisis. Specialized uses of EEG as a prognostic biomarker have emerged in traumatic brain injury for predicting language function and covert consciousness, cardiac arrest for predicting coma recovery, and subarachnoid hemorrhage for predicting neurologic deterioration due to delayed cerebral ischemia.
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35
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EEG Patterns and Outcomes After Hypoxic Brain Injury: A Systematic Review and Meta-analysis. Neurocrit Care 2021; 36:292-301. [PMID: 34379270 DOI: 10.1007/s12028-021-01322-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 07/26/2021] [Indexed: 10/20/2022]
Abstract
Electroencephalography (EEG) is used to prognosticate recovery in comatose patients with hypoxic ischemic brain injury (HIBI) secondary to cardiac arrest. We sought to determine the prognostic use of specific EEG patterns for predicting disability and death following HIBI secondary to cardiac arrest. This systematic review searched Medline, Embase, and Cochrane Central up to January 2020. We included original research involving prospective and retrospective cohort studies relating specific EEG patterns to disability and death in comatose adult patients suffering HIBI post cardiac arrest requiring admission to an intensive care setting. We evaluated study quality using the Quality of Diagnostic Accuracy Studies 2 tool. Descriptive statistics were used to summarize study, patient, and EEG characteristics. We pooled study-level estimates of sensitivity and specificity for EEG patterns defined a priori using a random effect bivariate and univariate meta-analysis when appropriate. Funnel plots were used to assess publication bias. Of 5191 abstracts, 333 were reviewed in full text, of which 57 were included in the systematic review and 32 in meta-analyses. No reported EEG pattern was found to be invariably associated with death or disability across all studies. Pooled specificities of status epilepticus, burst suppression, and electrocerebral silence were high (92-99%), but sensitivities were low (6-39%) when predicting a composite outcome of disability and death. Study quality varied depending on domain; patient flow and timing performed was well conducted in all, whereas EEG interpretation was retrospective in 17 of 39 studies. Accounting for variable study quality, EEG demonstrates high specificity with a low risk of false negative outcome attribution for disability and death when status epilepticus, burst suppression, or electrocerebral silence is detected. Increased use of standardized cross-study protocols and definitions of EEG patterns are required to better evaluate the prognostic use of EEG for comatose patients with HIBI following cardiac arrest.
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36
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Awakening from post anoxic coma with burst suppression with identical bursts. Resusc Plus 2021; 7:100151. [PMID: 34386780 PMCID: PMC8342773 DOI: 10.1016/j.resplu.2021.100151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/14/2021] [Accepted: 07/02/2021] [Indexed: 11/20/2022] Open
Abstract
Background Electroencephalography (EEG) is commonly used after cardiac arrest. Burst suppression with identical bursts (BSIB) has been reported as a perfectly specific predictor of poor outcome but published case series are small. We describe two patients with BSIB who awakened from coma after cardiac arrest. Methods We identified two out-of-hospital cardiac arrest (OHCA) patients with coma and BSIB. We determined the etiology of arrest, presenting neurological examination, potential confounders to neurological assessment, neurodiagnostics and time to awakening. We reviewed and interpreted EEGs using 2021 American Clinical Neurophysiology Society guidelines. We quantified identicality of bursts by calculating pairwise correlation coefficients between the first 500 ms of each aligned burst. Results In case one we present a 62-year-old man with OHCA secondary to septic shock. EEG showed burst suppression pattern, with bursts consisted of high amplitude generalized spike waves in lock-step with myoclonus (inter-burst correlation = 0.86). He followed commands 3 days after arrest, when repeat EEG showed a continuous, variable and reactive background without epileptiform activity. Case two was a 49-year-old woman with OHCA secondary to polysubstance overdose. Initial EEG revealed burst suppression with high amplitude generalized polyspike-wave bursts with associated myoclonus. She followed commands on post-arrest day 4, when repeat EEG showed a continuous, variable and reactive background with frequent runs of bifrontal predominant sharply contoured rhythmic delta activity. Conclusion These cases highlight the perils of prognosticating with a single modality in comatose cardiac arrest patients.
