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Bougouin W, Lascarrou JB, Chelly J, Benghanem S, Geri G, Maizel J, Fage N, Sboui G, Pichon N, Daubin C, Sauneuf B, Mongardon N, Taccone F, Hermann B, Colin G, Lesieur O, Deye N, Chudeau N, Cour M, Bourenne J, Klouche K, Klein T, Raphalen JH, Muller G, Galbois A, Bruel C, Jacquier S, Paul M, Sandroni C, Cariou A. Performance of the ERC/ESICM-recommendations for neuroprognostication after cardiac arrest: insights from a prospective multicenter cohort. Resuscitation 2024:110362. [PMID: 39151721 DOI: 10.1016/j.resuscitation.2024.110362] [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: 07/11/2024] [Revised: 08/09/2024] [Accepted: 08/11/2024] [Indexed: 08/19/2024]
Abstract
Brief abstract: In a multicentre network of 28 ICUs in France and Belgium, all comatose patients who fulfilled the 2021 ERC-ESICM criteria for poor outcome after cardiac arrest died or survived with severe neurological disability, even after excluding patients with active WLST to limit self-fulfilling prophecy bias. However, in almost half of the patients, these criteria were not fulfilled, resulting in an indeterminate outcome; in these patients, normal NSE levels and benign EEG predicted neurological recovery, helping reduce prognostic uncertainty. AIM To investigate the performance of the 2021 ERC/ESICM-recommended algorithm for predicting poor outcome after cardiac arrest (CA) and potential tools for predicting neurological recovery in patients with indeterminate outcome. METHODS Prospective, multicenter study on out-of-hospital CA survivors from 28 ICUs of the AfterROSC network. In patients comatose with a Glasgow Coma Scale motor score ≤3 at ≥72 hours after resuscitation, we measured: 1) the accuracy of neurological examination, biomarkers (neuron-specific enolase, NSE), electrophysiology (EEG and SSEP) and neuroimaging (brain CT and MRI) for predicting poor outcome (modified Rankin scale score≥4 at 90 days), and 2) the ability of low or decreasing NSE levels and benign EEG to predict good outcome in patients whose prognosis remained indeterminate. RESULTS Among 337 included patients, the ERC-ESICM algorithm predicted poor neurological outcome in 175 patients, of whom 106 (60%) had withdrawal of life-sustaining treatment (WLST). Among the 69 patients without active WLST, the positive predictive value for an unfavourable outcome was 100% [95-100]%. The specificity of individual predictors ranged from 90% for EEG to 100% for clinical examination and SSEP. Among the remaining 162 patients with indeterminate outcome, a combination of 2 favourable signs predicted good outcome with 99[96-100]% specificity and 23[11-38%]% sensitivity. Conclusion All comatose resuscitated patients not undergoing WLST who fulfilled the ERC-ESICM criteria for poor outcome after CA had poor outcome at three months, even if a self-fulfilling prophecy cannot be completely excluded. In patients with indeterminate outcome (half of the population), favourable signs predicted neurological recovery, reducing prognostic uncertainty.
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Affiliation(s)
- Wulfran Bougouin
- AfterROSC Network Group, Paris, France; Université de Paris Cité, Inserm, Paris Cardiovascular Research Center, Paris, France; Ramsay Générale de Santé, Hôpital Privé Jacques Cartier, Massy, France.
| | - Jean-Baptiste Lascarrou
- AfterROSC Network Group, Paris, France; Université de Paris Cité, Inserm, Paris Cardiovascular Research Center, Paris, France; Service de Médecine Intensive Réanimation, University Hospital Center, Nantes, France
| | - Jonathan Chelly
- AfterROSC Network Group, Paris, France; Réanimation Polyvalente, Centre Hospitalier Intercommunal Toulon La Seyne sur Mer, Toulon, France
| | - Sarah Benghanem
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, APHP, CHU Cochin, Université Paris Cité, Paris, France
| | - Guillaume Geri
- AfterROSC Network Group, Paris, France; Réanimation Polyvalente, Groupe Hospitalier Privé Ambroise Paré Hartmann, Neuilly-sur-Seine, France
| | - Julien Maizel
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CHU Amiens, Amiens, France
| | - Nicolas Fage
- AfterROSC Network Group, Paris, France; Département de médecine intensive réanimation et médecine hyperbare, CHU Angers, Angers, France
| | - Ghada Sboui
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CH Béthune, Béthune, France
| | - Nicolas Pichon
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CH Brive‑La‑Gaillarde, Brive, France
| | - Cédric Daubin
- AfterROSC Network Group, Paris, France; CHU de Caen Normandie, Médecine Intensive Réanimation, 14000 CAEN, France
| | - Bertrand Sauneuf
- AfterROSC Network Group, Paris, France; Réanimation Médecine Intensive, Centre Hospitalier Public du Cotentin, 50100 Cherbourg-en-Cotentin, France
| | - Nicolas Mongardon
- AfterROSC Network Group, Paris, France; Service d'Anesthésie‑Réanimation et Médecine Péri-Opératoire, APHP, CHU Henri Mondor, Créteil, France
| | - Fabio Taccone
- AfterROSC Network Group, Paris, France; Réanimation, ERASME, Brussels, Belgium
| | - Bertrand Hermann
- AfterROSC Network Group, Paris, France; Médecine Intensive-Réanimation, AP-HP, Hôpital Européen Georges Pompidou, 20 rue Leblanc, Paris, France
| | - Gwenhaël Colin
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CHD Vendée, La Roche‑Sur‑Yon, France
| | - Olivier Lesieur
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CH La Rochelle, La Rochelle, France
| | - Nicolas Deye
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, APHP, CHU Lariboisière, Paris, France
| | - Nicolas Chudeau
- AfterROSC Network Group, Paris, France; Réanimation médico-chirurgicale, CH Le Mans, Le Mans, France
| | - Martin Cour
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, Hospices Civils Lyon, Lyon, France
| | - Jeremy Bourenne
- AfterROSC Network Group, Paris, France; Réanimation des Urgences et Déchocage, CHU La Timone, APHM, Marseille, France
| | - Kada Klouche
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CHU Montpellier, Montpellier, France
| | - Thomas Klein
- AfterROSC Network Group, Paris, France; Service de Médecine Intensive Réanimation Brabois CHRU Nancy France
| | - Jean-Herlé Raphalen
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, APHP, CHU Necker, Paris, France
| | - Grégoire Muller
- AfterROSC Network Group, Paris, France; Centre Hospitalier Universitaire (CHU) d'Orléans, Médecine Intensive Réanimation, Université de Tours, MR INSERM 1327 ISCHEMIA, Université de Tours, F37000, Tours, France, Clinical Research in Intensive Care and Sepsis-Trial Group for Global Evaluation and Research in Sepsis (CRICS_TRIGGERSep) French Clinical Research Infrastructure Network (F-CRIN) Research Network
| | - Arnaud Galbois
- AfterROSC Network Group, Paris, France; Service de Réanimation Polyvalente, Ramsay-Santé, Hôpital Privé Claude Galien, Quincy‑Sous‑Sénart, France
| | - Cédric Bruel
- AfterROSC Network Group, Paris, France; Service de Réanimation Polyvalente, Groupe Hospitalier Paris Saint Joseph, Paris, France
| | - Sophie Jacquier
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CHU Tours, Tours, France
| | - Marine Paul
- AfterROSC Network Group, Paris, France; Médecine Intensive Réanimation, CH Versailles, Le Chesnay, France
| | - 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
| | - Alain Cariou
- AfterROSC Network Group, Paris, France; Université de Paris Cité, Inserm, Paris Cardiovascular Research Center, Paris, France; Ramsay Générale de Santé, Hôpital Privé Jacques Cartier, Massy, France
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2
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Bazbaz A, Varon J. Neuroprognostication, withdrawal of care and long-term outcomes after cardiopulmonary resuscitation. Curr Opin Crit Care 2024:00075198-990000000-00202. [PMID: 39150054 DOI: 10.1097/mcc.0000000000001194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
PURPOSE OF REVIEW Survivors of cardiac arrest often have increased long-term risks of mortality and disability that are primarily associated with hypoxic-ischemic brain injury (HIBI). This review aims to examine health-related long-term outcomes after cardiac arrest. RECENT FINDINGS A notable portion of cardiac arrest survivors face a decline in their quality of life, encountering persistent physical, cognitive, and mental health challenges emerging years after the initial event. Within the first-year postarrest, survivors are at elevated risk for stroke, epilepsy, and psychiatric conditions, along with a heightened susceptibility to developing dementia. Addressing these challenges necessitates establishing comprehensive, multidisciplinary care systems tailored to the needs of these individuals. SUMMARY HIBI remains the leading cause of disability among cardiac arrest survivors. No single strategy is likely to improve long term outcomes after cardiac arrest. A multimodal neuroprognostication approach (clinical examination, imaging, neurophysiology, and biomarkers) is recommended by guidelines, but fails to predict long-term outcomes. Cardiac arrest survivors often experience long-term disabilities that negatively impact their quality of life. The likelihood of such outcomes implements a multidisciplinary care an integral part of long-term recovery.
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Affiliation(s)
| | - Joseph Varon
- Dorrington Medical Associates, PA
- The University of Houston College of Medicine, Houston, Texas, USA
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3
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Turella S, Dankiewicz J, Ben-Hamouda N, Bernhard Nilsen K, Düring J, Endisch C, Engstrøm M, Flügel D, Gaspard N, Grejs AM, Haenggi M, Haffey S, Imbach L, Johnsen B, Kemlink D, Leithner C, Legriel S, Lindehammar H, Mazzon G, Nielsen N, Peyre A, Ribalta Stanford B, Roman-Pognuz E, Rossetti AO, Schrag C, Valeriánová A, Wendel-Garcia P, Zubler F, Cronberg T, Westhall E. EEG for good outcome prediction after cardiac arrest: A multicentre cohort study. Resuscitation 2024:110319. [PMID: 39029579 DOI: 10.1016/j.resuscitation.2024.110319] [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: 06/12/2024] [Revised: 07/06/2024] [Accepted: 07/08/2024] [Indexed: 07/21/2024]
Abstract
AIM Assess the prognostic ability of a non-highly malignant and reactive EEG to predict good outcome after cardiac arrest (CA). METHODS Prospective observational multicentre substudy of the "Targeted Hypothermia versus Targeted Normothermia after Out-of-hospital Cardiac Arrest Trial", also known as the TTM2-trial. Presence or absence of highly malignant EEG patterns and EEG reactivity to external stimuli were prospectively assessed and reported by the trial sites. Highly malignant patterns were defined as burst-suppression or suppression with or without superimposed periodic discharges. Multimodal prognostication was performed 96 h after CA. Good outcome at 6 months was defined as a modified Rankin Scale score of 0-3. RESULTS 873 comatose patients at 59 sites had an EEG assessment during the hospital stay. Of these, 283 (32%) had good outcome. EEG was recorded at a median of 69 h (IQR 47-91) after CA. Absence of highly malignant EEG patterns was seen in 543 patients of whom 255 (29% of the cohort) had preserved EEG reactivity. A non-highly malignant and reactive EEG had 56% (CI 50-61) sensitivity and 83% (CI 80-86) specificity to predict good outcome. Presence of EEG reactivity contributed (p < 0.001) to the specificity of EEG to predict good outcome compared to only assessing background pattern without taking reactivity into account. CONCLUSION Nearly one-third of comatose patients resuscitated after CA had a non-highly malignant and reactive EEG that was associated with a good long-term outcome. Reactivity testing should be routinely performed since preserved EEG reactivity contributed to prognostic performance.
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Affiliation(s)
- S Turella
- Department of Clinical Sciences Lund, Clinical Neurophysiology, Lund University, Lund, Sweden
| | - J Dankiewicz
- Department of Clinical Sciences Lund, Cardiology, Lund University, Lund, Sweden
| | - N Ben-Hamouda
- Department of Adult Intensive Care Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - K Bernhard Nilsen
- Section for Clinical Neurophysiology, Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - J Düring
- Department of Clinical Sciences, Anaesthesia and Intensive Care, Lund University, Malmö, Sweden
| | - C Endisch
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt - Universität zu Berlin, Department of Neurology and Experimental Neurology, Augustenburger Platz 1, 13353 Berlin, Germany
| | - M Engstrøm
- Department of Clinical Neurophysiology, St. Olavs University Hospital and Department of Neuromedicine and Movement Science (INB) NTNU, Trondheim, Norway
| | - D Flügel
- Department of Neurology, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - N Gaspard
- Department of Neurology, Erasme University Hospital, Université Libre de Bruxelles, Brussels, Belgium; Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - A M Grejs
- Department of Intensive Care Medicine, Aarhus University Hospital and Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - M Haenggi
- Department of Intensive Care Medicine, Bern University Hospital, University of Bern, Bern, Switzerland
| | - S Haffey
- Department of Clinical Neurophysiology, Royal Victoria Hospital, Belfast, Ireland
| | - L Imbach
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - B Johnsen
- Department of Clinical Medicine, Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - D Kemlink
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - C Leithner
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt - Universität zu Berlin, Department of Neurology and Experimental Neurology, Augustenburger Platz 1, 13353 Berlin, Germany
| | - S Legriel
- Intensive Care Unit, Versailles Hospital, France
| | - H Lindehammar
- Clinical Neurophysiology, Department of Clinical and Experimental Medicine, Linköping University, Sweden
| | - G Mazzon
- Department of Neurology, University Hospital of Trieste, Trieste, Italy
| | - N Nielsen
- Department of Clinical Sciences Lund, Anesthesiology and Intensive Care Medicine, Helsingborg Hospital, Helsingborg, Sweden
| | - A Peyre
- Department of Neurology, Centre Hospitalier Universitaire de Nantes, Nantes, France
| | - B Ribalta Stanford
- Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden
| | - E Roman-Pognuz
- Intensive Care Unit, University Hospital of Trieste, Trieste, Italy
| | - A O Rossetti
- Department of Neurology, University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - C Schrag
- Intensive Care Department, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - A Valeriánová
- General University Hospital in Prague, Prague, Czech Republic
| | - P Wendel-Garcia
- Institute of Intensive Care Medicine, University Hospital Zürich, Zürich, Switzerland
| | - F Zubler
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - T Cronberg
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
| | - E Westhall
- Department of Clinical Sciences Lund, Clinical Neurophysiology, Lund University, Lund, Sweden.
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Bitar R, Khan UM, Rosenthal ES. Utility and rationale for continuous EEG monitoring: a primer for the general intensivist. Crit Care 2024; 28:244. [PMID: 39014421 PMCID: PMC11251356 DOI: 10.1186/s13054-024-04986-0] [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: 02/06/2024] [Accepted: 06/09/2024] [Indexed: 07/18/2024] Open
Abstract
This review offers a comprehensive guide for general intensivists on the utility of continuous EEG (cEEG) monitoring for critically ill patients. Beyond the primary role of EEG in detecting seizures, this review explores its utility in neuroprognostication, monitoring neurological deterioration, assessing treatment responses, and aiding rehabilitation in patients with encephalopathy, coma, or other consciousness disorders. Most seizures and status epilepticus (SE) events in the intensive care unit (ICU) setting are nonconvulsive or subtle, making cEEG essential for identifying these otherwise silent events. Imaging and invasive approaches can add to the diagnosis of seizures for specific populations, given that scalp electrodes may fail to identify seizures that may be detected by depth electrodes or electroradiologic findings. When cEEG identifies SE, the risk of secondary neuronal injury related to the time-intensity "burden" often prompts treatment with anti-seizure medications. Similarly, treatment may be administered for seizure-spectrum activity, such as periodic discharges or lateralized rhythmic delta slowing on the ictal-interictal continuum (IIC), even when frank seizures are not evident on the scalp. In this setting, cEEG is utilized empirically to monitor treatment response. Separately, cEEG has other versatile uses for neurotelemetry, including identifying the level of sedation or consciousness. Specific conditions such as sepsis, traumatic brain injury, subarachnoid hemorrhage, and cardiac arrest may each be associated with a unique application of cEEG; for example, predicting impending events of delayed cerebral ischemia, a feared complication in the first two weeks after subarachnoid hemorrhage. After brief training, non-neurophysiologists can learn to interpret quantitative EEG trends that summarize elements of EEG activity, enhancing clinical responsiveness in collaboration with clinical neurophysiologists. Intensivists and other healthcare professionals also play crucial roles in facilitating timely cEEG setup, preventing electrode-related skin injuries, and maintaining patient mobility during monitoring.
