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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 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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Șerban CA, Barborică A, Roceanu AM, Mîndruță IR, Ciurea J, Stancu M, Pâslaru AC, Zăgrean AM, Zăgrean L, Moldovan M. Towards an electroencephalographic measure of awareness based on the reactivity of oscillatory macrostates to hearing a subject's own name. Eur J Neurosci 2024; 59:771-785. [PMID: 37675619 DOI: 10.1111/ejn.16138] [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: 10/12/2022] [Revised: 08/09/2023] [Accepted: 08/16/2023] [Indexed: 09/08/2023]
Abstract
We proposed that the brain's electrical activity is composed of a sequence of alternating states with repeating topographic spectral distributions on scalp electroencephalogram (EEG), referred to as oscillatory macrostates. The macrostate showing the largest decrease in the probability of occurrence, measured as a percentage (reactivity), during sensory stimulation was labelled as the default EEG macrostate (DEM). This study aimed to assess the influence of awareness on DEM reactivity (DER). We included 11 middle cerebral artery ischaemic stroke patients with impaired awareness having a median Glasgow Coma Scale (GCS) of 6/15 and a group of 11 matched healthy controls. EEG recordings were carried out during auditory 1 min stimulation epochs repeating either the subject's own name (SON) or the SON in reverse (rSON). The DEM was identified across three SON epochs alternating with three rSON epochs. Compared with the patients, the DEM of controls contained more posterior theta activity reflecting source dipoles that could be mapped in the posterior cingulate cortex. The DER was measured from the 1 min quiet baseline preceding each stimulation epoch. The difference in mean DER between the SON and rSON epochs was measured by the salient EEG reactivity (SER) theoretically ranging from -100% to 100%. The SER was 12.4 ± 2.7% (Mean ± standard error of the mean) in controls and only 1.3 ± 1.9% in the patient group (P < 0.01). The patient SER decreased with the Glasgow Coma Scale. Our data suggest that awareness increases DER to SON as measured by SER.
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Affiliation(s)
- Cosmin-Andrei Șerban
- Physics Department, University of Bucharest, Bucharest, Romania
- Termobit Prod SRL, Bucharest, Romania
- FHC Inc, Bowdoin, Maine, USA
| | - Andrei Barborică
- Physics Department, University of Bucharest, Bucharest, Romania
- Termobit Prod SRL, Bucharest, Romania
- FHC Inc, Bowdoin, Maine, USA
| | | | | | - Jan Ciurea
- Department of Neurosurgery, Bagdasar-Arseni Emergency Hospital, Bucharest, Romania
| | - Mihai Stancu
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Division of Neurobiology, Faculty of Biology, Ludwig Maximilian University, Munich, Germany
| | - Alexandru C Pâslaru
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Zăgrean
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Leon Zăgrean
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihai Moldovan
- Termobit Prod SRL, Bucharest, Romania
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
- Clinical Neurophysiology and Neurology, Rigshospitalet, Copenhagen, Denmark
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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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Qing K, Alkhachroum A, Claassen J, Forgacs P, Schiff N. The Electrographic Effects of Ketamine on Patients With Refractory Status Epilepticus After Cardiac Arrest: A Single-Center Retrospective Cohort. J Clin Neurophysiol 2024:00004691-990000000-00119. [PMID: 38194637 DOI: 10.1097/wnp.0000000000001065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024] Open
Abstract
PURPOSE To investigate the effects of ketamine on patients with refractory status epilepticus after cardiac arrest. METHODS In this retrospective cohort, selected EEG segments from patients after cardiac arrest were classified into different EEG patterns (based on background continuity and burden of epileptiform discharges) and spectral profiles (based on the presence of frequency components). For patients who received ketamine, EEG data were compared before, during, and after ketamine infusion; for the no-ketamine group, EEG data were compared at three separated time points during recording. Ketamine usage was determined by clinical providers. Electrographic improvement in epileptiform activity was scored, and the odds ratio was calculated using the Fisher exact test. Functional outcome measures at time of discharge were also examined. RESULTS Of a total of 38 patients with postcardiac arrest refractory status epilepticus, 13 received ketamine and 25 did not. All patients were on ≥2 antiseizure medications including at least one sedative infusion (midazolam). For the ketamine group, eight patients had electrographic improvement, compared with only two patients in the no-ketamine group, with an odds ratio of 7.19 (95% confidence interval 1.16-44.65, P value of 0.0341) for ketamine versus no ketamine. Most of the patients who received ketamine had myoclonic status epilepticus, and overall neurologic outcomes were poor with no patients having a favorable outcome. CONCLUSIONS For postarrest refractory status epilepticus, ketamine use was associated with electrographic improvement, but with the available data, it is unclear whether ketamine use or EEG improvement can be linked to better functional recovery.