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37
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Song JL, Kim JA, Struck AF, Zhang R, Westover MB. A model of metabolic supply-demand mismatch leading to secondary brain injury. J Neurophysiol 2021; 126:653-667. [PMID: 34232754 DOI: 10.1152/jn.00674.2020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Secondary brain injury (SBI) is defined as new or worsening injury to the brain after an initial neurologic insult, such as hemorrhage, trauma, ischemic stroke, or infection. It is a common and potentially preventable complication following many types of primary brain injury (PBI). However, mechanistic details about how PBI leads to additional brain injury and evolves into SBI are poorly characterized. In this work, we propose a mechanistic model for the metabolic supply demand mismatch hypothesis (MSDMH) of SBI. Our model, based on the Hodgkin-Huxley model, supplemented with additional dynamics for extracellular potassium, oxygen concentration, and excitotoxity, provides a high-level unified explanation for why patients with acute brain injury frequently develop SBI. We investigate how decreased oxygen, increased extracellular potassium, excitotoxicity, and seizures can induce SBI and suggest three underlying paths for how events following PBI may lead to SBI. The proposed model also helps explain several important empirical observations, including the common association of acute brain injury with seizures, the association of seizures with tissue hypoxia and so on. In contrast to current practices which assume that ischemia plays the predominant role in SBI, our model suggests that metabolic crisis involved in SBI can also be nonischemic. Our findings offer a more comprehensive understanding of the complex interrelationship among potassium, oxygen, excitotoxicity, seizures, and SBI.NEW & NOTEWORTHY We present a novel mechanistic model for the metabolic supply demand mismatch hypothesis (MSDMH), which attempts to explain why patients with acute brain injury frequently develop seizure activity and secondary brain injury (SBI). Specifically, we investigate how decreased oxygen, increased extracellular potassium, excitotoxicity, seizures, all common sequalae of primary brain injury (PBI), can induce SBI and suggest three underlying paths for how events following PBI may lead to SBI.
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Affiliation(s)
- Jiang-Ling Song
- The Medical Big Data Research Center, Northwest University, Xi'an, China.,Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jennifer A Kim
- Department of Neurology, Yale New Haven Hospital, New Haven, Connecticut
| | - Aaron F Struck
- Departments of Neurology, University of Wisconsin-Madison, Madison, Wisconsin.,William S Middleton Veterans Administration Hospital, Madison, Wisconsin
| | - Rui Zhang
- The Medical Big Data Research Center, Northwest University, Xi'an, China
| | - M Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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38
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Shanker A, Abel JH, Schamberg G, Brown EN. Etiology of Burst Suppression EEG Patterns. Front Psychol 2021; 12:673529. [PMID: 34177731 PMCID: PMC8222661 DOI: 10.3389/fpsyg.2021.673529] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 05/14/2021] [Indexed: 12/14/2022] Open
Abstract
Burst-suppression electroencephalography (EEG) patterns of electrical activity, characterized by intermittent high-power broad-spectrum oscillations alternating with isoelectricity, have long been observed in the human brain during general anesthesia, hypothermia, coma and early infantile encephalopathy. Recently, commonalities between conditions associated with burst-suppression patterns have led to new insights into the origin of burst-suppression EEG patterns, their effects on the brain, and their use as a therapeutic tool for protection against deleterious neural states. These insights have been further supported by advances in mechanistic modeling of burst suppression. In this Perspective, we review the origins of burst-suppression patterns and use recent insights to weigh evidence in the controversy regarding the extent to which burst-suppression patterns observed during profound anesthetic-induced brain inactivation are associated with adverse clinical outcomes. Whether the clinical intent is to avoid or maintain the brain in a state producing burst-suppression patterns, monitoring and controlling neural activity presents a technical challenge. We discuss recent advances that enable monitoring and control of burst suppression.