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Affiliation(s)
- Ribal Bitar
- Department of Neurology, Massachusetts General Hospital, 55 Fruit St., Lunder 644, Boston, MA, 02114, USA
| | - Usaamah M Khan
- Department of Neurology, Massachusetts General Hospital, 55 Fruit St., Lunder 644, Boston, MA, 02114, USA
| | - Eric S Rosenthal
- Department of Neurology, Massachusetts General Hospital, 55 Fruit St., Lunder 644, Boston, MA, 02114, USA.
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Hakim A, Branca M, Kurmann C, Wagner B, Iten M, Hänggi M, Wagner F. CT brain perfusion patterns and clinical outcome after successful cardiopulmonary resuscitation: A pilot study. Resuscitation 2024; 200:110216. [PMID: 38626861 DOI: 10.1016/j.resuscitation.2024.110216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 04/07/2024] [Accepted: 04/08/2024] [Indexed: 06/19/2024]
Abstract
AIM CT perfusion is a valuable tool for evaluating cerebrovascular diseases, but its role in patients with hypoxic ischaemic encephalopathy is unclear. This study aimed to investigate 1) the patterns of cerebral perfusion changes that may occur early on after successful resuscitation, and 2) their correlation with clinical outcome to explore their value for predicting outcome. METHODS We conducted a retrospective analysis of perfusion maps from patients who underwent CT brain perfusion within 12 h following successful resuscitation. We classified the perfusion changes into distinct patterns. According to the cerebral performance category (CPC) score clinical outcome was categorised as favourable (CPC 1-2), or unfavourable (CPC 3-5). RESULTS A total of 87 patients were included of whom 33 had a favourable outcome (60.6% male, mean age 60 ± 16 years), whereas 54 exhibited an unfavourable outcome (59.3% male, mean age 60 ± 19 years). Of the patients in the favourable outcome group, 30.3% showed no characteristic perfusion changes, in contrast to the unfavourable outcome group where all patients exhibit changes in perfusion. Eighteen perfusion patterns were identified. The most significant patterns for prediction of unfavourable outcome in terms of their high specificity and frequency were hypoperfusion of the brainstem as well as coexisting hypoperfusion of the brainstem and thalamus. CONCLUSION This pilot study identified various perfusion patterns in patients after resuscitation, indicative of circulatory changes associated with post-cardiac-arrest brain injury. After validation, certain patterns could potentially be used in conjunction with other prognostic markers for stratifying patients and adjusting personalized treatment following cardiopulmonary resuscitation. Normal brain perfusion within 12 h after resuscitation is predictive of favourable outcome with high specificity.
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Affiliation(s)
- Arsany Hakim
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital Bern University Hospital, and University of Bern, Bern, Switzerland.
| | | | - Christoph Kurmann
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital Bern University Hospital, and University of Bern, Bern, Switzerland
| | - Benedikt Wagner
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital Bern University Hospital, and University of Bern, Bern, Switzerland
| | - Manuela Iten
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Matthias Hänggi
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Franca Wagner
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital Bern University Hospital, and University of Bern, Bern, Switzerland
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6
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Liu G, Wang Y, Tian F, Chen W, Cui L, Jiang M, Zhang Y, Gao K, Su Y, Wang H. Quantitative EEG reactivity induced by electrical stimulation predicts good outcome in comatose patients after cardiac arrest. Ann Intensive Care 2024; 14:99. [PMID: 38935167 PMCID: PMC11211292 DOI: 10.1186/s13613-024-01339-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 06/17/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND EEG reactivity is a predictor for neurological outcome in comatose patients after cardiac arrest (CA); however, its application is limited by variability in stimulus types and visual assessment. We aimed to evaluate the prognostic value of the quantitative analysis of EEG reactivity induced by standardized electrical stimulation and for early prognostication in this population. METHODS This prospective observational study recruited post-CA comatose patients in Xuanwu Hospital, Capital Medical University (Beijing, China) between January 2016 and June 2023. EEG reactivity to electrical or traditional pain stimulation was randomly performed via visual and quantitative analysis. Neurological outcome within 6 months was dichotomized as good (Cerebral Performance Categories, CPC 1-2) or poor (CPC 3-5). RESULTS Fifty-eight post-CA comatose patients were admitted, and 52 patients were included in the final analysis, of which 19 (36.5%) had good outcomes. EEG reactivity induced with the electrical stimulation had superior performance to the traditional pain stimulation for good outcome prediction (quantitative analysis: AUC 0.932 vs. 0.849, p = 0.048). When using the electrical stimulation, the AUC of EEG reactivity to predict good outcome by visual analysis was 0.838, increasing to 0.932 by quantitative analysis (p = 0.039). Comparing to the traditional pain stimulation by visual analysis, the AUC of EEG reactivity for good prognostication by the electrical stimulation with quantitative analysis was significantly improved (0.932 vs. 0.770, p = 0.004). CONCLUSIONS EEG reactivity induced by the standardized electrical stimulation in combination with quantitative analysis is a promising formula for post-CA comatose patients, with increased predictive accuracy.
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Affiliation(s)
- Gang Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Yuan Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Fei Tian
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Weibi Chen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Lili Cui
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Mengdi Jiang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Yan Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Keming Gao
- Department of Psychiatry, Mood Disorders Program, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Yingying Su
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China.
| | - Hongxing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Brain Injury Evaluation Quality Control Center, National Center for Neurological Disorders, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China.
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7
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Benghanem S, Sharshar T, Gavaret M, Dumas F, Diehl JL, Brechot N, Picard F, Candia-Rivera D, Le MP, Pène F, Cariou A, Hermann B. Heart rate variability for neuro-prognostication after CA: Insight from the Parisian registry. Resuscitation 2024:110294. [PMID: 38925291 DOI: 10.1016/j.resuscitation.2024.110294] [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: 04/08/2024] [Revised: 05/31/2024] [Accepted: 06/19/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Hypoxic ischemic brain injury (HIBI) induced by cardiac arrest (CA) seems to predominate in cortical areas and to a lesser extent in the brainstem. These regions play key roles in modulating the activity of the autonomic nervous system (ANS), that can be assessed through analyses of heart rate variability (HRV). The objective was to evaluate the prognostic value of various HRV parameters to predict neurological outcome after CA. METHODS Retrospective monocentric study assessing the prognostic value of HRV markers and their association with HIBI severity. Patients admitted for CA who underwent EEG for persistent coma after CA were included. HRV markers were computed from 5 min signal of the ECG lead of the EEG recording. HRV indices were calculated in the time-, frequency-, and non-linear domains. Frequency-domain analyses differentiated very low frequency (VLF 0.003-0.04 Hz), low frequency (LF 0.04-0.15 Hz), high frequency (HF 0.15-0.4 Hz), and LF/HF ratio. HRV indices were compared to other prognostic markers: pupillary light reflex, EEG, N20 on somatosensory evoked potentials (SSEP) and biomarkers (neuron specific enolase-NSE). Neurological outcome at 3 months was defined as unfavorable in case of best CPC 3-4-5. RESULTS Between 2007 and 2021, 199 patients were included. Patients were predominantly male (64%), with a median age of 60 [48.9-71.7] years. 76% were out-of-hospital CA, and 30% had an initial shockable rhythm. Neurological outcome was unfavorable in 73%. Compared to poor outcome, patients with a good outcome had higher VLF (0.21 vs 0.09 ms2/Hz, p < 0.01), LF (0.07 vs 0.04 ms2/Hz, p = 0.003), and higher LF/HF ratio (2.01 vs 1.01, p = 0.008). Several non-linear domain indices were also higher in the good outcome group, such as SD2 (15.1 vs 10.2, p = 0.016) and DFA α1 (1.03 vs 0.78, p = 0.002). These indices also differed depending on the severity of EEG pattern and abolition of pupillary light reflex. These time-frequency and non-linear domains HRV parameters were predictive of poor neurological outcome, with high specificity despite a low sensitivity. CONCLUSION In comatose patients after CA, some HRV markers appear to be associated with unfavorable outcome, EEG severity and PLR abolition, although the sensitivity of these HRV markers remains limited.
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Affiliation(s)
- Sarah Benghanem
- Medical Intensive Care Unit, APHP.Paris Centre, Cochin Hospital, Paris, France; University Paris Cité, Medical School, Paris F-75006, France; INSERM 1266, Institute of Psychiatry and Neurosciences of Paris (IPNP), INSERM UMR 1266, Paris, France.
| | - Tarek Sharshar
- University Paris Cité, Medical School, Paris F-75006, France; INSERM 1266, Institute of Psychiatry and Neurosciences of Paris (IPNP), INSERM UMR 1266, Paris, France; Neuro-ICU, GHU Paris Sainte Anne, Paris, France
| | - Martine Gavaret
- University Paris Cité, Medical School, Paris F-75006, France; INSERM 1266, Institute of Psychiatry and Neurosciences of Paris (IPNP), INSERM UMR 1266, Paris, France; Neurophysiology and Epileptology Department, GHU Paris Sainte Anne, Paris, France
| | - Florence Dumas
- University Paris Cité, Medical School, Paris F-75006, France; Emergency Department, APHP.Paris Centre, Cochin Hospital, Paris, France
| | - Jean-Luc Diehl
- University Paris Cité, Medical School, Paris F-75006, France; Medical ICU, AP-HP, Hôpital Européen Georges Pompidou, 20 rue Leblanc, Paris F-75015, France
| | - Nicolas Brechot
- University Paris Cité, Medical School, Paris F-75006, France; Medical ICU, AP-HP, Hôpital Européen Georges Pompidou, 20 rue Leblanc, Paris F-75015, France
| | - Fabien Picard
- University Paris Cité, Medical School, Paris F-75006, France; Cardiology Department, APHP.Paris Centre, Cochin Hospital, Paris, France
| | - Diego Candia-Rivera
- Institut du Cerveau et de la Moelle épinière - ICM, INSERM U1127, CNRS UMR 7225, F-75013 Paris, France
| | - Minh-Pierre Le
- Medical Intensive Care Unit, APHP.Paris Centre, Cochin Hospital, Paris, France
| | - Frederic Pène
- Medical Intensive Care Unit, APHP.Paris Centre, Cochin Hospital, Paris, France; University Paris Cité, Medical School, Paris F-75006, France
| | - Alain Cariou
- Medical Intensive Care Unit, APHP.Paris Centre, Cochin Hospital, Paris, France; University Paris Cité, Medical School, Paris F-75006, France
| | - Bertrand Hermann
- University Paris Cité, Medical School, Paris F-75006, France; INSERM 1266, Institute of Psychiatry and Neurosciences of Paris (IPNP), INSERM UMR 1266, Paris, France; Medical ICU, AP-HP, Hôpital Européen Georges Pompidou, 20 rue Leblanc, Paris F-75015, France
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8
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Steinberg A. Emergent Management of Hypoxic-Ischemic Brain Injury. Continuum (Minneap Minn) 2024; 30:588-610. [PMID: 38830064 DOI: 10.1212/con.0000000000001426] [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: 06/05/2024]
Abstract
OBJECTIVE This article outlines interventions used to improve outcomes for patients with hypoxic-ischemic brain injury after cardiac arrest. LATEST DEVELOPMENTS Emergent management of patients after cardiac arrest requires prevention and treatment of primary and secondary brain injury. Primary brain injury is minimized by excellent initial resuscitative efforts. Secondary brain injury prevention requires the detection and correction of many pathophysiologic processes that may develop in the hours to days after the initial arrest. Key physiologic parameters important to secondary brain injury prevention include optimization of mean arterial pressure, cerebral perfusion, oxygenation and ventilation, intracranial pressure, temperature, and cortical hyperexcitability. This article outlines recent data regarding the treatment and prevention of secondary brain injury. Different patients likely benefit from different treatment strategies, so an individualized approach to treatment and prevention of secondary brain injury is advisable. Clinicians must use multimodal sources of data to prognosticate outcomes after cardiac arrest while recognizing that all prognostic tools have shortcomings. ESSENTIAL POINTS Neurologists should be involved in the postarrest care of patients with hypoxic-ischemic brain injury to improve their outcomes. Postarrest care requires nuanced and patient-centered approaches to the prevention and treatment of primary and secondary brain injury and neuroprognostication.
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9
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Vitt JR, Mainali S. Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients. Semin Neurol 2024; 44:342-356. [PMID: 38569520 DOI: 10.1055/s-0044-1785504] [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: 04/05/2024]
Abstract
The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for significant strides in patient diagnosis, treatment, and prognostication in neurocritical care. These technologies offer the potential to unravel complex patterns within vast datasets ranging from vast clinical data and EEG (electroencephalogram) readings to advanced cerebral imaging facilitating a more nuanced understanding of patient conditions. Despite their promise, the implementation of AI and ML faces substantial hurdles. Historical biases within training data, the challenge of interpreting multifaceted data streams, and the "black box" nature of ML algorithms present barriers to widespread clinical adoption. Moreover, ethical considerations around data privacy and the need for transparent, explainable models remain paramount to ensure trust and efficacy in clinical decision-making.This article reflects on the emergence of AI and ML as integral tools in neurocritical care, discussing their roles from the perspective of both their scientific promise and the associated challenges. We underscore the importance of extensive validation in diverse clinical settings to ensure the generalizability of ML models, particularly considering their potential to inform critical medical decisions such as withdrawal of life-sustaining therapies. Advancement in computational capabilities is essential for implementing ML in clinical settings, allowing for real-time analysis and decision support at the point of care. As AI and ML are poised to become commonplace in clinical practice, it is incumbent upon health care professionals to understand and oversee these technologies, ensuring they adhere to the highest safety standards and contribute to the realization of personalized medicine. This engagement will be pivotal in integrating AI and ML into patient care, optimizing outcomes in neurocritical care through informed and data-driven decision-making.
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Affiliation(s)
- Jeffrey R Vitt
- Department of Neurological Surgery, UC Davis Medical Center, Sacramento, California
| | - Shraddha Mainali
- Department of Neurology, Virginia Commonwealth University, Richmond, Virginia
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10
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Hsiao CL, Chen PY, Chen IA, Lin SK. The Role of Routine Electroencephalography in the Diagnosis of Seizures in Medical Intensive Care Units. Diagnostics (Basel) 2024; 14:1111. [PMID: 38893637 PMCID: PMC11171977 DOI: 10.3390/diagnostics14111111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 05/15/2024] [Accepted: 05/22/2024] [Indexed: 06/21/2024] Open
Abstract
Seizures should be diagnosed and treated to ensure optimal health outcomes in critically ill patients admitted in the medical intensive care unit (MICU). Continuous electroencephalography is still infrequently used in the MICU. We investigated the effectiveness of routine EEG (rEEG) in detecting seizures in the MICU. A total of 560 patients admitted to the MICU between October 2018 and March 2023 and who underwent rEEG were reviewed. Seizure-related rEEG constituted 47% of all rEEG studies. Totally, 39% of the patients experienced clinical seizures during hospitalization; among them, 48% experienced the seizure, and 13% experienced their first seizure after undergoing an rEEG study. Seventy-seven percent of the patients had unfavorable short-term outcomes. Patients with cardiovascular diseases were the most likely to have the suppression/burst suppression (SBS) EEG pattern and the highest mortality rate. The rhythmic and periodic patterns (RPPs) and electrographic seizure (ESz) EEG pattern were associated with seizures within 24 h after rEEG, which was also related to unfavorable outcomes. Significant predictors of death were age > 59 years, the male gender, the presence of cardiovascular disease, a Glasgow Coma Scale score ≤ 5, and the SBS EEG pattern, with a predictive performance of 0.737 for death. rEEG can help identify patients at higher risk of seizures. We recommend repeated rEEG in patients with ESz or RPP EEG patterns to enable a more effective monitoring of seizure activities.