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Affiliation(s)
- Kurt Qing
- Department of Neurology, New York-Presbyterian Hospital Weill Cornell, New York, New York, U.S.A
| | - Ayham Alkhachroum
- Department of Neurology, University of Miami, Miami, Florida, U.S.A.; and
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York, New York, U.S.A
| | - Peter Forgacs
- Department of Neurology, New York-Presbyterian Hospital Weill Cornell, New York, New York, U.S.A
| | - Nicholas Schiff
- Department of Neurology, New York-Presbyterian Hospital Weill Cornell, New York, New York, U.S.A
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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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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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Horn J, Admiraal M, Hofmeijer J. Diagnosis and management of seizures and myoclonus after cardiac arrest. EUROPEAN HEART JOURNAL. ACUTE CARDIOVASCULAR CARE 2023; 12:525-531. [PMID: 37486703 DOI: 10.1093/ehjacc/zuad086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 07/25/2023]
Affiliation(s)
- Janneke Horn
- Department of Intensive care Medicine, AmsterdamUMC, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Neurosciences Institute, AmsterdamUMC, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Marjolein Admiraal
- Neurosciences Institute, AmsterdamUMC, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Department of Neurology and Clinical Neurophysiology, AmsterdamUMC, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Jeannette Hofmeijer
- Department of Clinical Neurophysiology, Technical Medical Center, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
- Department of Neurology, Rijnstate Hospital, Wagnerlaan 55, 6815 AD Arnhem, The Netherlands
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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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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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Neurophysiological and Clinical Correlates of Acute Posthypoxic Myoclonus. J Clin Neurophysiol 2023; 40:117-122. [PMID: 36521068 DOI: 10.1097/wnp.0000000000000937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
SUMMARY Prognostication following cardiorespiratory arrest relies on the neurological examination, which is supported by neuroimaging and neurophysiological testing. Acute posthypoxic myoclonus (PHM) is a clinical entity that has prognostic significance and historically has been considered an indicator of poor outcome, but this is not invariably the case. "Malignant" and more "benign" forms of acute PHM have been described and differentiating them is key in understanding their meaning in prognosis. Neurophysiological tests, electroencephalogram in particular, and clinical phenotyping are crucial in defining subtypes of acute PHM. This review describes the neurophysiological and phenotypic markers of malignant and benign forms of acute PHM, a clinical approach to evaluating acute PHM following cardiorespiratory arrest in determining prognosis, and gaps in our understanding of acute PHM that require further study.
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Yu S, Wu C, Zhu Y, Diao M, Hu W. Rat model of asphyxia-induced cardiac arrest and resuscitation. Front Neurosci 2023; 16:1087725. [PMID: 36685224 PMCID: PMC9846144 DOI: 10.3389/fnins.2022.1087725] [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: 11/02/2022] [Accepted: 12/07/2022] [Indexed: 01/05/2023] Open
Abstract
Neurologic injury after cardiopulmonary resuscitation is the main cause of the low survival rate and poor quality of life among patients who have experienced cardiac arrest. In the United States, as the American Heart Association reported, emergency medical services respond to more than 347,000 adults and more than 7,000 children with out-of-hospital cardiac arrest each year. In-hospital cardiac arrest is estimated to occur in 9.7 per 1,000 adult cardiac arrests and 2.7 pediatric events per 1,000 hospitalizations. Yet the pathophysiological mechanisms of this injury remain unclear. Experimental animal models are valuable for exploring the etiologies and mechanisms of diseases and their interventions. In this review, we summarize how to establish a standardized rat model of asphyxia-induced cardiac arrest. There are four key focal areas: (1) selection of animal species; (2) factors to consider during modeling; (3) intervention management after return of spontaneous circulation; and (4) evaluation of neurologic function. The aim was to simplify a complex animal model, toward clarifying cardiac arrest pathophysiological processes. It also aimed to help standardize model establishment, toward facilitating experiment homogenization, convenient interexperimental comparisons, and translation of experimental results to clinical application.