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Affiliation(s)
- Akshay Shanker
- Department of Anesthesiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, United States
- Department of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - John H. Abel
- Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA, United States
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, United States
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States
| | - Gabriel Schamberg
- Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA, United States
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Emery N. Brown
- Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA, United States
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, United States
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39
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Nolan JP, Sandroni C, Böttiger BW, Cariou A, Cronberg T, Friberg H, Genbrugge C, Haywood K, Lilja G, Moulaert VRM, Nikolaou N, Olasveengen TM, Skrifvars MB, Taccone F, Soar J. Postreanimationsbehandlung. Notf Rett Med 2021. [DOI: 10.1007/s10049-021-00892-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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40
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Peluso L, Gaspard N. Electroencephalography in post-cardiac arrest patients: a matter of timing? Minerva Anestesiol 2021; 87:637-639. [PMID: 33938681 DOI: 10.23736/s0375-9393.21.15715-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Lorenzo Peluso
- Department of Intensive Care, Cliniques Universitaires de Bruxelles - Erasme Hospital, Brussels, Belgium -
| | - Nicolas Gaspard
- Department of Neurology, Cliniques Universitaires de Bruxelles - Erasme Hospital, Brussels, Belgium.,Department of Neurology, Yale University Medical School, New Haven, CT, USA
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41
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Doerrfuss JI, Kowski AB, Holtkamp M, Thinius M, Leithner C, Storm C. Prognostic value of 'late' electroencephalography recordings in patients with cardiopulmonal resuscitation after cardiac arrest. J Neurol 2021; 268:4248-4257. [PMID: 33871711 PMCID: PMC8505381 DOI: 10.1007/s00415-021-10549-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 04/02/2021] [Accepted: 04/05/2021] [Indexed: 11/20/2022]
Abstract
Background Electroencephalography (EEG) significantly contributes to the neuroprognostication after resuscitation from cardiac arrest. Recent studies suggest that the prognostic value of EEG is highest for continuous recording within the first days after cardiac arrest. Early continuous EEG, however, is not available in all hospitals. In this observational study, we sought to evaluate the predictive value of a ‘late’ EEG recording 5–14 days after cardiac arrest without sedatives. Methods We retrospectively analyzed EEG data in consecutive adult patients treated at the medical intensive care units (ICU) of the Charité—Universitätsmedizin Berlin. Outcome was assessed as cerebral performance category (CPC) at discharge from ICU, with an unfavorable outcome being defined as CPC 4 and 5. Results In 187 patients, a ‘late’ EEG recording was performed. Of these patients, 127 were without continuous administration of sedative agents for at least 24 h before the EEG recording. In this patient group, a continuously suppressed background activity < 10 µV predicted an unfavorable outcome with a sensitivity of 31% (95% confidence interval (CI) 20–45) and a specificity of 99% (95% CI 91–100). In patients with suppressed background activity and generalized periodic discharges, sensitivity was 15% (95% CI 7–27) and specificity was 100% (95% CI 94–100). GPDs on unsuppressed background activity were associated with a sensitivity of 42% (95% CI 29–46) and a specificity of 92% (95% CI 82–97). Conclusions A ‘late’ EEG performed 5 to 14 days after resuscitation from cardiac arrest can aide in prognosticating functional outcome. A suppressed EEG background activity in this time period indicates poor outcome. Supplementary Information The online version contains supplementary material available at 10.1007/s00415-021-10549-y.