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Affiliation(s)
- Cheng-Lun Hsiao
- Stroke Center and Department of Neurology, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan; (C.-L.H.); (P.-Y.C.)
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
| | - Pei-Ya Chen
- Stroke Center and Department of Neurology, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan; (C.-L.H.); (P.-Y.C.)
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
| | - I-An Chen
- Taiwan Center for Drug Evaluation, Taipei 11557, Taiwan;
| | - Shinn-Kuang Lin
- Stroke Center and Department of Neurology, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan; (C.-L.H.); (P.-Y.C.)
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
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11
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Benghanem S, Kubis N, Gayat E, Loiodice A, Pruvost-Robieux E, Sharshar T, Foucrier A, Figueiredo S, Bouilleret V, De Montmollin E, Bagate F, Lefaucheur JP, Guidet B, Appartis E, Cariou A, Varnet O, Jost PH, Megarbane B, Degos V, Le Guennec L, Naccache L, Legriel S, Woimant F, Gregoire C, Cortier D, Crassard I, Timsit JF, Mazighi M, Sonneville R. Prognostic value of early EEG abnormalities in severe stroke patients requiring mechanical ventilation: a pre-planned analysis of the SPICE prospective multicenter study. Crit Care 2024; 28:173. [PMID: 38783313 PMCID: PMC11119574 DOI: 10.1186/s13054-024-04957-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024] Open
Abstract
INTRODUCTION Prognostication of outcome in severe stroke patients necessitating invasive mechanical ventilation poses significant challenges. The objective of this study was to assess the prognostic significance and prevalence of early electroencephalogram (EEG) abnormalities in adult stroke patients receiving mechanical ventilation. METHODS This study is a pre-planned ancillary investigation within the prospective multicenter SPICE cohort study (2017-2019), conducted in 33 intensive care units (ICUs) in the Paris area, France. We included adult stroke patients requiring invasive mechanical ventilation, who underwent at least one intermittent EEG examination during their ICU stay. The primary endpoint was the functional neurological outcome at one year, determined using the modified Rankin scale (mRS), and dichotomized as unfavorable (mRS 4-6, indicating severe disability or death) or favorable (mRS 0-3). Multivariable regression analyses were employed to identify EEG abnormalities associated with functional outcomes. RESULTS Of the 364 patients enrolled in the SPICE study, 153 patients (49 ischemic strokes, 52 intracranial hemorrhages, and 52 subarachnoid hemorrhages) underwent at least one EEG at a median time of 4 (interquartile range 2-7) days post-stroke. Rates of diffuse slowing (70% vs. 63%, p = 0.37), focal slowing (38% vs. 32%, p = 0.15), periodic discharges (2.3% vs. 3.7%, p = 0.9), and electrographic seizures (4.5% vs. 3.7%, p = 0.4) were comparable between patients with unfavorable and favorable outcomes. Following adjustment for potential confounders, an unreactive EEG background to auditory and pain stimulations (OR 6.02, 95% CI 2.27-15.99) was independently associated with unfavorable outcomes. An unreactive EEG predicted unfavorable outcome with a specificity of 48% (95% CI 40-56), sensitivity of 79% (95% CI 72-85), and positive predictive value (PPV) of 74% (95% CI 67-81). Conversely, a benign EEG (defined as continuous and reactive background activity without seizure, periodic discharges, triphasic waves, or burst suppression) predicted favorable outcome with a specificity of 89% (95% CI 84-94), and a sensitivity of 37% (95% CI 30-45). CONCLUSION The absence of EEG reactivity independently predicts unfavorable outcomes at one year in severe stroke patients requiring mechanical ventilation in the ICU, although its prognostic value remains limited. Conversely, a benign EEG pattern was associated with a favorable outcome.
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Affiliation(s)
- Sarah Benghanem
- AP-HP.Centre, Medical ICU, Cochin Hospital, Paris, France
- University Paris Cité, Medical School, Paris, France
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris-IPNP, Paris, France
| | - Nathalie Kubis
- University Paris Cité, Medical School, Paris, France
- APHP.Nord, Clinical Physiology Department, UMRS_1144, Université Paris Cite, Paris, France
| | - Etienne Gayat
- University Paris Cité, Medical School, Paris, France
- APHP.Nord, Department of Anesthesiology and Critical Care, DMU Parabol, Université Paris Cite, Paris, France
| | | | - Estelle Pruvost-Robieux
- University Paris Cité, Medical School, Paris, France
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris-IPNP, Paris, France
- Neurophysiology and Epileptology Department, GHU Psychiatry & Neurosciences, Sainte Anne, Paris, France
| | - Tarek Sharshar
- University Paris Cité, Medical School, Paris, France
- Department of Neuroanesthesiology and Intensive Care, Sainte Anne Hospital, Paris, France
| | - Arnaud Foucrier
- APHP, Department of Anesthesiology and Critical Care, Beaujon University Hospital, Clichy, France
| | - Samy Figueiredo
- APHP, Department of Anesthesiology and Critical Care, Bicêtre University Hospitals, Le Kremlin Bicêtre, France
| | - Viviane Bouilleret
- Neurophysiology and Epileptology Department, Bicêtre University Hospitals, Le Kremlin Bicêtre, France
| | | | - François Bagate
- APHP, Department of Intensive Care Medicine, Henri Mondor University Hospital and Université de Paris Est Créteil, Créteil, France
| | | | - Bertrand Guidet
- APHP, Department of Intensive Care Medicine, Saint Antoine University Hospital, Paris, France
| | - Emmanuelle Appartis
- Neurophysiology Department, Saint Antoine University Hospital, Paris, France
| | - Alain Cariou
- AP-HP.Centre, Medical ICU, Cochin Hospital, Paris, France
- University Paris Cité, Medical School, Paris, France
| | - Olivier Varnet
- APHP, Department of Physiology, Bichat-Claude Bernard University Hospital, 75018, Paris, France
| | - Paul Henri Jost
- APHP, Department of Anesthesiology and Intensive Care, Henri Mondor Hospital, Creteil, France
| | | | - Vincent Degos
- APHP, Department of Anesthesiology and Neurointensive Care, Pitié Salpétrière Hospital, Paris, France
| | - Loic Le Guennec
- APHP, Medical ICU, Pitié Salpétrière Hospital, Paris, France
| | - Lionel Naccache
- APHP, Department of Physiology, Pitié Salpétrière Hospital, Paris, France
| | | | | | - Charles Gregoire
- Department of Intensive Care, Rothschild Hospital Foundation, Paris, France
| | - David Cortier
- Department of Intensive Care, Foch Hospital, Paris, France
| | | | - Jean-François Timsit
- APHP, Department of Intensive Care Medicine, Bichat-Claude Bernard University Hospital, 46 rue Henri Huchard, 75018, Paris, France
- Université Paris Cité, INSERM UMR 1137, IAME, Paris, France
| | - Mikael Mazighi
- APHP Nord, Department of Neurology, Lariboisière University Hospital, Department of Interventional Neuroradiology, Fondation Rothschild Hospital, FHU Neurovasc, Paris, France
- Université Paris Cité, INSERM UMR 1144, Paris, France
| | - Romain Sonneville
- APHP, Department of Intensive Care Medicine, Bichat-Claude Bernard University Hospital, 46 rue Henri Huchard, 75018, Paris, France.
- Université Paris Cité, INSERM UMR 1137, IAME, Paris, France.
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12
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Bencsik CM, Kramer AH, Couillard P, MacKay M, Kromm JA. Postarrest Neuroprognostication: Practices and Opinions of Canadian Physicians. Can J Neurol Sci 2024; 51:404-415. [PMID: 37489539 DOI: 10.1017/cjn.2023.261] [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] [Indexed: 07/26/2023]
Abstract
BACKGROUND Objective, evidence-based neuroprognostication of postarrest patients is crucial to avoid inappropriate withdrawal of life-sustaining therapies or prolonged, invasive, and costly therapies that could perpetuate suffering when there is no chance of an acceptable recovery. Postarrest prognostication guidelines exist; however, guideline adherence and practice variability are unknown. OBJECTIVE To investigate Canadian practices and opinions regarding assessment of neurological prognosis in postarrest patients. METHODS An anonymous electronic survey was distributed to physicians who care for adult postarrest patients. RESULTS Of the 134 physicians who responded to the survey, 63% had no institutional protocols for neuroprognostication. While the use of targeted temperature management did not affect the timing of neuroprognostication, an increasing number of clinical findings suggestive of a poor prognosis affected the timing of when physicians were comfortable concluding patients had a poor prognosis. Variability existed in what factors clinicians' thought were confounders. Physicians identified bilaterally absent pupillary light reflexes (85%), bilaterally absent corneal reflexes (80%), and status myoclonus (75%) as useful in determining poor prognosis. Computed tomography, magnetic resonance imaging, and spot electroencephalography were the most useful and accessible tests. Somatosensory evoked potentials were useful, but logistically challenging. Serum biomarkers were unavailable at most centers. Most (79%) physicians agreed ≥2 definitive findings on neurologic exam, electrophysiologic tests, neuroimaging, and/or biomarkers are required to determine a poor prognosis with a high degree of certainty. Distress during the process of neuroprognostication was reported by 70% of physicians and 51% request a second opinion from an external expert. CONCLUSION Significant variability exists in post-cardiac arrest neuroprognostication practices among Canadian physicians.
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Affiliation(s)
- Caralyn M Bencsik
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
| | - Andreas H Kramer
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Philippe Couillard
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | | | - Julie A Kromm
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
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13
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Bencsik C, Josephson C, Soo A, Ainsworth C, Savard M, van Diepen S, Kramer A, Kromm J. The Evolving Role of Electroencephalography in Postarrest Care. Can J Neurol Sci 2024:1-13. [PMID: 38572611 DOI: 10.1017/cjn.2024.55] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
Electroencephalography is an accessible, portable, noninvasive and safe means of evaluating a patient's brain activity. It can aid in diagnosis and management decisions for post-cardiac arrest patients with seizures, myoclonus and other non-epileptic movements. It also plays an important role in a multimodal approach to neuroprognostication predicting both poor and favorable outcomes. Individuals ordering, performing and interpreting these tests, regardless of the indication, should understand the supporting evidence, logistical considerations, limitations and impact the results may have on postarrest patients and their families as outlined herein.
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Affiliation(s)
- Caralyn Bencsik
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
| | - Colin Josephson
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Andrea Soo
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
| | - Craig Ainsworth
- Division of Cardiology, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Martin Savard
- Département de Médecine, Université Laval, Quebec City, QC, Canada
| | - Sean van Diepen
- Department of Critical Care Medicine, University of Alberta, Edmonton, AB, Canada
- Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Andreas Kramer
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Julie Kromm
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
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14
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Hermann B, Candia‐Rivera D, Sharshar T, Gavaret M, Diehl J, Cariou A, Benghanem S. Aberrant brain-heart coupling is associated with the severity of post cardiac arrest brain injury. Ann Clin Transl Neurol 2024; 11:866-882. [PMID: 38243640 PMCID: PMC11021613 DOI: 10.1002/acn3.52000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 12/24/2023] [Indexed: 01/21/2024] Open
Abstract
OBJECTIVE To investigate autonomic nervous system activity measured by brain-heart interactions in comatose patients after cardiac arrest in relation to the severity and prognosis of hypoxic-ischemic brain injury. METHODS Strength and complexity of bidirectional interactions between EEG frequency bands (delta, theta, and alpha) and ECG heart rate variability frequency bands (low frequency, LF and high frequency, HF) were computed using a synthetic data generation model. Primary outcome was the severity of brain injury, assessed by (i) standardized qualitative EEG classification, (ii) somatosensory evoked potentials (N20), and (iii) neuron-specific enolase levels. Secondary outcome was the 3-month neurological status, assessed by the Cerebral Performance Category score [good (1-2) vs. poor outcome (3-4-5)]. RESULTS Between January 2007 and July 2021, 181 patients were admitted to ICU for a resuscitated cardiac arrest. Poor neurological outcome was observed in 134 patients (74%). Qualitative EEG patterns suggesting high severity were associated with decreased LF/HF. Severity of EEG changes were proportional to higher absolute values of brain-to-heart coupling strength (p < 0.02 for all brain-to-heart frequencies) and lower values of alpha-to-HF complexity (p = 0.049). Brain-to-heart coupling strength was significantly higher in patients with bilateral absent N20 and correlated with neuron-specific enolase levels at Day 3. This aberrant brain-to-heart coupling (increased strength and decreased complexity) was also associated with 3-month poor neurological outcome. INTERPRETATION Our results suggest that autonomic dysfunctions may well represent hypoxic-ischemic brain injury post cardiac arrest pathophysiology. These results open avenues for integrative monitoring of autonomic functioning in critical care patients.
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Affiliation(s)
- Bertrand Hermann
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitHEGP Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP.Centre)ParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
| | - Diego Candia‐Rivera
- Sorbonne Université, Paris Brain Institute (ICM), INRIA, CNRS UMR 722, INSERM U1127, AP‐HP Hôpital Pitié‐SalpêtrièreParisFrance
| | - Tarek Sharshar
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- GHU Paris Psychiatrie Neurosciences, Service hospitalo‐universitaire de Neuro‐anesthésie réanimationParisFrance
| | - Martine Gavaret
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- Neurophysiology and Epileptology DepartmentGHU Paris Psychiatrie et NeurosciencesParisFrance
| | - Jean‐Luc Diehl
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitHEGP Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP.Centre)ParisFrance
- Université Paris Cité, INSERM, Innovative Therapies in HaemostasisParisFrance
- Biosurgical Research Lab (Carpentier Foundation)ParisFrance
| | - Alain Cariou
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitCochin Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP‐Centre)ParisFrance
- Paris‐Cardiovascular‐Research‐CenterINSERM U970ParisFrance
| | - Sarah Benghanem
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- Medical Intensive Care UnitCochin Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP‐Centre)ParisFrance
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15
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Qing K, Forgacs P, Schiff N. EEG Pattern With Spectral Analysis Can Prognosticate Good and Poor Neurologic Outcomes After Cardiac Arrest. J Clin Neurophysiol 2024; 41:236-244. [PMID: 36007069 PMCID: PMC9905375 DOI: 10.1097/wnp.0000000000000958] [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] [Indexed: 11/26/2022] Open
Abstract
PURPOSE To investigate the prognostic value of a simple stratification system of electroencephalographical (EEG) patterns and spectral types for patients after cardiac arrest. METHODS In this prospectively enrolled cohort, using manually selected EEG segments, patients after cardiac arrest were stratified into five independent EEG patterns (based on background continuity and burden of highly epileptiform discharges) and four independent power spectral types (based on the presence of frequency components). The primary outcome is cerebral performance category (CPC) at discharge. Results from multimodal prognostication testing were included for comparison. RESULTS Of a total of 72 patients, 6 had CPC 1-2 by discharge, all of whom had mostly continuous EEG background without highly epileptiform activity at day 3. However, for the same EEG background pattern at day 3, 19 patients were discharged at CPC 3 and 15 patients at CPC 4-5. After adding spectral analysis, overall sensitivity for predicting good outcomes (CPC 1-2) was 83.3% (95% confidence interval 35.9% to 99.6%) and specificity was 97.0% (89.5% to 99.6%). In this cohort, standard prognostication testing all yielded 100% specificity but low sensitivity, with imaging being the most sensitive at 54.1% (36.9% to 70.5%). CONCLUSIONS Adding spectral analysis to qualitative EEG analysis may further improve the diagnostic accuracy of EEG and may aid developing novel measures linked to good outcomes in postcardiac arrest coma.