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12
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Holla SK, Krishnamurthy PV, Subramaniam T, Dhakar MB, Struck AF. Electrographic Seizures in the Critically Ill. Neurol Clin 2022; 40:907-925. [PMID: 36270698 PMCID: PMC10508310 DOI: 10.1016/j.ncl.2022.03.015] [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: 12/13/2022]
Abstract
Identifying and treating critically ill patients with seizures can be challenging. In this article, the authors review the available data on patient populations at risk, seizure prognostication with tools such as 2HELPS2B, electrographic seizures and the various ictal-interictal continuum patterns with their latest definitions and associated risks, ancillary testing such as imaging studies, serum biomarkers, and invasive multimodal monitoring. They also illustrate 5 different patient scenarios, their treatment and outcomes, and propose recommendations for targeted treatment of electrographic seizures in critically ill patients.
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Affiliation(s)
- Smitha K Holla
- Department of Neurology, UW Medical Foundation Centennial building, 1685 Highland Avenue, Madison, WI 53705, USA.
| | | | - Thanujaa Subramaniam
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 15 York Street, Building LLCI, 10th Floor, Suite 1003 New Haven, CT 06520, USA
| | - Monica B Dhakar
- Department of Neurology, The Warren Alpert Medical School of Brown University, 593 Eddy St, APC 5, Providence, RI 02903, USA
| | - Aaron F Struck
- Department of Neurology, UW Medical Foundation Centennial building, 1685 Highland Avenue, Madison, WI 53705, USA; William S Middleton Veterans Hospital, Madison WI, USA
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13
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A Simplified Electroencephalography Montage and Interpretation for Evaluation of Comatose Patients in the ICU. Crit Care Explor 2022; 4:e0781. [DOI: 10.1097/cce.0000000000000781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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14
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Repetitive Electroencephalography as Biomarker for the Prediction of Survival in Patients with Post-Hypoxic Encephalopathy. J Clin Med 2022; 11:jcm11216253. [DOI: 10.3390/jcm11216253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 11/07/2022] Open
Abstract
Predicting survival in patients with post-hypoxic encephalopathy (HE) after cardiopulmonary resuscitation is a challenging aspect of modern neurocritical care. Here, continuous electroencephalography (cEEG) has been established as the gold standard for neurophysiological outcome prediction. Unfortunately, cEEG is not comprehensively available, especially in rural regions and developing countries. The objective of this monocentric study was to investigate the predictive properties of repetitive EEGs (rEEGs) with respect to 12-month survival based on data for 199 adult patients with HE, using log-rank and multivariate Cox regression analysis (MCRA). A total number of 59 patients (29.6%) received more than one EEG during the first 14 days of acute neurocritical care. These patients were analyzed for the presence of and changes in specific EEG patterns that have been shown to be associated with favorable or poor outcomes in HE. Based on MCRA, an initially normal amplitude with secondary low-voltage EEG remained as the only significant predictor for an unfavorable outcome, whereas all other relevant parameters identified by univariate analysis remained non-significant in the model. In conclusion, rEEG during early neurocritical care may help to assess the prognosis of HE patients if cEEG is not available.
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15
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Hwang J, Cho SM, Ritzl EK. Recent applications of quantitative electroencephalography in adult intensive care units: a comprehensive review. J Neurol 2022; 269:6290-6309. [DOI: 10.1007/s00415-022-11337-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 10/15/2022]
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16
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Sharma S, Nunes M, Alkhachroum A. Adult Critical Care Electroencephalography Monitoring for Seizures: A Narrative Review. Front Neurol 2022; 13:951286. [PMID: 35911927 PMCID: PMC9334872 DOI: 10.3389/fneur.2022.951286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 06/22/2022] [Indexed: 11/13/2022] Open
Abstract
Electroencephalography (EEG) is an important and relatively inexpensive tool that allows intensivists to monitor cerebral activity of critically ill patients in real time. Seizure detection in patients with and without acute brain injury is the primary reason to obtain an EEG in the Intensive Care Unit (ICU). In response to the increased demand of EEG, advances in quantitative EEG (qEEG) created an approach to review large amounts of data instantly. Finally, rapid response EEG is now available to reduce the time to detect electrographic seizures in limited-resource settings. This review article provides a concise overview of the technical aspects of EEG monitoring for seizures, clinical indications for EEG, the various available modalities of EEG, common and challenging EEG patterns, and barriers to EEG monitoring in the ICU.