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Affiliation(s)
- Jakob I Doerrfuss
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany.
| | - Alexander B Kowski
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Martin Holtkamp
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Moritz Thinius
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christoph Leithner
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christian Storm
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
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42
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Peluso L, Legros B, Caroyer S, Taccone FS, Gaspard N. Falsely predictive EEG and clinical signs after post-anoxic brain injury under sevoflurane anesthesia. Clin Neurophysiol 2021; 132:1080-1082. [PMID: 33765473 DOI: 10.1016/j.clinph.2021.02.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 02/09/2021] [Accepted: 02/12/2021] [Indexed: 12/01/2022]
Affiliation(s)
- Lorenzo Peluso
- Department of Intensive Care Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Benjamin Legros
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Sarah Caroyer
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Fabio Silvio Taccone
- Department of Intensive Care Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Nicolas Gaspard
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
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43
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Nolan JP, Sandroni C, Böttiger BW, Cariou A, Cronberg T, Friberg H, Genbrugge C, Haywood K, Lilja G, Moulaert VRM, Nikolaou N, Olasveengen TM, Skrifvars MB, Taccone F, Soar J. European Resuscitation Council and European Society of Intensive Care Medicine guidelines 2021: post-resuscitation care. Intensive Care Med 2021; 47:369-421. [PMID: 33765189 PMCID: PMC7993077 DOI: 10.1007/s00134-021-06368-4] [Citation(s) in RCA: 417] [Impact Index Per Article: 139.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 02/08/2021] [Indexed: 12/13/2022]
Abstract
The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation and organ donation.
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Affiliation(s)
- Jerry P. Nolan
- University of Warwick, Warwick Medical School, Coventry, CV4 7AL UK
- Royal United Hospital, Bath, BA1 3NG UK
| | - Claudio Sandroni
- Department of Intensive Care, Emergency Medicine and Anaesthesiology, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Rome, Italy
- Institute of Anaesthesiology and Intensive Care Medicine, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Bernd W. Böttiger
- Department of Anaesthesiology and Intensive Care Medicine, University Hospital of Cologne, Kerpener Straße 62, 50937 Cologne, Germany
| | - Alain Cariou
- Cochin University Hospital (APHP) and University of Paris (Medical School), Paris, France
| | - Tobias Cronberg
- Department of Clinical Sciences, Neurology, Lund University, Skane University Hospital, Lund, Sweden
| | - Hans Friberg
- Department of Clinical Sciences, Anaesthesia and Intensive Care Medicine, Lund University, Skane University Hospital, Lund, Sweden
| | - Cornelia Genbrugge
- Acute Medicine Research Pole, Institute of Experimental and Clinical Research (IREC), Université Catholique de Louvain, Brussels, Belgium
- Emergency Department, University Hospitals Saint-Luc, Brussels, Belgium
| | - Kirstie Haywood
- Warwick Research in Nursing, Division of Health Sciences, Warwick Medical School, University of Warwick, Room A108, Coventry, CV4 7AL UK
| | - Gisela Lilja
- Department of Clinical Sciences Lund, Neurology, Lund University, Skane University Hospital, Lund, Sweden
| | - Véronique R. M. Moulaert
- Department of Rehabilitation Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Nikolaos Nikolaou
- Cardiology Department, Konstantopouleio General Hospital, Athens, Greece
| | - Theresa Mariero Olasveengen
- Department of Anesthesiology, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Markus B. Skrifvars
- Department of Emergency Care and Services, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Fabio Taccone
- Department of Intensive Care, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Jasmeet Soar
- Southmead Hospital, North Bristol NHS Trust, Bristol, BS10 5NB UK
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44
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Nolan JP, Sandroni C, Böttiger BW, Cariou A, Cronberg T, Friberg H, Genbrugge C, Haywood K, Lilja G, Moulaert VRM, Nikolaou N, Mariero Olasveengen T, Skrifvars MB, Taccone F, Soar J. European Resuscitation Council and European Society of Intensive Care Medicine Guidelines 2021: Post-resuscitation care. Resuscitation 2021; 161:220-269. [PMID: 33773827 DOI: 10.1016/j.resuscitation.2021.02.012] [Citation(s) in RCA: 338] [Impact Index Per Article: 112.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation, and organ donation.