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Affiliation(s)
- Kurt Qing
- New York-Presbyterian Weill Cornell Medical Center
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16
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Berg KM, Bray JE, Ng KC, Liley HG, Greif R, Carlson JN, Morley PT, Drennan IR, Smyth M, Scholefield BR, Weiner GM, Cheng A, Djärv T, Abelairas-Gómez C, Acworth J, Andersen LW, Atkins DL, Berry DC, Bhanji F, Bierens J, Bittencourt Couto T, Borra V, Böttiger BW, Bradley RN, Breckwoldt J, Cassan P, Chang WT, Charlton NP, Chung SP, Considine J, Costa-Nobre DT, Couper K, Dainty KN, Dassanayake V, Davis PG, Dawson JA, Fernanda de Almeida M, De Caen AR, Deakin CD, Dicker B, Douma MJ, Eastwood K, El-Naggar W, Fabres JG, Fawke J, Fijacko N, Finn JC, Flores GE, Foglia EE, Folke F, Gilfoyle E, Goolsby CA, Granfeldt A, Guerguerian AM, Guinsburg R, Hatanaka T, Hirsch KG, Holmberg MJ, Hosono S, Hsieh MJ, Hsu CH, Ikeyama T, Isayama T, Johnson NJ, Kapadia VS, Daripa Kawakami M, Kim HS, Kleinman ME, Kloeck DA, Kudenchuk P, Kule A, Kurosawa H, Lagina AT, Lauridsen KG, Lavonas EJ, Lee HC, Lin Y, Lockey AS, Macneil F, Maconochie IK, John Madar R, Malta Hansen C, Masterson S, Matsuyama T, McKinlay CJD, Meyran D, Monnelly V, Nadkarni V, Nakwa FL, Nation KJ, Nehme Z, Nemeth M, Neumar RW, Nicholson T, Nikolaou N, Nishiyama C, Norii T, Nuthall GA, Ohshimo S, Olasveengen TM, Gene Ong YK, Orkin AM, Parr MJ, Patocka C, Perkins GD, Perlman JM, Rabi Y, Raitt J, Ramachandran S, Ramaswamy VV, Raymond TT, Reis AG, Reynolds JC, Ristagno G, Rodriguez-Nunez A, Roehr CC, Rüdiger M, Sakamoto T, Sandroni C, Sawyer TL, Schexnayder SM, Schmölzer GM, Schnaubelt S, Semeraro F, Singletary EM, Skrifvars MB, Smith CM, Soar J, Stassen W, Sugiura T, Tijssen JA, Topjian AA, Trevisanuto D, Vaillancourt C, Wyckoff MH, Wyllie JP, Yang CW, Yeung J, Zelop CM, Zideman DA, Nolan JP. 2023 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces. Resuscitation 2024; 195:109992. [PMID: 37937881 DOI: 10.1016/j.resuscitation.2023.109992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
The International Liaison Committee on Resuscitation engages in a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation and first aid science. Draft Consensus on Science With Treatment Recommendations are posted online throughout the year, and this annual summary provides more concise versions of the final Consensus on Science With Treatment Recommendations from all task forces for the year. Topics addressed by systematic reviews this year include resuscitation of cardiac arrest from drowning, extracorporeal cardiopulmonary resuscitation for adults and children, calcium during cardiac arrest, double sequential defibrillation, neuroprognostication after cardiac arrest for adults and children, maintaining normal temperature after preterm birth, heart rate monitoring methods for diagnostics in neonates, detection of exhaled carbon dioxide in neonates, family presence during resuscitation of adults, and a stepwise approach to resuscitation skills training. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research. Additional topics are addressed with scoping reviews and evidence updates.
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17
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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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18
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Wimmer H, Stensønes SH, Benth JŠ, Lundqvist C, Andersen GØ, Draegni T, Sunde K, Nakstad ER. Outcome prediction in comatose cardiac arrest patients with initial shockable and non-shockable rhythms. Acta Anaesthesiol Scand 2024; 68:263-273. [PMID: 37876138 DOI: 10.1111/aas.14337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 09/16/2023] [Accepted: 09/19/2023] [Indexed: 10/26/2023]
Abstract
BACKGROUND Prognosis after out-of-hospital cardiac arrest (OHCA) is presumed poorer in patients with non-shockable than shockable rhythms, frequently leading to treatment withdrawal. Multimodal outcome prediction is recommended 72 h post-arrest in still comatose patients, not considering initial rhythms. We investigated accuracy of outcome predictors in all comatose OHCA survivors, with a particular focus on shockable vs. non-shockable rhythms. METHODS In this observational NORCAST sub-study, patients still comatose 72 h post-arrest were stratified by shockable vs. non-shockable rhythms for outcome prediction analyzes. Good outcome was defined as cerebral performance category 1-2 within 6 months. False positive rate (FPR) was used for poor and sensitivity for good outcome prediction accuracy. RESULTS Overall, 72/128 (56%) patients with shockable and 12/50 (24%) with non-shockable rhythms had good outcome (p < .001). For poor outcome prediction, absent pupillary light reflexes (PLR) and corneal reflexes (clinical predictors) 72 h after sedation withdrawal, PLR 96 h post-arrest, and somatosensory evoked potentials (SSEP), all had FPR <0.1% in both groups. Unreactive EEG and neuron-specific enolase (NSE) >60 μg/L 24-72 h post-arrest had better precision in shockable patients. For good outcome, the clinical predictors, SSEP and CT, had 86%-100% sensitivity in both groups. For NSE, sensitivity varied from 22% to 69% 24-72 h post-arrest. The outcome predictors indicated severe brain injury proportionally more often in patients with non-shockable than with shockable rhythms. For all patients, clinical predictors, CT, and SSEP, predicted poor and good outcome with high accuracy. CONCLUSION Outcome prediction accuracy was comparable for shockable and non-shockable rhythms. PLR and corneal reflexes had best precision 72 h after sedation withdrawal and 96 h post-arrest.
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Affiliation(s)
- Henning Wimmer
- Department of Acute Medicine, Oslo University Hospital, Ullevål, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Jūratė Šaltytė Benth
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Health Services Research Unit, Akershus University Hospital, Nordbyhagen, Norway
| | - Christofer Lundqvist
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Health Services Research Unit, Akershus University Hospital, Nordbyhagen, Norway
- Department of Neurology, Akershus University Hospital, Nordbyhagen, Norway
| | - Geir Ø Andersen
- Department of Cardiology, Oslo University Hospital, Ullevål, Norway
| | - Tomas Draegni
- Department of Research and Development, Oslo University Hospital, Ullevål, Norway
| | - Kjetil Sunde
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Anaesthesia and Intensive Care, Oslo University Hospital, Ullevål, Norway
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19
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Nikolovski SS, Lazic AD, Fiser ZZ, Obradovic IA, Tijanic JZ, Raffay V. Recovery and Survival of Patients After Out-of-Hospital Cardiac Arrest: A Literature Review Showcasing the Big Picture of Intensive Care Unit-Related Factors. Cureus 2024; 16:e54827. [PMID: 38529434 PMCID: PMC10962929 DOI: 10.7759/cureus.54827] [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] [Accepted: 02/23/2024] [Indexed: 03/27/2024] Open
Abstract
As an important public health issue, out-of-hospital cardiac arrest (OHCA) requires several stages of high quality medical care, both on-field and after hospital admission. Post-cardiac arrest shock can lead to severe neurological injury, resulting in poor recovery outcome and increased risk of death. These characteristics make this condition one of the most important issues to deal with in post-OHCA patients hospitalized in intensive care units (ICUs). Also, the majority of initial post-resuscitation survivors have underlying coronary diseases making revascularization procedure another crucial step in early management of these patients. Besides keeping myocardial blood flow at a satisfactory level, other tissues must not be neglected as well, and maintaining mean arterial pressure within optimal range is also preferable. All these procedures can be simplified to a certain level along with using targeted temperature management methods in order to decrease metabolic demands in ICU-hospitalized post-OHCA patients. Additionally, withdrawal of life-sustaining therapy as a controversial ethical topic is under constant re-evaluation due to its possible influence on overall mortality rates in patients initially surviving OHCA. Focusing on all of these important points in process of managing ICU patients is an imperative towards better survival and complete recovery rates.
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Affiliation(s)
- Srdjan S Nikolovski
- Pathology and Laboratory Medicine, Cardiovascular Research Institute, Loyola University Chicago Health Science Campus, Maywood, USA
- Emergency Medicine, Serbian Resuscitation Council, Novi Sad, SRB
| | - Aleksandra D Lazic
- Emergency Center, Clinical Center of Vojvodina, Novi Sad, SRB
- Emergency Medicine, Serbian Resuscitation Council, Novi Sad, SRB
| | - Zoran Z Fiser
- Emergency Medicine, Department of Emergency Medicine, Novi Sad, SRB
| | - Ivana A Obradovic
- Anesthesiology, Resuscitation, and Intensive Care, Sveti Vračevi Hospital, Bijeljina, BIH
| | - Jelena Z Tijanic
- Emergency Medicine, Municipal Institute of Emergency Medicine, Kragujevac, SRB
| | - Violetta Raffay
- School of Medicine, European University Cyprus, Nicosia, CYP
- Emergency Medicine, Serbian Resuscitation Council, Novi Sad, SRB
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20
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Gonzalez D, Dahiya G, Mutirangura P, Ergando T, Mello G, Singh R, Bentho O, Elliott AM. Post Cardiac Arrest Care in the Cardiac Intensive Care Unit. Curr Cardiol Rep 2024; 26:35-49. [PMID: 38214836 DOI: 10.1007/s11886-023-02015-0] [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] [Accepted: 12/08/2023] [Indexed: 01/13/2024]
Abstract
PURPOSE OF REVIEW Cardiac arrests constitute a leading cause of mortality in the adult population and cardiologists are often tasked with the management of patients following cardiac arrest either as a consultant or primary provider in the cardiac intensive care unit. Familiarity with evidence-based practice for post-cardiac arrest care is a requisite for optimizing outcomes in this highly morbid group. This review will highlight important concepts necessary to managing these patients. RECENT FINDINGS Emerging evidence has further elucidated optimal care of post-arrest patients including timing for routine coronary angiography, utility of therapeutic hypothermia, permissive hypercapnia, and empiric aspiration pneumonia treatment. The complicated state of multi-organ failure following cardiac arrest needs to be carefully optimized by the clinician to prevent further neurologic injury and promote systemic recovery. Future studies should be aimed at understanding if these findings extend to specific patient populations, especially those at the highest risk for poor outcomes.
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Affiliation(s)
- Daniel Gonzalez
- Department of Medicine, Division of Cardiology, University of Minnesota, 420 Delaware St SE, MMC 508, Minneapolis, MN, 55455, USA
| | - Garima Dahiya
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Duke University, Durham, USA
| | | | | | - Gregory Mello
- University of Minnesota Medical School, Minneapolis, USA
| | - Rahul Singh
- Department of Medicine, Division of Cardiology, University of Minnesota, 420 Delaware St SE, MMC 508, Minneapolis, MN, 55455, USA
| | - Oladi Bentho
- Department of Neurology, University of Minnesota, Minneapolis, USA
| | - Andrea M Elliott
- Department of Medicine, Division of Cardiology, University of Minnesota, 420 Delaware St SE, MMC 508, Minneapolis, MN, 55455, USA.
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21
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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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22
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Turella S, Dankiewicz J, Friberg H, Jakobsen JC, Leithner C, Levin H, Lilja G, Moseby-Knappe M, Nielsen N, Rossetti AO, Sandroni C, Zubler F, Cronberg T, Westhall E. The predictive value of highly malignant EEG patterns after cardiac arrest: evaluation of the ERC-ESICM recommendations. Intensive Care Med 2024; 50:90-102. [PMID: 38172300 PMCID: PMC10811097 DOI: 10.1007/s00134-023-07280-9] [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: 06/22/2023] [Accepted: 11/14/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE The 2021 guidelines endorsed by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) recommend using highly malignant electroencephalogram (EEG) patterns (HMEP; suppression or burst-suppression) at > 24 h after cardiac arrest (CA) in combination with at least one other concordant predictor to prognosticate poor neurological outcome. We evaluated the prognostic accuracy of HMEP in a large multicentre cohort and investigated the added value of absent EEG reactivity. METHODS This is a pre-planned prognostic substudy of the Targeted Temperature Management trial 2. The presence of HMEP and background reactivity to external stimuli on EEG recorded > 24 h after CA was prospectively reported. Poor outcome was measured at 6 months and defined as a modified Rankin Scale score of 4-6. Prognostication was multimodal, and withdrawal of life-sustaining therapy (WLST) was not allowed before 96 h after CA. RESULTS 845 patients at 59 sites were included. Of these, 579 (69%) had poor outcome, including 304 (36%) with WLST due to poor neurological prognosis. EEG was recorded at a median of 71 h (interquartile range [IQR] 52-93) after CA. HMEP at > 24 h from CA had 50% [95% confidence interval [CI] 46-54] sensitivity and 93% [90-96] specificity to predict poor outcome. Specificity was similar (93%) in 541 patients without WLST. When HMEP were unreactive, specificity improved to 97% [94-99] (p = 0.008). CONCLUSION The specificity of the ERC-ESICM-recommended EEG patterns for predicting poor outcome after CA exceeds 90% but is lower than in previous studies, suggesting that large-scale implementation may reduce their accuracy. Combining HMEP with an unreactive EEG background significantly improved specificity. As in other prognostication studies, a self-fulfilling prophecy bias may have contributed to observed results.
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Affiliation(s)
- Sara Turella
- Department of Intensive Care, Emergency Medicine and Anesthesiology, Fondazione Policlinico Universitario "Agostino Gemelli", IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Josef Dankiewicz
- Department of Clinical Sciences Lund, Cardiology, Lund University, Lund, Sweden
| | - Hans Friberg
- Department of Clinical Sciences Lund, Anaesthesia and Intensive Care, Lund University, Lund, Sweden
| | - Janus Christian Jakobsen
- Copenhagen Trial Unit, Capital Region, Copenhagen, Denmark
- Department of Regional Health Research, The Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Christoph Leithner
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Helena Levin
- Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Gisela Lilja
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
- Skane University Hospital, Lund, Sweden
| | - Marion Moseby-Knappe
- Department of Clinical Sciences Lund, Neurology and Rehabilitation, Lund University, Lund, Sweden
| | - Niklas Nielsen
- Department of Clinical Sciences Lund, Anesthesiology and Intensive Care Medicine, Helsingborg Hospital, Helsingborg, Sweden
| | - Andrea O Rossetti
- Department of Neurology, University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Claudio Sandroni
- Department of Intensive Care, Emergency Medicine and Anesthesiology, Fondazione Policlinico Universitario "Agostino Gemelli", IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Frédéric Zubler
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Tobias Cronberg
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
| | - Erik Westhall
- Department of Clinical Sciences, Clinical Neurophysiology, Lund University, S-221 85, Lund, Sweden.