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Affiliation(s)
- Jerry P Nolan
- University of Warwick, Warwick Medical School, Coventry CV4 7AL, UK; Royal United Hospital, Bath, BA1 3NG, UK.
| | - Claudio Sandroni
- Department of Intensive Care, Emergency Medicine and Anaesthesiology, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Rome, Italy; Institute of Anaesthesiology and Intensive Care Medicine, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Bernd W Böttiger
- University Hospital of Cologne, Kerpener Straße 62, D-50937 Cologne, Germany
| | - Alain Cariou
- Cochin University Hospital (APHP) and University of Paris (Medical School), Paris, France
| | - Tobias Cronberg
- Department of Clinical Sciences, Neurology, Lund University, Skane University Hospital, Lund, Sweden
| | - Hans Friberg
- Department of Clinical Sciences, Anaesthesia and Intensive Care Medicine, Lund University, Skane University Hospital, Lund, Sweden
| | - Cornelia Genbrugge
- Acute Medicine Research Pole, Institute of Experimental and Clinical Research (IREC) Université Catholique de Louvain, Brussels, Belgium; Emergency Department, University Hospitals Saint-Luc, Brussels, Belgium
| | - Kirstie Haywood
- Warwick Research in Nursing, Room A108, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK
| | - Gisela Lilja
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Neurology, Lund, Sweden
| | - Véronique R M Moulaert
- University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, The Netherlands
| | - Nikolaos Nikolaou
- Cardiology Department, Konstantopouleio General Hospital, Athens, Greece
| | - Theresa Mariero Olasveengen
- Department of Anesthesiology, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Markus B Skrifvars
- Department of Emergency Care and Services, University of Helsinki and Helsinki University Hospital, Finland
| | - Fabio Taccone
- Department of Intensive Care, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Jasmeet Soar
- Southmead Hospital, North Bristol NHS Trust, Bristol BS10 5NB, UK
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Khalili-Ardali M, Wu S, Tonin A, Birbaumer N, Chaudhary U. Neurophysiological aspects of the completely locked-in syndrome in patients with advanced amyotrophic lateral sclerosis. Clin Neurophysiol 2021; 132:1064-1076. [PMID: 33743301 DOI: 10.1016/j.clinph.2021.01.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 01/12/2021] [Accepted: 01/18/2021] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Amyotrophic lateral sclerosis (ALS) patients in completely locked-in syndrome (CLIS) are incapable of expressing themselves, and their state of consciousness and awareness is difficult to evaluate. Due to the complete paralysis included paralysis of eye muscles, any assessment of the perceptual and psychophysiological state can only be implemented in passive experimental paradigms with neurophysiological recordings. METHODS Four patients in CLIS were investigated in several experiments including resting state, visual stimulation (eyes open vs eyes closed), auditory stimulation (modified local-global paradigm), somatosensory stimulation (electrical stimulation of the median nerve), and during sleep. RESULTS All patients showed altered neurophysiological metrics, but a unique and common pattern could not be found between patients. However, slowing of the electroencephalography (EEG) and attenuation or absence of alpha wave activity was common in all patients. In two of the four patients, a slow dominant frequency emerged at 4 Hz with synchronized EEG at all channels. In the other two patients slowing of EEG appears less synchronized. EEGs between eyes open and eyes closed were significantly different in all patients. The dominant slow frequency during the day changes during slow-wave sleep (supposedly sleep stage 3) to even slower frequencies below 2 Hz. Somatosensory evoked potentials (SEPs) were absent or significantly altered in comparison to healthy subjects, similarly for auditory evoked potentials (AEPs). CONCLUSIONS The heterogeneity of the results underscores the fact that no single neurophysiological index is available to assess psychophysiological states in unresponsive ALS patients in CLIS. This caveat may also be valid for the assessment of cognitive processes; a functioning BCI can be the solution. SIGNIFICANCE Most of the studies of the neurophysiology of ALS patients focused on the early stage of the disease, and there are very few studies on the late stage when patients are completely paralyzed with no means of communication (i.e., CLIS). This study provides quantitative metrics of different neurophysiological aspects of these patients.
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Affiliation(s)
- Majid Khalili-Ardali
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany
| | - Shizhe Wu
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany
| | - Alessandro Tonin
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany; Wyss Center for Bio and Neuroengineering, Geneva, Switzerland
| | - Niels Birbaumer
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany.
| | - Ujwal Chaudhary
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany
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Frohlich J, Toker D, Monti MM. Consciousness among delta waves: a paradox? Brain 2021; 144:2257-2277. [PMID: 33693596 DOI: 10.1093/brain/awab095] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 02/12/2021] [Accepted: 02/25/2021] [Indexed: 01/29/2023] Open
Abstract
A common observation in EEG research is that consciousness vanishes with the appearance of delta (1 - 4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are very frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalised epileptic seizures, and disorders of consciousness such as coma and vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the "down states" or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and nonconvulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalogram or MEG signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.
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Affiliation(s)
- Joel Frohlich
- Department of Psychology, University of California Los Angeles, 3423 Franz Hall, Los Angeles, California 90095, USA
| | - Daniel Toker
- Department of Psychology, University of California Los Angeles, 3423 Franz Hall, Los Angeles, California 90095, USA
| | - Martin M Monti
- Department of Psychology, University of California Los Angeles, 3423 Franz Hall, Los Angeles, California 90095, USA.,Department of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90095, USA
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47
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Khazanova D, Douglas VC, Amorim E. A matter of timing: EEG monitoring for neurological prognostication after cardiac arrest in the era of targeted temperature management. Minerva Anestesiol 2021; 87:704-713. [PMID: 33591136 DOI: 10.23736/s0375-9393.21.14793-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Neuromonitoring with electroencephalography (EEG) is an essential tool in neurological prognostication post-cardiac arrest. EEG allows reliable and real-time assessment of early changes in background patterns, development of seizures and epileptiform activity, as well as testing for background reactivity to stimuli despite use of sedation or targeted temperature management. Delayed emergence of consciousness post-cardiac arrest is common, therefore longitudinal monitoring of EEG allows the detection of trends indicative of neurological improvement before coma recovery can be observed clinically. In this review, we summarize essential recent literature in EEG monitoring for neurological prognostication post-cardiac arrest in the context of targeted temperature management, with a particular focus on the importance of the evolution of EEG patterns in the first few days following resuscitation.
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Affiliation(s)
- Darya Khazanova
- Department of Neurology, University of California, San Francisco, CA, USA.,Division of Neurology, Zuckerberg San Francisco General Hospital, San Francisco, CA, USA
| | - Vanja C Douglas
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Edilberto Amorim
- Department of Neurology, University of California, San Francisco, CA, USA - .,Division of Neurology, Zuckerberg San Francisco General Hospital, San Francisco, CA, USA
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48
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Abstract
PURPOSE OF REVIEW Randomized controlled trials investigating the initial pharmacological treatment of status epilepticus have been recently published. Furthermore, status epilepticus arising in comatose survivors after cardiac arrest has received increasing attention in the last years. This review offers an updated assessment of status epilepticus treatment in these different scenarios. RECENT FINDINGS Initial benzodiazepines underdosing is common and correlates with development of status epilepticus refractoriness. The recently published ESETT trial provides high-level evidence regarding the equivalence of fosphenytoin, valproate, and levetiracetam as a second-line option. Myoclonus or epileptiform transients on electroencephalography occur in up to 1/3 of patients surviving a cardiac arrest. Contrary to previous assumptions regarding an almost invariable association with death, at least 1/10 of them may awaken with reasonably good prognosis, if treated. Multimodal prognostication including clinical examination, EEG, somatosensory evoked potentials, biochemical markers, and neuroimaging help identifying patients with a chance to recover consciousness, in whom a trial with antimyoclonic compounds and at times general anesthetics is indicated. SUMMARY There is a continuous, albeit relatively slow progress in knowledge regarding different aspect of status epilepticus; recent findings refine some treatment strategies and help improving patients' outcomes. Further high-quality studies are clearly needed to further improve the management of these patients, especially those with severe, refractory status epilepticus forms.