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23
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Berg KM, Bray JE, Ng KC, Liley HG, Greif R, Carlson JN, Morley PT, Drennan IR, Smyth M, Scholefield BR, Weiner GM, Cheng A, Djärv T, Abelairas-Gómez C, Acworth J, Andersen LW, Atkins DL, Berry DC, Bhanji F, Bierens J, Bittencourt Couto T, Borra V, Böttiger BW, Bradley RN, Breckwoldt J, Cassan P, Chang WT, Charlton NP, Chung SP, Considine J, Costa-Nobre DT, Couper K, Dainty KN, Dassanayake V, Davis PG, Dawson JA, de Almeida MF, De Caen AR, Deakin CD, Dicker B, Douma MJ, Eastwood K, El-Naggar W, Fabres JG, Fawke J, Fijacko N, Finn JC, Flores GE, Foglia EE, Folke F, Gilfoyle E, Goolsby CA, Granfeldt A, Guerguerian AM, Guinsburg R, Hatanaka T, Hirsch KG, Holmberg MJ, Hosono S, Hsieh MJ, Hsu CH, Ikeyama T, Isayama T, Johnson NJ, Kapadia VS, Kawakami MD, Kim HS, Kleinman ME, Kloeck DA, Kudenchuk P, Kule A, Kurosawa H, Lagina AT, Lauridsen KG, Lavonas EJ, Lee HC, Lin Y, Lockey AS, Macneil F, Maconochie IK, Madar RJ, Malta Hansen C, Masterson S, Matsuyama T, McKinlay CJD, Meyran D, Monnelly V, Nadkarni V, Nakwa FL, Nation KJ, Nehme Z, Nemeth M, Neumar RW, Nicholson T, Nikolaou N, Nishiyama C, Norii T, Nuthall GA, Ohshimo S, Olasveengen TM, Ong YKG, Orkin AM, Parr MJ, Patocka C, Perkins GD, Perlman JM, Rabi Y, Raitt J, Ramachandran S, Ramaswamy VV, Raymond TT, Reis AG, Reynolds JC, Ristagno G, Rodriguez-Nunez A, Roehr CC, Rüdiger M, Sakamoto T, Sandroni C, Sawyer TL, Schexnayder SM, Schmölzer GM, Schnaubelt S, Semeraro F, Singletary EM, Skrifvars MB, Smith CM, Soar J, Stassen W, Sugiura T, Tijssen JA, Topjian AA, Trevisanuto D, Vaillancourt C, Wyckoff MH, Wyllie JP, Yang CW, Yeung J, Zelop CM, Zideman DA, Nolan JP. 2023 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces. Circulation 2023; 148:e187-e280. [PMID: 37942682 PMCID: PMC10713008 DOI: 10.1161/cir.0000000000001179] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
The International Liaison Committee on Resuscitation engages in a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation and first aid science. Draft Consensus on Science With Treatment Recommendations are posted online throughout the year, and this annual summary provides more concise versions of the final Consensus on Science With Treatment Recommendations from all task forces for the year. Topics addressed by systematic reviews this year include resuscitation of cardiac arrest from drowning, extracorporeal cardiopulmonary resuscitation for adults and children, calcium during cardiac arrest, double sequential defibrillation, neuroprognostication after cardiac arrest for adults and children, maintaining normal temperature after preterm birth, heart rate monitoring methods for diagnostics in neonates, detection of exhaled carbon dioxide in neonates, family presence during resuscitation of adults, and a stepwise approach to resuscitation skills training. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research. Additional topics are addressed with scoping reviews and evidence updates.
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24
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Disanto G, Villa M, Maleska Maceski A, Prosperetti C, Gobbi C, Kuhle J, Cassina T, Agazzi P. Longitudinal serum neurofilament light kinetics in post-anoxic encephalopathy. Ann Clin Transl Neurol 2023; 10:2407-2412. [PMID: 37743737 PMCID: PMC10723239 DOI: 10.1002/acn3.51903] [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: 06/02/2023] [Revised: 09/01/2023] [Accepted: 09/08/2023] [Indexed: 09/26/2023] Open
Abstract
Serum neurofilament light (sNfL) is a promising marker of outcome after cardiac arrest, but its kinetics are unclear. We prospectively measured sNfL concentrations in 62 patients at 0, 1, 3, 5, 7 and 10 days after cardiac arrest. Survivors and non-survivors had similar sNfL at admission (14.2 [8.6-21.9] vs. 22.5 [14.2-46.9] pg/mL) but largely different at 24 h (16.4 [10.2-293] vs. 464.3 [151.8-1658.2], respectively). The AUC for sNfL concentrations predicting death was above 0.95 from Day 1 to 10 (highest on Day 3). Late sNfL measurements may exert prognostic value, especially when early samples are unavailable or prognosis remains unclear.
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Affiliation(s)
- Giulio Disanto
- Neurocenter of Southern Switzerland, Civic Hospital, Ente Ospedaliero CantonaleLuganoSwitzerland
| | - Michele Villa
- Department of Cardiac Anesthesia and Intensive CareCardiocentro Ticino Institute, Ente Ospedaliero CantonaleLuganoSwitzerland
| | - Aleksandra Maleska Maceski
- Department of NeurologyUniversity Hospital and University of BaselBaselSwitzerland
- Multiple Sclerosis Centre and Research Centre for Clinical Neurimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical ResearchUniversity Hospital and University of BaselBaselSwitzerland
| | - Chiara Prosperetti
- Neurocenter of Southern Switzerland, Civic Hospital, Ente Ospedaliero CantonaleLuganoSwitzerland
| | - Claudio Gobbi
- Neurocenter of Southern Switzerland, Civic Hospital, Ente Ospedaliero CantonaleLuganoSwitzerland
| | - Jens Kuhle
- Department of NeurologyUniversity Hospital and University of BaselBaselSwitzerland
- Multiple Sclerosis Centre and Research Centre for Clinical Neurimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical ResearchUniversity Hospital and University of BaselBaselSwitzerland
| | - Tiziano Cassina
- Department of Cardiac Anesthesia and Intensive CareCardiocentro Ticino Institute, Ente Ospedaliero CantonaleLuganoSwitzerland
| | - Pamela Agazzi
- Neurocenter of Southern Switzerland, Civic Hospital, Ente Ospedaliero CantonaleLuganoSwitzerland
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Sohn G, Kim SE. Measurement of thalamus and cortical damages in hypoxic ischemic encephalopathy. IBRO Neurosci Rep 2023; 15:179-185. [PMID: 37731916 PMCID: PMC10507579 DOI: 10.1016/j.ibneur.2023.09.002] [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: 03/12/2023] [Revised: 09/04/2023] [Accepted: 09/04/2023] [Indexed: 09/22/2023] Open
Abstract
Background The thalamic gray-white matter ratios (GWRs) on CT and quantitative suppression ratios (SRs) of background activities on EEG may reflect damages in the thalamus and cerebral hemispheres in patients with hypoxic-ischemic encephalopathy (HIE). Methods The inclusion criteria were (1) cardiac arrest patients over the age of 20 years from March 2010 to March 2020, and (2) patients who had both EEG and brain CT within 7 days after cardiac arrest. The thalamic GWRs were semi-quantitatively measured by using the region of interest (ROI). SRs of background were analyzed with the installed software (Persyst® v13) in EEG machine. Results 175 patients were included among 686 patients with HIE and the thalamic GWRs of 168 patients were successfully measured. 155 patients (89 %) showed poor outcomes. The poor outcome group revealed not only higher SRs, but also lower thalamic GWRs. The thalamic GWRs showed a negative correlation to the SRs (ρ (rho) = -0.36, p < 0.0001 for right side, ρ (rho) = -0.31, p < 0.0001 for left side). The good outcome group showed neither beyond the cut-off values of thalamic GWRs nor SRs [40 % (59/148) VS 0 % (0/20) in right side, p = 0.0005 %, and 28 % (42/148) VS 0 % (0/20) in left side, p = 0.0061]. Conclusion The thalamic GWRs and SRs may reflect the damage in the thalamus and cerebral hemispheres in patients with HIE. Insults in the thalamocortical circuit (TCC) or the thalamus might be responsible for the poor outcome.
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Affiliation(s)
| | - Sung Eun Kim
- Correspondence to: Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan 48108, Republic of Korea.
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Nakamichi Y, Ichibayashi R, Watanabe M, Suzuki G, Serizawa H, Yamamoto S, Masuyama Y, Honda M. Improved Neurological Outcome of Perampanel for Hypoxic-Ischemic Encephalopathy in Patients After Out-of-Hospital Cardiac Arrest Resuscitation. Cureus 2023; 15:e51392. [PMID: 38292945 PMCID: PMC10826245 DOI: 10.7759/cureus.51392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/30/2023] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Although the resuscitation rate for out-of-hospital cardiac arrest (OHCA) patients in Japan is increasing due to the widespread use of automated external defibrillators, the proportion of patients who can return to society remains low at approximately 7%. Many patients have poor neurological outcomes and cannot return to society because of post-resuscitation hypoxic-ischemic encephalopathy. While the resumption of cardiac rhythm is important for patients with OHCA, improving neurological outcomes and returning to society are also important. OBJECTIVES To investigate whether perampanel, an antiepileptic drug that provides neurological protection against stroke and head injury, could improve neurological outcomes in patients resuscitated after OHCA. METHODS The participants included 33 patients with OHCA admitted to our hospital from January 2021 to June 2022 and 33 patients admitted before that time. Perampanel was administered to the patients in the intervention group immediately after resuscitation. We defined a Cerebral Performance Category (CPC) score of 1.2 as a good neurological outcome. RESULTS There was no significant difference in neurological outcomes at intensive care unit discharge between the intervention and non-intervention groups (number of CPC 1.2: 16/33 vs. 9/33); however, neurological outcomes at hospital discharge were significantly better in the intervention group (number of CPC 1.2: 19/33 vs. 9/33 P = 0.01). CONCLUSION The α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate receptor inhibitory and neuronal protective effects of perampanel may have inhibited the progression of hypoxic-ischemic encephalopathy, which develops after the resumption of cardiac rhythm, and suppressed neuronal damage. Early administration of perampanel after resuscitation of patients with OHCA may improve neurological outcomes.
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Affiliation(s)
- Yoshimi Nakamichi
- Emergency Medicine, Toho University Medical Center Omori Hospital, Tokyo, JPN
| | - Ryo Ichibayashi
- Internal Medicine, Toho University Medical Center Sakura Hospital, Chiba, JPN
| | - Masayuki Watanabe
- Emergency Medicine, Toho University Medical Center Omori Hospital, Tokyo, JPN
| | - Ginga Suzuki
- Emergency Medicine, Toho University Medical Center Omori Hospital, Tokyo, JPN
| | - Hibiki Serizawa
- Emergency Medicine, Toho University Medical Center Omori Hospital, Tokyo, JPN
| | - Saki Yamamoto
- Emergency Medicine, Toho University Medical Center Omori Hospital, Tokyo, JPN
| | - Yuka Masuyama
- Emergency Medicine, Toho University Medical Center Omori Hospital, Tokyo, JPN
| | - Mitsuru Honda
- Emergency Medicine, Toho University Medical Center Omori Hospital, Tokyo, JPN
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Orav K, Bosque Varela P, Prüwasser T, Machegger L, Leitinger M, Trinka E, Kuchukhidze G. Post-hypoxic status epilepticus - A distinct subtype of status epilepticus with poor prognosis. Epileptic Disord 2023; 25:823-832. [PMID: 37776308 PMCID: PMC10947449 DOI: 10.1002/epd2.20164] [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: 06/20/2023] [Revised: 08/31/2023] [Accepted: 09/23/2023] [Indexed: 10/02/2023]
Abstract
OBJECTIVE To evaluate the clinical outcome of patients with possible and definitive post-hypoxic status epilepticus (SE) and to describe the SE types in patients with definitive post-hypoxic SE. METHODS Patients with definitive or possible SE resulting from hypoxic brain injury after cardiac arrest (CA) were prospectively recruited. Intermittent EEG was used for the diagnosis of SE according to clinical practice. Two raters blinded to outcome analyzed EEGs retrospectively for possible and definitive SE patterns and background features (frequency, continuity, reactivity, and voltage). Definitive SE was classified according to semiology (ILAE). Mortality and Cerebral Performance Categories (CPC) score were evaluated 1 month after CA. RESULTS We included 64 patients of whom 92% died. Among the survivors, only one patient had a good neurological outcome (CPC 1). No patient survived with a burst suppression pattern, low voltage, or electro-cerebral silence in any EEG. Possible or definitive SE was diagnosed in a median of 47 h (IQR 39-72 h) after CA. EEG criteria for definitive electrographic SE were fulfilled in 39% of patients; in 38% - for electroclinical SE and in 23% - for ictal-interictal continuum (IIC). The outcome did not differ significantly between the three groups. The only patient with good functional outcome belonged to the IIC group. Comatose non-convulsive SE (NCSE) without subtle motor phenomenon occurred in 20% of patients with definitive electrographic SE and outcome was similar to other types of SE. SIGNIFICANCE Possible or definitive SE due to hypoxic brain injury is associated with poor prognosis. The outcome of patients with electrographic SE, electroclinical SE, and IIC did not differ significantly. Outcome was similar in patients with definitive electrographic SE with and without prominent motor features.
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Affiliation(s)
- Kateriine Orav
- Department of Neurology, Member of the European Reference Network EpiCARE, Centre for Cognitive Neuroscience, Christian Doppler University HospitalParacelsus Medical University of SalzburgSalzburgAustria
- Department of NeurologyNorth Estonia Medical CentreTallinnEstonia
| | - Pilar Bosque Varela
- Department of Neurology, Member of the European Reference Network EpiCARE, Centre for Cognitive Neuroscience, Christian Doppler University HospitalParacelsus Medical University of SalzburgSalzburgAustria
| | - Tanja Prüwasser
- Department of Neurology, Member of the European Reference Network EpiCARE, Centre for Cognitive Neuroscience, Christian Doppler University HospitalParacelsus Medical University of SalzburgSalzburgAustria
- Department of MathematicsParis‐Lodron UniversitySalzburgAustria
| | - Lukas Machegger
- Department of Neuroradiology, Christian Doppler University HospitalParacelsus Medical University of SalzburgSalzburgAustria
| | - Markus Leitinger
- Department of Neurology, Member of the European Reference Network EpiCARE, Centre for Cognitive Neuroscience, Christian Doppler University HospitalParacelsus Medical University of SalzburgSalzburgAustria
| | - Eugen Trinka
- Department of Neurology, Member of the European Reference Network EpiCARE, Centre for Cognitive Neuroscience, Christian Doppler University HospitalParacelsus Medical University of SalzburgSalzburgAustria
- Neuroscience InstituteChristian Doppler University HospitalSalzburgAustria
- Karl Landsteiner Institute for Neurorehabilitation and Space NeurologySalzburgAustria
| | - Giorgi Kuchukhidze
- Department of Neurology, Member of the European Reference Network EpiCARE, Centre for Cognitive Neuroscience, Christian Doppler University HospitalParacelsus Medical University of SalzburgSalzburgAustria
- Neuroscience InstituteChristian Doppler University HospitalSalzburgAustria
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Pinero Colon Y, Acar A, Garcia Losarcos N, Fotedar N. Teaching Video NeuroImage: Postanoxic Tonic Eyelid Opening. Neurology 2023; 101:e2056-e2057. [PMID: 37652697 PMCID: PMC10662986 DOI: 10.1212/wnl.0000000000207877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 07/31/2023] [Indexed: 09/02/2023] Open
Affiliation(s)
- Yael Pinero Colon
- From the Neurological Institute (Y.P.C., A.A., N.G.L., N.F.), University Hospitals of Cleveland; and Case Western Reserve University School of Medicine (Y.P.C., A.A., N.G.L., N.F.), Cleveland, OH
| | - Aybuke Acar
- From the Neurological Institute (Y.P.C., A.A., N.G.L., N.F.), University Hospitals of Cleveland; and Case Western Reserve University School of Medicine (Y.P.C., A.A., N.G.L., N.F.), Cleveland, OH
| | - Naiara Garcia Losarcos
- From the Neurological Institute (Y.P.C., A.A., N.G.L., N.F.), University Hospitals of Cleveland; and Case Western Reserve University School of Medicine (Y.P.C., A.A., N.G.L., N.F.), Cleveland, OH
| | - Neel Fotedar
- From the Neurological Institute (Y.P.C., A.A., N.G.L., N.F.), University Hospitals of Cleveland; and Case Western Reserve University School of Medicine (Y.P.C., A.A., N.G.L., N.F.), Cleveland, OH.
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Fenter H, Rossetti AO, Beuchat I. Continuous versus Routine Electroencephalography in the Intensive Care Unit: A Review of Current Evidence. Eur Neurol 2023; 87:17-25. [PMID: 37952533 PMCID: PMC11003555 DOI: 10.1159/000535085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 11/05/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Electroencephalography (EEG) has long been used to detect seizures in patients with disorders of consciousness. In recent years, there has been a drastically increased adoption of continuous EEG (cEEG) in the intensive care units (ICUs). Given the resources necessary to record and interpret cEEG, this is still not available in every center and widespread recommendations to use continuous instead of routine EEG (typically lasting 20 min) are still a matter of some debate. Considering recent literature and personal experience, this review offers a rationale and practical advice to address this question. SUMMARY Despite the development of increasingly performant imaging techniques and several validated biomarkers, EEG remains central to clinicians in the intensive care unit and has been experiencing expanding popularity for at least 2 decades. Not only does EEG allow seizure or status epilepticus detection, which in the ICU often present without clinical movements, but it is also paramount for the prognostic evaluation of comatose patients, especially after cardiac arrest, and for detecting delayed ischemia after subarachnoid hemorrhage. At the end of the last Century, improvements of technical and digital aspects regarding recording and storage of EEG tracings have progressively led to the era of cEEG and automated quantitative analysis. KEY MESSAGES As compared to repeated rEEG, cEEG in comatose patients does not seem to improve clinical prognosis to a relevant extent, despite allowing a more performant of detection ictal events and consequent therapeutic modifications. The choice between cEEG and rEEG must therefore always be patient-tailored.
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Affiliation(s)
- Helene Fenter
- Department of Neurology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Andrea O Rossetti
- Department of Neurology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Isabelle Beuchat
- Department of Neurology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
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30
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Ding X, Shen Z. Electroencephalography Prediction of Neurological Outcomes After Hypoxic-Ischemic Brain Injury: A Systematic Review and Meta-Analysis. Clin EEG Neurosci 2023:15500594231211105. [PMID: 37941351 DOI: 10.1177/15500594231211105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.
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Affiliation(s)
- Xina Ding
- Department of Brain Function, Hospital of Nantong University, No. 20 Xisi Road, Chongchuan District, Nantong City, Jiangsu Province, 226001, China
| | - Zhixiao Shen
- Department of Brain Function, Hospital of Nantong University, No. 20 Xisi Road, Chongchuan District, Nantong City, Jiangsu Province, 226001, China
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31
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Bevers MB. Refining the continuum of neurologic prognosis - Predicting brain death after cardiac arrest. Resuscitation 2023; 192:109990. [PMID: 37805059 DOI: 10.1016/j.resuscitation.2023.109990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 09/27/2023] [Indexed: 10/09/2023]
Affiliation(s)
- Matthew B Bevers
- Division of Neurocritical Care, Brigham and Women's Hospital, Boston, MA, United States
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32
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Villamar MF, Ayub N, Koenig SJ. Automated Seizure Detection in Patients with Cardiac Arrest: A Retrospective Review of Ceribell™ Rapid-EEG Recordings. Neurocrit Care 2023; 39:505-513. [PMID: 36788179 DOI: 10.1007/s12028-023-01681-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 01/23/2023] [Indexed: 02/16/2023]
Abstract
BACKGROUND In patients with cardiac arrest who remain comatose after return of spontaneous circulation, seizures and other abnormalities on electroencephalogram (EEG) are common. Thus, guidelines recommend urgent initiation of EEG for the evaluation of seizures in this population. Point-of-care EEG systems, such as Ceribell™ Rapid Response EEG (Rapid-EEG), allow for prompt initiation of EEG monitoring, albeit through a reduced-channel montage. Rapid-EEG incorporates an automated seizure detection software (Clarity™) to measure seizure burden in real time and alert clinicians at the bedside when a high seizure burden, consistent with possible status epilepticus, is identified. External validation of Clarity is still needed. Our goal was to evaluate the real-world performance of Clarity for the detection of seizures and status epilepticus in a sample of patients with cardiac arrest. METHODS This study was a retrospective review of Rapid-EEG recordings from all the patients who were admitted to the medical intensive care unit at Kent Hospital (Warwick, RI) between 6/1/2021 and 3/18/2022 for management after cardiac arrest and who underwent Rapid-EEG monitoring as part of their routine clinical care (n = 21). Board-certified epileptologists identified events that met criteria for seizures or status epilepticus, as per the 2021 American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology, and evaluated any seizure burden detections generated by Clarity. RESULTS In this study, 4 of 21 patients with cardiac arrest (19.0%) who underwent Rapid-EEG monitoring had multiple electrographic seizures, and 2 of those patients (9.5%) had electrographic status epilepticus within the first 24 h of the study. None of these ictal abnormalities were detected by the Clarity seizure detection system. Clarity showed 0% seizure burden throughout the entirety of all four Rapid-EEG recordings, including the EEG pages that showed definite seizures or status epilepticus. CONCLUSIONS The presence of frequent electrographic seizures and/or status epilepticus can go undetected by Clarity. Timely and careful review of all raw Rapid-EEG recordings by a qualified human EEG reader is necessary to guide clinical care, regardless of Clarity seizure burden measurements.
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Affiliation(s)
- Mauricio F Villamar
- Department of Neurology, The Warren Alpert Medical School of Brown University, Providence, RI, USA.
- Department of Medicine, Kent Hospital, Warwick, RI, USA.
| | - Neishay Ayub
- Department of Neurology, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Seth J Koenig
- Department of Medicine, Kent Hospital, Warwick, RI, USA
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Dhakar MB, Sheikh ZB, Desai M, Desai RA, Sternberg EJ, Popescu C, Baron-Lee J, Rampal N, Hirsch LJ, Gilmore EJ, Maciel CB. Developing a Standardized Approach to Grading the Level of Brain Dysfunction on EEG. J Clin Neurophysiol 2023; 40:553-561. [PMID: 35239553 DOI: 10.1097/wnp.0000000000000919] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE To assess variability in interpretation of electroencephalogram (EEG) background activity and qualitative grading of cerebral dysfunction based on EEG findings, including which EEG features are deemed most important in this determination. METHODS A web-based survey (Qualtrics) was disseminated to electroencephalographers practicing in institutions participating in the Critical Care EEG Monitoring Research Consortium between May 2017 and August 2018. Respondents answered 12 questions pertaining to their training and EEG interpretation practices and graded 40 EEG segments (15-second epochs depicting patients' most stimulated state) using a 6-grade scale. Fleiss' Kappa statistic evaluated interrater agreement. RESULTS Of 110 respondents, 78.2% were attending electroencephalographers with a mean of 8.3 years of experience beyond training. Despite 83% supporting the need for a standardized approach to interpreting the degree of dysfunction on EEG, only 13.6% used a previously published or an institutional grading scale. The overall interrater agreement was fair ( k = 0.35). Having Critical Care EEG Monitoring Research Consortium nomenclature certification (40.9%) or EEG board certification (70%) did not improve interrater agreement ( k = 0.26). Predominant awake frequencies and posterior dominant rhythm were ranked as the most important variables in grading background dysfunction, followed by continuity and reactivity. CONCLUSIONS Despite the preference for a standardized grading scale for background EEG interpretation, the lack of interrater agreement on levels of dysfunction even among experienced academic electroencephalographers unveils a barrier to the widespread use of EEG as a clinical and research neuromonitoring tool. There was reasonable agreement on the features that are most important in this determination. A standardized approach to grading cerebral dysfunction, currently used by the authors, and based on this work, is proposed.
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Affiliation(s)
- Monica B Dhakar
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, Rhode Island, U.S.A
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
| | - Zubeda B Sheikh
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
- Department of Neurology, West Virginia University School of Medicine, Morgantown, West Virginia, U.S.A
| | - Masoom Desai
- Department of Neurology, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma, U.S.A
| | - Raj A Desai
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida College of Pharmacy, Gainesville, Florida, U.S.A
| | - Eliezer J Sternberg
- Division of Neurology, Milford Regional Medical Center, Milford, Massachusetts, U.S.A
- Department of Neurology, University of Massachusetts Medical School, Worcester, Massachusetts, U.S.A
| | - Cristina Popescu
- Department of Social and Public Health, Ohio University, Athens, Ohio, U.S.A
| | - Jacqueline Baron-Lee
- Department of Neurology, UF-Health Shands Hospital, University of Florida College of Medicine, Gainesville, Florida, U.S.A.; and
| | | | - Lawrence J Hirsch
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
| | - Emily J Gilmore
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
| | - Carolina B Maciel
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
- Department of Neurology, UF-Health Shands Hospital, University of Florida College of Medicine, Gainesville, Florida, U.S.A.; and
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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: 5] [Impact Index Per Article: 5.0] [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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35
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Zubler F, Tzovara A. Deep learning for EEG-based prognostication after cardiac arrest: from current research to future clinical applications. Front Neurol 2023; 14:1183810. [PMID: 37560450 PMCID: PMC10408678 DOI: 10.3389/fneur.2023.1183810] [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: 03/10/2023] [Accepted: 07/03/2023] [Indexed: 08/11/2023] Open
Abstract
Outcome prognostication in comatose patients after cardiac arrest (CA) remains to date a challenge. The major determinant of clinical outcome is the post-hypoxic/ischemic encephalopathy. Electroencephalography (EEG) is routinely used to assess neural functions in comatose patients. Currently, EEG-based outcome prognosis relies on visual evaluation by medical experts, which is time consuming, prone to subjectivity, and oblivious to complex patterns. The field of deep learning has given rise to powerful algorithms for detecting patterns in large amounts of data. Analyzing EEG signals of coma patients with deep neural networks with the goal of assisting in outcome prognosis is therefore a natural application of these algorithms. Here, we provide the first narrative literature review on the use of deep learning for prognostication after CA. Existing studies show overall high performance in predicting outcome, relying either on spontaneous or on auditory evoked EEG signals. Moreover, the literature is concerned with algorithmic interpretability, and has shown that largely, deep neural networks base their decisions on clinically or neurophysiologically meaningful features. We conclude this review by discussing considerations that the fields of artificial intelligence and neurology will need to jointly address in the future, in order for deep learning algorithms to break the publication barrier, and to be integrated in clinical practice.
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Affiliation(s)
- Frederic Zubler
- Department of Neurology, Spitalzentrum Biel, University of Bern, Biel/Bienne, Switzerland
| | - Athina Tzovara
- Institute of Computer Science, University of Bern, Bern, Switzerland
- Department of Neurology, Zentrum für Experimentelle Neurologie and Sleep Wake Epilepsy Center—Neurotec, Inselspital University Hospital Bern, Bern, Switzerland
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36
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Pease M, Elmer J, Shahabadi AZ, Mallela AN, Ruiz-Rodriguez JF, Sexton D, Barot N, Gonzalez-Martinez JA, Shutter L, Okonkwo DO, Castellano JF. Predicting posttraumatic epilepsy using admission electroencephalography after severe traumatic brain injury. Epilepsia 2023; 64:1842-1852. [PMID: 37073101 PMCID: PMC11293840 DOI: 10.1111/epi.17622] [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: 09/12/2022] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 04/20/2023]
Abstract
OBJECTIVE Posttraumatic epilepsy (PTE) develops in as many as one third of severe traumatic brain injury (TBI) patients, often years after injury. Analysis of early electroencephalographic (EEG) features, by both standardized visual interpretation (viEEG) and quantitative EEG (qEEG) analysis, may aid early identification of patients at high risk for PTE. METHODS We performed a case-control study using a prospective database of severe TBI patients treated at a single center from 2011 to 2018. We identified patients who survived 2 years postinjury and matched patients with PTE to those without using age and admission Glasgow Coma Scale score. A neuropsychologist recorded outcomes at 1 year using the Expanded Glasgow Outcomes Scale (GOSE). All patients underwent continuous EEG for 3-5 days. A board-certified epileptologist, blinded to outcomes, described viEEG features using standardized descriptions. We extracted 14 qEEG features from an early 5-min epoch, described them using qualitative statistics, then developed two multivariable models to predict long-term risk of PTE (random forest and logistic regression). RESULTS We identified 27 patients with and 35 without PTE. GOSE scores were similar at 1 year (p = .93). The median time to onset of PTE was 7.2 months posttrauma (interquartile range = 2.2-22.2 months). None of the viEEG features was different between the groups. On qEEG, the PTE cohort had higher spectral power in the delta frequencies, more power variance in the delta and theta frequencies, and higher peak envelope (all p < .01). Using random forest, combining qEEG and clinical features produced an area under the curve of .76. Using logistic regression, increases in the delta:theta power ratio (odds ratio [OR] = 1.3, p < .01) and peak envelope (OR = 1.1, p < .01) predicted risk for PTE. SIGNIFICANCE In a cohort of severe TBI patients, acute phase EEG features may predict PTE. Predictive models, as applied to this study, may help identify patients at high risk for PTE, assist early clinical management, and guide patient selection for clinical trials.
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Affiliation(s)
- Matthew Pease
- Department of Neurological Surgery, University of Pittsburgh Medical Center Healthcare System, Pittsburgh, Pennsylvania, USA
| | - Jonathan Elmer
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Critical Care, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Ameneh Zare Shahabadi
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Arka N. Mallela
- Department of Neurological Surgery, University of Pittsburgh Medical Center Healthcare System, Pittsburgh, Pennsylvania, USA
| | | | - Daniel Sexton
- Department of Neurosurgery, Duke University, Durham, North Carolina, USA
| | - Niravkumar Barot
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jorge A. Gonzalez-Martinez
- Department of Neurological Surgery, University of Pittsburgh Medical Center Healthcare System, Pittsburgh, Pennsylvania, USA
| | - Lori Shutter
- Department of Neurological Surgery, University of Pittsburgh Medical Center Healthcare System, Pittsburgh, Pennsylvania, USA
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Critical Care, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - David O. Okonkwo
- Department of Neurological Surgery, University of Pittsburgh Medical Center Healthcare System, Pittsburgh, Pennsylvania, USA
| | - James F. Castellano
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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Tziakouri A, Novy J, Ben-Hamouda N, Rossetti AO. Relationship between serum neuron-specific enolase and EEG after cardiac arrest: A reappraisal. Clin Neurophysiol 2023; 151:100-106. [PMID: 37236128 DOI: 10.1016/j.clinph.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 04/05/2023] [Accepted: 05/01/2023] [Indexed: 05/28/2023]
Abstract
OBJECTIVE Electroencephalogram (EEG) and serum neuron specific enolase (NSE) are frequently used prognosticators after cardiac arrest (CA). This study explored the association between NSE and EEG, considering the role of EEG timing, its background continuity, reactivity, occurrence of epileptiform discharges, and pre-defined malignancy degree. METHODS Retrospective analysis including 445 consecutive adults from a prospective registry, surviving the first 24 hours after CA and undergoing multimodal evaluation. EEG were interpreted blinded to NSE results. RESULTS Higher NSE was associated with poor EEG prognosticators, such as increasing malignancy, repetitive epileptiform discharges and lack of background reactivity, independently of EEG timing (including sedation and temperature). When stratified for background continuity, NSE was higher with repetitive epileptiform discharges, except in the case of suppressed EEGs. This relationship showed some variation according to the recording time. CONCLUSIONS Neuronal injury after CA, reflected by NSE, correlates with several EEG features: increasing EEG malignancy, lack of background reactivity, and presence of repetitive epileptiform discharges. The correlation between epileptiform discharges and NSE is influenced by underlying EEG background and timing. SIGNIFICANCE This study, describing the complex interplay between serum NSE and epileptiform features, suggests that epileptiform discharges reflect neuronal injury particularly in non-suppressed EEG.
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Affiliation(s)
- Andria Tziakouri
- Department of Neurology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jan Novy
- Department of Neurology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Nawfel Ben-Hamouda
- Department of Adult Intensive Care Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Andrea O Rossetti
- Department of Neurology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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Haxhija Z, Seder DB, May TL, Hassager C, Friberg H, Lilja G, Ceric A, Nielsen N, Dankiewicz J. External validation of the CREST model to predict early circulatory-etiology death after out-of-hospital cardiac arrest without initial ST-segment elevation myocardial infarction. BMC Cardiovasc Disord 2023; 23:311. [PMID: 37340361 DOI: 10.1186/s12872-023-03334-4] [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: 12/04/2022] [Accepted: 06/06/2023] [Indexed: 06/22/2023] Open
Abstract
BACKGROUND The CREST model is a prediction model, quantitating the risk of circulatory-etiology death (CED) after cardiac arrest based on variables available at hospital admission, and intend to guide the triage of comatose patients without ST-segment-elevation myocardial infarction after successful cardiopulmonary resuscitation. This study assessed performance of the CREST model in the Target Temperature Management (TTM) trial cohort. METHODS We retrospectively analyzed data from resuscitated out-of-hospital cardiac arrest (OHCA) patients in the TTM-trial. Demographics, clinical characteristics, and CREST variables (history of coronary artery disease, initial heart rhythm, initial ejection fraction, shock at admission and ischemic time > 25 min) were assessed in univariate and multivariable analysis. The primary outcome was CED. The discriminatory power of the logistic regression model was assessed using the C-statistic and goodness of fit was tested according to Hosmer-Lemeshow. RESULTS Among 329 patients eligible for final analysis, 71 (22%) had CED. History of ischemic heart disease, previous arrhythmia, older age, initial non-shockable rhythm, shock at admission, ischemic time > 25 min and severe left ventricular dysfunction were variables associated with CED in univariate analysis. CREST variables were entered into a logistic regression model and the area under the curve for the model was 0.73 with adequate calibration according to Hosmer-Lemeshow test (p = 0.602). CONCLUSIONS The CREST model had good validity and a discrimination capability for predicting circulatory-etiology death after resuscitation from cardiac arrest without ST-segment elevation myocardial infarction. Application of this model could help to triage high-risk patients for transfer to specialized cardiac centers.