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49
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Hirsch LJ, Fong MW, Leitinger M, LaRoche SM, Beniczky S, Abend NS, Lee JW, Wusthoff CJ, Hahn CD, Westover MB, Gerard EE, Herman ST, Haider HA, Osman G, Rodriguez-Ruiz A, Maciel CB, Gilmore EJ, Fernandez A, Rosenthal ES, Claassen J, Husain AM, Yoo JY, So EL, Kaplan PW, Nuwer MR, van Putten M, Sutter R, Drislane FW, Trinka E, Gaspard N. American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology: 2021 Version. J Clin Neurophysiol 2021; 38:1-29. [PMID: 33475321 PMCID: PMC8135051 DOI: 10.1097/wnp.0000000000000806] [Citation(s) in RCA: 344] [Impact Index Per Article: 114.7] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- Lawrence J. Hirsch
- Comprehensive Epilepsy Center, Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
| | - Michael W.K. Fong
- Westmead Comprehensive Epilepsy Unit, Westmead Hospital, University of Sydney, Sydney, Australia
| | - Markus Leitinger
- Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria
| | - Suzette M. LaRoche
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, U.S.A
| | - Sandor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund and Aarhus University Hospital, Aarhus, Denmark
| | - Nicholas S. Abend
- Departments of Neurology and Pediatrics, The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A
| | - Jong Woo Lee
- Brigham and Women’s Hospital, Boston, Massachusetts, U.S.A
| | | | - Cecil D. Hahn
- Division of Neurology, The Hospital for Sick Children, and Department of Pediatrics, University of Toronto, Toronto, Canada
| | | | - Elizabeth E. Gerard
- Comprehensive Epilepsy Center, Department of Neurology, Northwestern University, Chicago, Illinois, U.S.A
| | | | - Hiba Arif Haider
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, U.S.A
| | - Gamaleldin Osman
- Department of Neurology, Henry Ford Hospital, Detroit, Michigan, U.S.A
| | - Andres Rodriguez-Ruiz
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, U.S.A
| | - Carolina B. Maciel
- Division of Neurocritical Care, Department of Neurology, University of Florida, Gainesville, Florida, U.S.A
| | - Emily J. Gilmore
- Comprehensive Epilepsy Center, Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
| | - Andres Fernandez
- Department of Neurology, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania, U.S.A
| | - Eric S. Rosenthal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Jan Claassen
- Neurocritical Care, Department of Neurology, Columbia University, New York, New York, U.S.A
| | - Aatif M. Husain
- Department of Medicine (Neurology), Duke University Medical Center, and Veterans Affairs Medical Center, Durham, North Carolina, U.S.A
| | - Ji Yeoun Yoo
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Elson L. So
- Division of Epilepsy, Mayo Clinic, Rochester, Minnesota, U.S.A
| | - Peter W. Kaplan
- Department of Neurology, Johns Hopkins University School of Medicine, Johns Hopkins Bayview Medical Center, Baltimore, Maryland, U.S.A
| | - Marc R. Nuwer
- Department of Neurology, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California, U.S.A
| | - Michel van Putten
- Medisch Spectrum Twente and University of Twente, Enschede, The Netherlands
| | - Raoul Sutter
- Medical Intensive Care Units and Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Frank W. Drislane
- Department of Neurology, Harvard Medical School, and Comprehensive Epilepsy Center, Beth Israel Deaconess Medical Center, Boston, Massachusetts, U.S.A
| | - Eugen Trinka
- Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria
| | - Nicolas Gaspard
- Department of Neurology, Université Libre de Bruxelles, Hôpital Erasme, Brussels, Belgium
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50
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Peluso L, Rechichi S, Franchi F, Pozzebon S, Scolletta S, Brasseur A, Legros B, Vincent JL, Creteur J, Gaspard N, Taccone FS. Electroencephalographic features in patients undergoing extracorporeal membrane oxygenation. CRITICAL CARE : THE OFFICIAL JOURNAL OF THE CRITICAL CARE FORUM 2020; 24:629. [PMID: 33126887 PMCID: PMC7598240 DOI: 10.1186/s13054-020-03353-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 10/21/2020] [Indexed: 11/10/2022]
Abstract
Background Neurologic injury is one of the most frequent causes of death in patients undergoing extracorporeal membrane oxygenation (ECMO). As neurological examination is often unreliable in sedated patients, additional neuromonitoring is needed. However, the value of electroencephalogram (EEG) in adult ECMO patients has not been well assessed. Therefore, the aim of this study was to assess the occurrence of electroencephalographic abnormalities in patients treated with extracorporeal membrane oxygenation (ECMO) and their association with 3-month neurologic outcome.