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Affiliation(s)
- Zana Haxhija
- Department of Clinical Sciences, Anesthesia and Intensive Care, Lund University, Skane University Hospital, Malmo, Sweden.
- Division of Anesthesia and Intensive Care, Department of Clinical sciences Lund, Lund University, Skane University Hospital, Carl Bertil Laurells gata 9, Malmo, 205 02, Sweden.
| | - David B Seder
- Department of Critical Care Services, Maine Medical Center, Portland Maine, USA
| | - Teresa L May
- Department of Critical Care Services, Maine Medical Center, Portland Maine, USA
| | - Christian Hassager
- Department of Cardiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Hans Friberg
- Department of Clinical Sciences, Anesthesia and Intensive Care, Lund University, Skane University Hospital, Malmo, Sweden
| | - Gisela Lilja
- Department of Clinical sciences, Neurology, Lund University, Skane University Hospital, Lund, Sweden
| | - Ameldina Ceric
- Department of Clinical Sciences, Anesthesia and Intensive Care, Lund University, Skane University Hospital, Malmo, Sweden
| | - Niklas Nielsen
- Department of Clinical Sciences, Anesthesia and Intensive Care, Lund University, Helsingborg Hospital, Helsingborg, Sweden
| | - Josef Dankiewicz
- Department of Clinical Sciences, Cardiology, Lund University, Skane University Hospital, Lund, Sweden
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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: 32] [Impact Index Per Article: 32.0] [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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Kumar A, Ridha M, Claassen J. Prognosis of consciousness disorders in the intensive care unit. Presse Med 2023; 52:104180. [PMID: 37805070 PMCID: PMC10995112 DOI: 10.1016/j.lpm.2023.104180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 10/03/2023] [Indexed: 10/09/2023] Open
Abstract
Assessments of consciousness are a critical part of prognostic algorithms for critically ill patients suffering from severe brain injuries. There have been significant advances in the field of coma science over the past two decades, providing clinicians with more advanced and precise tools for diagnosing and prognosticating disorders of consciousness (DoC). Advanced neuroimaging and electrophysiological techniques have vastly expanded our understanding of the biological mechanisms underlying consciousness, and have helped identify new states of consciousness. One of these, termed cognitive motor dissociation, can predict functional recovery at 1 year post brain injury, and is present in up to 15-20% of patients with DoC. In this chapter, we review several tools that are used to predict DoC, describing their strengths and limitations, from the neurological examination to advanced imaging and electrophysiologic techniques. We also describe multimodal assessment paradigms that can be used to identify covert consciousness and thus help recognize patients with the potential for future recovery and improve our prognostication practices.
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Affiliation(s)
- Aditya Kumar
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA
| | - Mohamed Ridha
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA.
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van Gils PCW, Ruijter BJ, Bloo RJK, van Putten MJAM, Foudraine NA, van Hout MSE, Tromp SC, van Mook WNKA, Rouhl RPW, van Heugten CM, Hofmeijer J. Cognition, emotional state, and quality of life of survivors after cardiac arrest with rhythmic and periodic EEG patterns. Resuscitation 2023:109830. [PMID: 37182824 DOI: 10.1016/j.resuscitation.2023.109830] [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: 02/06/2023] [Revised: 05/03/2023] [Accepted: 05/04/2023] [Indexed: 05/16/2023]
Abstract
AIM Rhythmic and periodic patterns (RPPs) on the electroencephalogram (EEG) in comatose patients after cardiac arrest have been associated with high case fatality rates. A good neurological outcome according to the Cerebral Performance Categories (CPC) has been reported in up to 10% of cases. Data on cognitive, emotional, and quality of life outcomes are lacking. We aimed to provide insight into these outcomes at one-year follow-up. METHODS We assessed outcome of surviving comatose patients after cardiac arrest with RPPs included in the 'treatment of electroencephalographic status epilepticus after cardiopulmonary resuscitation' (TELSTAR) trial at one-year follow-up, including the CPC for functional neurological outcome, a cognitive assessment, the hospital anxiety and depression scale (HADS) for emotional outcomes, and the 36-item short-form health survey (SF-36) for quality of life. Cognitive impairment was defined as a score of more than 1.5 SD below the mean on ≥ 2 (sub)tests within a cognitive domain. RESULTS Fourteen patients were included (median age 58 years, 21% female), of whom 13 had a cognitive impairment. Eleven of 14 were impaired in memory, 9/14 in executive functioning, and 7/14 in attention. The median scores on the HADS and SF-36 were all worse than expected. Based on the CPC alone, 8/14 had a good outcome (CPC 1-2). CONCLUSION Nearly all cardiac arrest survivors with RPPs during the comatose state have cognitive impairments at one-year follow-up. The incidence of anxiety and depression symptoms seem relatively high and quality of life relatively poor, despite 'good' outcomes according to the CPC.
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Affiliation(s)
- Pauline C W van Gils
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands; Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, Enschede, the Netherlands; Limburg Brain Injury Center, Maastricht University, Maastricht, the Netherlands.
| | - Barry J Ruijter
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, Enschede, the Netherlands; Department of Neurology, OLVG, Amsterdam, the Netherlands
| | - Rubia J K Bloo
- Department of medical psychology, Rijnstate Hospital, Arnhem, the Netherlands
| | - Michel J A M van Putten
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, Enschede, the Netherlands; Departments of Neurology and Clinical Neurophysiology, Medisch Spectrum Twente, Enschede, the Netherlands
| | - Norbert A Foudraine
- Department of Intensive Care, VieCuri Medical Center, Venlo, the Netherlands
| | | | - Selma C Tromp
- Departments of Neurology and Clinical Neurophysiology, St. Antonius Hospital, Nieuwegein, the Netherlands; Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Walther N K A van Mook
- Department of Intensive Care Medicine, and Academy for Postgraduate Training, Maastricht University Medical Centre+; School of Health Professions Education, Maastricht University, the Netherlands
| | - Rob P W Rouhl
- Department of Neurology, Maastricht University Medical Centre+, the Netherlands; Academic Centre for Epileptology Kempenhaeghe/MUMC+, the Netherlands
| | - Caroline M van Heugten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands; Limburg Brain Injury Center, Maastricht University, Maastricht, the Netherlands; Department of Neuropsychology and psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Jeannette Hofmeijer
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, Enschede, the Netherlands; Department of Neurology, Rijnstate Hospital, Arnhem, the Netherlands
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Shlobin NA, Aru J, Vicente R, Zemmar A. What happens in the brain when we die? Deciphering the neurophysiology of the final moments in life. Front Aging Neurosci 2023; 15:1143848. [PMID: 37228251 PMCID: PMC10203241 DOI: 10.3389/fnagi.2023.1143848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 04/12/2023] [Indexed: 05/27/2023] Open
Abstract
When do we die and what happens in the brain when we die? The mystery around these questions has engaged mankind for centuries. Despite the challenges to obtain recordings of the dying brain, recent studies have contributed to better understand the processes occurring during the last moments of life. In this review, we summarize the literature on neurophysiological changes around the time of death. Perhaps the only subjective description of death stems from survivors of near-death experiences (NDEs). Hallmarks of NDEs include memory recall, out-of-body experiences, dreaming, and meditative states. We survey the evidence investigating neurophysiological changes of these experiences in healthy subjects and attempt to incorporate this knowledge into the existing literature investigating the dying brain to provide valuations for the neurophysiological footprint and timeline of death. We aim to identify reasons explaining the variations of data between studies investigating this field and provide suggestions to standardize research and reduce data variability.
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Affiliation(s)
- Nathan A. Shlobin
- Department of Neurosurgery, Henan Provincial People’s Hospital, Henan University School of Medicine, Zhengzhou, China
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Raul Vicente
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Ajmal Zemmar
- Department of Neurosurgery, Henan Provincial People’s Hospital, Henan University School of Medicine, Zhengzhou, China
- Department of Neurological Surgery, University of Louisville School of Medicine, Louisville, KY, United States
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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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Lee DA, Park KM, Kim HC, Khoo CS, Lee BI, Kim SE. Spectrum of Ictal-Interictal Continuum: The Significance of 2HELPS2B Score and Background Suppression. J Clin Neurophysiol 2023; 40:364-370. [PMID: 34510091 DOI: 10.1097/wnp.0000000000000894] [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: 11/25/2022] Open
Abstract
PURPOSE The aims of this study were to identify (1) the spectrum of ictal-interictal continuum (IIC) using the two dimensions of 2HELPS2B score and background suppression and (2) the response to subsequent anti-seizure drugs depends on the spectrum of IIC. METHODS The study prospectively enrolled 62 patients with IIC on EEG. The diagnosis of nonconvulsive status epilepticus was attempted with Salzburg criteria as well as clinical and neuroimaging data. IICs were dichotomized into patients with nonconvulsive status epilepticus and coma-IIC. The 2HELPS2B score was evaluated as the original proposal. The suppression ratio was analyzed with Persyst software. RESULTS Forty-seven cases (75.8%) were nonconvulsive status epilepticus-IIC and 15 cases (24.2%) were coma-IIC. Multivariate analysis revealed that the 2HELPS2B score was the only significant variable dichotomizing the spectrum of IIC (odds ratio, 3.0; 95% confidence interval, 1.06-8.6; P = 0.03 for nonconvulsive status epilepticus-IIC). In addition, the suppression ratio was significantly negatively correlated with 2HELPS2B scores (Spearman coefficient = -0.37, P = 0.004 for left hemisphere and Spearman coefficient = -0.3, P = 0.02 for right hemisphere). Furthermore, patients with higher 2HELPS2B score (74% [14/19] in ≥2 points vs. 44% [14/32] in <2 points, P = 0.03 by χ 2 test) and lower suppression ratio (62% [23/37] in ≤2.18 vs. 35% [6/17] in >2.18, P = 0.06 by χ 2 test) seemed to be more responsive to subsequent anti-seizure drug. CONCLUSIONS The 2HELPS2B score and background suppression can be used to distinguish the spectrum of IIC and thereby predict the response to subsequent anti-seizure drug.
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Affiliation(s)
- Dong Ah Lee
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Kang Min Park
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Hyung Chan Kim
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Ching Soong Khoo
- Neurology Unit, Department of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia ; and
| | - Byung In Lee
- Department of Neurology, CHA Ilsan Medical Center, Ilsan, Republic of Korea
| | - Sung Eun Kim
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
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Annoni F, Su F, Peluso L, Lisi I, Caruso E, Pischiutta F, Gouvea Bogossian E, Garcia B, Njimi H, Vincent JL, Gaspard N, Ferlini L, Creteur J, Zanier ER, Taccone FS. Hypertonic sodium lactate infusion reduces vasopressor requirements and biomarkers of brain and cardiac injury after experimental cardiac arrest. Crit Care 2023; 27:161. [PMID: 37087454 PMCID: PMC10122448 DOI: 10.1186/s13054-023-04454-1] [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: 03/08/2023] [Accepted: 04/19/2023] [Indexed: 04/24/2023] Open
Abstract
INTRODUCTION Prognosis after resuscitation from cardiac arrest (CA) remains poor, with high morbidity and mortality as a result of extensive cardiac and brain injury and lack of effective treatments. Hypertonic sodium lactate (HSL) may be beneficial after CA by buffering severe metabolic acidosis, increasing brain perfusion and cardiac performance, reducing cerebral swelling, and serving as an alternative energetic cellular substrate. The aim of this study was to test the effects of HSL infusion on brain and cardiac injury in an experimental model of CA. METHODS After a 10-min electrically induced CA followed by 5 min of cardiopulmonary resuscitation maneuvers, adult swine (n = 35) were randomly assigned to receive either balanced crystalloid (controls, n = 11) or HSL infusion started during cardiopulmonary resuscitation (CPR, Intra-arrest, n = 12) or after return of spontaneous circulation (Post-ROSC, n = 11) for the subsequent 12 h. In all animals, extensive multimodal neurological and cardiovascular monitoring was implemented. All animals were treated with targeted temperature management at 34 °C. RESULTS Thirty-four of the 35 (97.1%) animals achieved ROSC; one animal in the Intra-arrest group died before completing the observation period. Arterial pH, lactate and sodium concentrations, and plasma osmolarity were higher in HSL-treated animals than in controls (p < 0.001), whereas potassium concentrations were lower (p = 0.004). Intra-arrest and Post-ROSC HSL infusion improved hemodynamic status compared to controls, as shown by reduced vasopressor requirements to maintain a mean arterial pressure target > 65 mmHg (p = 0.005 for interaction; p = 0.01 for groups). Moreover, plasma troponin I and glial fibrillary acid protein (GFAP) concentrations were lower in HSL-treated groups at several time-points than in controls. CONCLUSIONS In this experimental CA model, HSL infusion was associated with reduced vasopressor requirements and decreased plasma concentrations of measured biomarkers of cardiac and cerebral injury.
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Affiliation(s)
- Filippo Annoni
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium.
- Experimental Laboratory of Intensive Care, Free University of Brussels, Brussels, Belgium.
| | - Fuhong Su
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
- Experimental Laboratory of Intensive Care, Free University of Brussels, Brussels, Belgium
| | - Lorenzo Peluso
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy
- Department of Anesthesiology and Intensive Care, Humanitas Gavazzeni, Via M Gavazzeni 21, 24125, Bergamo, Italy
| | - Ilaria Lisi
- Laboratory of Traumatic Brain Injury and Neuroprotection, Department of Acute Brain Injury, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
| | - Enrico Caruso
- Laboratory of Traumatic Brain Injury and Neuroprotection, Department of Acute Brain Injury, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
| | - Francesca Pischiutta
- Laboratory of Traumatic Brain Injury and Neuroprotection, Department of Acute Brain Injury, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
| | | | - Bruno Garcia
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
- Experimental Laboratory of Intensive Care, Free University of Brussels, Brussels, Belgium
| | - Hassane Njimi
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
| | - Jean-Louis Vincent
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
| | - Nicolas Gaspard
- Department of Neurology, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
- Neurology Department, School of Medicine, Yale University, New Haven, CT, USA
| | - Lorenzo Ferlini
- Department of Neurology, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
| | - Jacques Creteur
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
| | - Elisa R Zanier
- Laboratory of Traumatic Brain Injury and Neuroprotection, Department of Acute Brain Injury, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
| | - Fabio Silvio Taccone
- Department of Intensive Care, Erasme Hospital, Lennik Road 808, 1070, Brussels, Belgium
- Experimental Laboratory of Intensive Care, Free University of Brussels, Brussels, Belgium
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Lévi-Strauss J, Hmeydia G, Benzakoun J, Bouchereau E, Hermann B, Legouy C, Oppenheim C, Sharshar T, Gavaret M, Pruvost-Robieux E. Discrepancies in the late auditory potentials of post-anoxic patients: watch out for focal brain lesions, a pilot retrospective study. Resuscitation 2023; 187:109801. [PMID: 37085038 DOI: 10.1016/j.resuscitation.2023.109801] [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: 02/02/2023] [Revised: 03/22/2023] [Accepted: 04/11/2023] [Indexed: 04/23/2023]
Abstract
AIMS Late auditory evoked potentials, and notably mismatch negativity (MMN) and P3 responses, can be used as part of the multimodal prognostic evaluation in post-anoxic disorders of consciousness (DOC). MMN response preferentially stems from the temporal cortex and the arcuate fasciculus. Situations with discrepant evaluations, for example MMN absent but P3 present, are frequent and difficult to interpret. We hypothesize that discrepant MMN-/P3+ results could reflect a higher prevalence of lesions in MMN generating regions. This study presents correlations between neurophysiological and neuroradiological results. METHODS This retrospective study was conducted on 38 post-anoxic DOC patients. Brain lesions were analyzed on 3T MRI both anatomically and through computation of the local arcuate fasciculus fractional anisotropy values on Diffusion Tensor Imaging sequences. Neurophysiological data and outcome were also analyzed. RESULTS Our cohort included 8 MMN-/P3+, 7 MMN+/P3+, 21 MMN-/P3- and 2 MMN-/P3+ patients, assessed at a median delay of 20.5 days since cardiac arrest. Our results show that MMN-/P3+ patients tended to have fewer temporal and basal ganglia lesions than MMN-/P3- patients, and more than MMN+/P3+ patients (p-values for trend: p=0.02 for temporal and p=0.02 for basal ganglia lesions). There was a statistical difference across groups for mean fractional anisotropy values in the arcuate fasciculus (p=0.008). The percentage of patients regaining consciousness at three months in MMN-/P3+ patients was higher than in MMN-/P3- patients and lower than in MMN+/P3+ patients. CONCLUSION This study suggests that discrepancies in late auditory evoked potentials may be linked to focal post-anoxic brain lesions, visible on brain MRI.
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Affiliation(s)
- Julie Lévi-Strauss
- University Paris Cité, Paris, France Neurophysiology department, GHU Psychiatry & Neurosciences,Sainte Anne, F-75014 Paris INSERM U 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris.
| | - Ghazi Hmeydia
- University Paris Cité, Paris, France, Neuroradiology department, GHU Psychiatry & Neurosciences, Sainte Anne, F-75014 Paris INSERM UMR 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
| | - Joseph Benzakoun
- University Paris Cité, Paris, France, Neuroradiology department, GHU Psychiatry & Neurosciences, Sainte Anne, F-75014 Paris INSERM UMR 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
| | - Eléonore Bouchereau
- University Paris Cité, Paris, France Neuro-intensive care department, GHU Psychiatry & Neurosciences, Sainte Anne, F-75014 Paris INSERM UMR 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
| | - Bertrand Hermann
- University Paris Cité, Paris, France Neuro-intensive care department, GHU Psychiatry & Neurosciences, Sainte Anne, F-75014 Paris INSERM UMR 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris; University Paris Cité, Paris, France Medical intensive care unit, HEGP Hospital, Assistance Publique - Hôpitaux de Paris-Centre (APHP-Centre), Paris, France; Institut du Cerveau et de la Moelle épinière - ICM, INSERM U1127, CNRS UMR 7225, F-75013, Paris, France
| | - Camille Legouy
- University Paris Cité, Paris, France Neuro-intensive care department, GHU Psychiatry & Neurosciences, Sainte Anne, F-75014 Paris INSERM UMR 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
| | - Catherine Oppenheim
- University Paris Cité, Paris, France, Neuroradiology department, GHU Psychiatry & Neurosciences, Sainte Anne, F-75014 Paris INSERM UMR 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
| | - Tarek Sharshar
- University Paris Cité, Paris, France Neuro-intensive care department, GHU Psychiatry & Neurosciences, Sainte Anne, F-75014 Paris INSERM UMR 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
| | - Martine Gavaret
- University Paris Cité, Paris, France Neurophysiology department, GHU Psychiatry & Neurosciences,Sainte Anne, F-75014 Paris INSERM U 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
| | - Estelle Pruvost-Robieux
- University Paris Cité, Paris, France Neurophysiology department, GHU Psychiatry & Neurosciences,Sainte Anne, F-75014 Paris INSERM U 1266, FHU NeuroVasc, Institut de Psychiatrie et Neurosciences de Paris-IPNP, F-75014 Paris
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Inoue F, Inoue A, Nishimura T, Takahashi R, Nakatani Y, Suga M, Kikuta S, Tada S, Maemura S, Matsuyama S, Ishihara S. PCO 2 on arrival as a predictive biomarker in patients with out-of-hospital cardiac arrest. Am J Emerg Med 2023; 69:92-99. [PMID: 37084483 DOI: 10.1016/j.ajem.2023.04.014] [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: 07/20/2022] [Revised: 03/31/2023] [Accepted: 04/07/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND Treating patients with out-of-hospital cardiac arrest (OHCA) requires early prediction of outcome, ideally on hospital arrival, as it can inform the clinical decisions involved. This study evaluated whether partial pressure of carbon dioxide (PCO2) on arrival is associated with outcome at one month OHCA patients. METHODS This was a single-center retrospective study of adult OHCA patients treated between January 2016 and December 2020. Outcomes were defined along the Cerebral Performance Category (CPC) scale. Primary outcome was mortality (CPC 5) at one month. Secondary outcomes were death or unfavorable neurological outcome (CPC 3-5) and unfavorable neurological outcome (CPC 3-4) at one month. Multivariable analysis was adjusted for age, sex, witnessed cardiac arrest, bystander cardiopulmonary resuscitation, initial shockable rhythm, and time from call to emergency medical services to hospital arrival. RESULTS Out of 977 OHCA patients in the study period, 19 were excluded because they were aged under 18 years, 79 because they underwent extracorporeal cardiopulmonary resuscitation, and 101 due to lack of PCO2 data. This study included 778 patients total; mortality (CPC 5) at one month was observed in 706 (90.7%), death or unfavorable neurological outcome (CPC 3-5) in 743 (95.5%), and unfavorable neurological outcome (CPC 3-4) in 37 (4.8%). In multivariable analysis, high PCO2 levels showed significant association with mortality (CPC 5) at one month (odds ratio [OR] [per 5 mmHg], 1.14; 95% confidence interval [CI], 1.08-1.21), death or unfavorable neurological outcome (CPC 3-5) (OR [per 5 mmHg], 1.29; 95% CI, 1.17-1.42), and unfavorable neurological outcome (CPC 3-4) (OR [per 5 mmHg], 1.21; 95% CI, 1.04-1.41). CONCLUSIONS High PCO2 on arrival was significantly associated with mortality and unfavorable neurological outcome in OHCA patients.
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Affiliation(s)
- Fumiya Inoue
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan; Department of Emergency Medicine, Hiroshima Citizens Hospital, Japan
| | - Akihiko Inoue
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan.
| | - Takeshi Nishimura
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Ryo Takahashi
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Yukihide Nakatani
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Masafumi Suga
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Shota Kikuta
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Shuhei Tada
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Saki Maemura
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Shigenari Matsuyama
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
| | - Satoshi Ishihara
- Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Japan
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McDevitt WM, Farley M, Martin-Lamb D, Jones TJ, Morris KP, Seri S, Scholefield BR. Feasibility of non-invasive neuro-monitoring during extracorporeal membrane oxygenation in children. Perfusion 2023; 38:547-556. [PMID: 35212252 DOI: 10.1177/02676591211066804] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Detection of neurological complications during extracorporeal membrane oxygenation (ECMO) may be enhanced with non-invasive neuro-monitoring. We investigated the feasibility of non-invasive neuro-monitoring in a paediatric intensive care (PIC) setting. METHODS In a single centre, prospective cohort study we assessed feasibility of recruitment, and neuro-monitoring via somatosensory evoked potentials (SSEP), electroencephalography (EEG) and near infrared spectroscopy (NIRS) during venoarterial (VA) ECMO in paediatric patients (0-15 years). Measures were obtained within 24h of cannulation, during an intermediate period, and finally at decannulation or echo stress testing. SSEP/EEG/NIRS measures were correlated with neuro-radiology findings, and clinical outcome assessed via the Pediatric cerebral performance category (PCPC) scale 30 days post ECMO cannulation. RESULTS We recruited 14/20 (70%) eligible patients (median age: 9 months; IQR:4-54, 57% male) over an 18-month period, resulting in a total of 42 possible SSEP/EEG/NIRS measurements. Of these, 32/42 (76%) were completed. Missed recordings were due to lack of access/consent within 24 h of cannulation (5/42, 12%) or PIC death/discharge (5/42, 12%). In each patient, the majority of SSEP (8/14, 57%), EEG (8/14, 57%) and NIRS (11/14, 79%) test results were within normal limits. All patients with abnormal neuroradiology (4/10, 40%), and 6/7 (86%) with poor outcome (PCPC ≥4) developed indirect SSEP, EEG or NIRS measures of neurological complications prior to decannulation. No study-related adverse events or neuro-monitoring data interpreting issues were experienced. CONCLUSION Non-invasive neuro-monitoring (SSEP/EEG/NIRS) during ECMO is feasible and may provide early indication of neurological complications in this high-risk population.
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Affiliation(s)
- William M McDevitt
- Department of Neurophysiology, 156630Birmingham Children's Hospital Birmingham, UK
| | - Margaret Farley
- Paediatric Intensive Care Unit, 156630Birmingham Children's Hospital, Birmingham, UK
| | - Darren Martin-Lamb
- Department of Neurophysiology, 156630Birmingham Children's Hospital Birmingham, UK
| | - Timothy J Jones
- Department of Cardiac Surgery, 156630Birmingham Children's Hospital, Birmingham, UK.,Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | - Kevin P Morris
- Paediatric Intensive Care Unit, 156630Birmingham Children's Hospital, Birmingham, UK.,Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Stefano Seri
- Department of Neurophysiology, 156630Birmingham Children's Hospital Birmingham, UK.,Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, UK
| | - Barnaby R Scholefield
- Paediatric Intensive Care Unit, 156630Birmingham Children's Hospital, Birmingham, UK.,Birmingham Acute Care Research Group, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
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Fordyce CB, Kramer AH, Ainsworth C, Christenson J, Hunter G, Kromm J, Lopez Soto C, Scales DC, Sekhon M, van Diepen S, Dragoi L, Josephson C, Kutsogiannis J, Le May MR, Overgaard CB, Savard M, Schnell G, Wong GC, Belley-Côté E, Fantaneanu TA, Granger CB, Luk A, Mathew R, McCredie V, Murphy L, Teitelbaum J. Neuroprognostication in the Post Cardiac Arrest Patient: A Canadian Cardiovascular Society Position Statement. Can J Cardiol 2023; 39:366-380. [PMID: 37028905 DOI: 10.1016/j.cjca.2022.12.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 12/13/2022] [Accepted: 12/14/2022] [Indexed: 04/08/2023] Open
Abstract
Cardiac arrest (CA) is associated with a low rate of survival with favourable neurologic recovery. The most common mechanism of death after successful resuscitation from CA is withdrawal of life-sustaining measures on the basis of perceived poor neurologic prognosis due to underlying hypoxic-ischemic brain injury. Neuroprognostication is an important component of the care pathway for CA patients admitted to hospital but is complex, challenging, and often guided by limited evidence. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to evaluate the evidence underlying factors or diagnostic modalities available to determine prognosis, recommendations were generated in the following domains: (1) circumstances immediately after CA; (2) focused neurologic exam; (3) myoclonus and seizures; (4) serum biomarkers; (5) neuroimaging; (6) neurophysiologic testing; and (7) multimodal neuroprognostication. This position statement aims to serve as a practical guide to enhance in-hospital care of CA patients and emphasizes the adoption of a systematic, multimodal approach to neuroprognostication. It also highlights evidence gaps.
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Affiliation(s)
- Christopher B Fordyce
- Division of Cardiology, Department of Medicine, Vancouver General Hospital, and the Centre for Cardiovascular Innovation, University of British Columbia, Vancouver, British Columbia.
| | - Andreas H Kramer
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta; Department of Critical Care, University of Calgary, Alberta
| | - Craig Ainsworth
- Division of Cardiology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Jim Christenson
- Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia
| | - Gary Hunter
- Division of Neurology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Julie Kromm
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta; Department of Critical Care, University of Calgary, Alberta
| | - Carmen Lopez Soto
- Department of Critical Care, King's College Hospital NHS Foundation Trust, London, United Kingdom
| | - Damon C Scales
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Mypinder Sekhon
- Division of Critical Care, Department of Medicine, Vancouver General Hospital, Djavad Mowafaghian Centre for Brain Health, International Centre for Repair Discoveries, University of British Columbia, Vancouver, British Columbia
| | - Sean van Diepen
- Department of Critical Care Medicine, University of Alberta, Edmonton, Alberta; Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, Alberta
| | - Laura Dragoi
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Colin Josephson
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta; Department of Critical Care, University of Calgary, Alberta
| | - Jim Kutsogiannis
- Department of Critical Care Medicine, University of Alberta, Edmonton, Alberta
| | - Michel R Le May
- Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, Ontario, Canada
| | - Christopher B Overgaard
- Division of Cardiology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Martin Savard
- Department of Neurological Sciences CHU de Québec - Hôpital de l'Enfant-Jésus Quebec City, Quebec, Canada
| | - Gregory Schnell
- Division of Cardiology, Department of Medicine, University of Calgary, Calgary, Alberta
| | - Graham C Wong
- Division of Cardiology, Department of Medicine, Vancouver General Hospital, and the Centre for Cardiovascular Innovation, University of British Columbia, Vancouver, British Columbia
| | - Emilie Belley-Côté
- Division of Cardiology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Tadeu A Fantaneanu
- Division of Neurology, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | | | - Adriana Luk
- Division of Cardiology, Department of Medicine, University of Toronto and the Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada
| | - Rebecca Mathew
- CAPITAL Research Group, Division of Cardiology, University of Ottawa Heart Institute, and the Faculty of Medicine, Division of Critical Care, University of Ottawa, Ottawa, Ontario, Canada
| | - Victoria McCredie
- Interdepartmental Division of Critical Care Medicine, University of Toronto, the Krembil Research Institute, Toronto Western Hospital, University Health Network, and Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Laurel Murphy
- Departments of Emergency Medicine and Critical Care, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Jeanne Teitelbaum
- Neurological Intensive Care Unit, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Abstract
OBJECTIVES Critically ill patients are at high risk of acute brain injury. Bedside multimodality neuromonitoring techniques can provide a direct assessment of physiologic interactions between systemic derangements and intracranial processes and offer the potential for early detection of neurologic deterioration before clinically manifest signs occur. Neuromonitoring provides measurable parameters of new or evolving brain injury that can be used as a target for investigating various therapeutic interventions, monitoring treatment responses, and testing clinical paradigms that could reduce secondary brain injury and improve clinical outcomes. Further investigations may also reveal neuromonitoring markers that can assist in neuroprognostication. We provide an up-to-date summary of clinical applications, risks, benefits, and challenges of various invasive and noninvasive neuromonitoring modalities. DATA SOURCES English articles were retrieved using pertinent search terms related to invasive and noninvasive neuromonitoring techniques in PubMed and CINAHL. STUDY SELECTION Original research, review articles, commentaries, and guidelines. DATA EXTRACTION Syntheses of data retrieved from relevant publications are summarized into a narrative review. DATA SYNTHESIS A cascade of cerebral and systemic pathophysiological processes can compound neuronal damage in critically ill patients. Numerous neuromonitoring modalities and their clinical applications have been investigated in critically ill patients that monitor a range of neurologic physiologic processes, including clinical neurologic assessments, electrophysiology tests, cerebral blood flow, substrate delivery, substrate utilization, and cellular metabolism. Most studies in neuromonitoring have focused on traumatic brain injury, with a paucity of data on other clinical types of acute brain injury. We provide a concise summary of the most commonly used invasive and noninvasive neuromonitoring techniques, their associated risks, their bedside clinical application, and the implications of common findings to guide evaluation and management of critically ill patients. CONCLUSIONS Neuromonitoring techniques provide an essential tool to facilitate early detection and treatment of acute brain injury in critical care. Awareness of the nuances of their use and clinical applications can empower the intensive care team with tools to potentially reduce the burden of neurologic morbidity in critically ill patients.
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Affiliation(s)
- Swarna Rajagopalan
- Department of Neurology, Cooper Medical School of Rowan University, Camden, NJ
| | - Aarti Sarwal
- Department of Neurology, Atrium Wake Forest School of Medicine, Winston-Salem, NC
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