Methods Retrospective analysis of all patients undergoing venous–venous (V–V) or venous–arterial (V–A) ECMO with a concomitant EEG recording (April 2009–December 2018), either recorded intermittently or continuously. EEG background was classified into four categories: mild/moderate encephalopathy (i.e., mostly defined by the presence of reactivity), severe encephalopathy (mostly defined by the absence of reactivity), burst-suppression (BS) and suppressed background. Epileptiform activity (i.e., ictal EEG pattern, sporadic epileptiform discharges or periodic discharges) and asymmetry were also reported. EEG findings were analyzed according to unfavorable neurological outcome (UO, defined as Glasgow Outcome Scale < 4) at 3 months after discharge. Results A total of 139 patients (54 [41–62] years; 60 (43%) male gender) out of 596 met the inclusion criteria and were analyzed. Veno–arterial (V–A) ECMO was used in 98 (71%); UO occurred in 99 (71%) patients. Continuous EEG was performed in 113 (81%) patients. The analysis of EEG background showed that 29 (21%) patients had severe encephalopathy, 4 (3%) had BS and 19 (14%) a suppressed background. In addition, 11 (8%) of patients had seizures or status epilepticus, 10 (7%) had generalized periodic discharges or lateralized periodic discharges, and 27 (19%) had asymmetry on EEG. In the multivariate analysis, the occurrence of ischemic stroke or intracranial hemorrhage (OR 4.57 [1.25–16.74]; p = 0.02) and a suppressed background (OR 10.08 [1.24–82.20]; p = 0.03) were independently associated with UO. After an adjustment for covariates, an increasing probability for UO was observed with more severe EEG background categories. Conclusions In adult patients treated with ECMO, EEG can identify patients with a high likelihood of poor outcome. In particular, suppressed background was independently associated with unfavorable neurological outcome.
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Affiliation(s)
- Lorenzo Peluso
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium.
| | - Serena Rechichi
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium.,Department of Medical Biotechnologies, Anesthesia and Intensive Care Unit, University of Siena, Via Bracci 1, 53100, Siena, Italy
| | - Federico Franchi
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium.,Department of Medical Biotechnologies, Anesthesia and Intensive Care Unit, University of Siena, Via Bracci 1, 53100, Siena, Italy
| | - Selene Pozzebon
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium.,Department of Medical Biotechnologies, Anesthesia and Intensive Care Unit, University of Siena, Via Bracci 1, 53100, Siena, Italy
| | - Sabino Scolletta
- Department of Medical Biotechnologies, Anesthesia and Intensive Care Unit, University of Siena, Via Bracci 1, 53100, Siena, Italy
| | - Alexandre Brasseur
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium
| | - Benjamin Legros
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070, Brussels, Belgium
| | - Jean-Louis Vincent
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium
| | - Jacques Creteur
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium
| | - Nicolas Gaspard
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070, Brussels, Belgium.,Department of Neurology, Yale University Medical School, 15, York Street, New Haven, CT, 06510, USA
| | - Fabio Silvio Taccone
- Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Brussels, Belgium
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