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Affiliation(s)
- Sonali Sharma
- Department of Neurology, University of Miami, Miami, FL, United States
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, United States
| | - Michelle Nunes
- Department of Neurology, University of Miami, Miami, FL, United States
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, United States
| | - Ayham Alkhachroum
- Department of Neurology, University of Miami, Miami, FL, United States
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, United States
- *Correspondence: Ayham Alkhachroum
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17
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Bouyaknouden D, Peddada TN, Ravishankar N, Fatima S, Fong-Isariyawongse J, Gilmore EJ, Lee JW, Struck AF, Gaspard N. Neurological Prognostication After Hypoglycemic Coma: Role of Clinical and EEG Findings. Neurocrit Care 2022; 37:273-280. [PMID: 35437670 DOI: 10.1007/s12028-022-01495-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 03/17/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Hypoglycemic coma (HC) is an uncommon but severe clinical condition associated with poor neurological outcome. There is a dearth of robust neurological prognostic factors after HC. On the other hand, there is an increasing body of literature on reliable prognostic markers in the postanoxic coma, a similar-albeit not identical-situation. The objective of this study was thus to investigate the use and predictive value of these markers in HC. METHODS We conducted a retrospective, multicenter, cohort study within five centers of the Critical Care EEG Monitoring Research Consortium. We queried our electroencephalography (EEG) databases to identify all patients undergoing continuous EEG monitoring after admission to an intensive care unit with HC (defined as Glasgow Coma Scale < 8 on admission and a first blood glucose level < 50 mg/dL or not documented but in an obvious clinical context) between 01/01/2010 and 12/31/2020. We studied the association of findings at neurological examination (Glasgow Coma Scale motor subscale, pupillary light and corneal reflexes) and at continuous EEG monitoring(highly malignant patterns, reactivity, periodic discharges, seizures) with best neurological outcome within 3 months after hospital discharge, defined by the Cerebral Performance Category as favorable (1-3: recovery of consciousness) versus unfavorable (4-5: lack of recovery of consciousness). RESULTS We identified 60 patients (30 [50%] women; age 62 [51-72] years). Thirty-one and 29 patients had a favorable and unfavorable outcome, respectively. The presence of pupillary reflexes (24 [100%] vs. 17 [81%]; p value 0.04) and a motor subscore > 2 (22 [92%] vs. 12 [63%]; p value 0.03) at 48-72 h were associated with a favorable outcome. A highly malignant EEG pattern was observed in 7 of 29 (24%) patients with unfavorable outcome versus 0 of 31 (0%) with favorable outcome, whereas the presence of EEG reactivity was observed in 28 of 31 (90%) patients with favorable outcome versus 13 of 29 (45%) with unfavorable outcome (p < 0.001 for comparison of all background categories). CONCLUSIONS This preliminary study suggests that highly malignant EEG patterns might be reliable prognostic markers of unfavorable outcome after HC. Other EEG findings, including lack of EEG reactivity and seizures and clinical findings appear less accurate. These findings should be replicated in a larger multicenter prospective study.
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Affiliation(s)
- Douaae Bouyaknouden
- Department of Neurology, Hôpital Erasme - Cliniques Universitaires de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Teja N Peddada
- Department of Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | | | - Safoora Fatima
- Department of Neurology, University of Wisconsin, Madison, WI, USA
| | | | - Emily J Gilmore
- Department of Neurology, Yale University, New Haven, CT, USA
| | - Jong Woo Lee
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Aaron F Struck
- Department of Neurology, University of Wisconsin, Madison, WI, USA.,William S. Middleton Veterans Hospital, Madison, WI, USA
| | - Nicolas Gaspard
- Department of Neurology, Hôpital Erasme - Cliniques Universitaires de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium. .,Department of Neurology, Yale University, New Haven, CT, USA.
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18
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Shoaib M, Choudhary RC, Chillale RK, Kim N, Miyara SJ, Haque S, Yin T, Frankfurt M, Molmenti EP, Zanos S, Kim J, Becker LB. Metformin-mediated mitochondrial protection post-cardiac arrest improves EEG activity and confers neuroprotection and survival benefit. FASEB J 2022; 36:e22307. [PMID: 35394702 DOI: 10.1096/fj.202200121r] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 03/09/2022] [Accepted: 03/28/2022] [Indexed: 12/25/2022]
Abstract
Cardiac arrest (CA) produces global ischemia/reperfusion injury resulting in substantial multiorgan damage. There are limited efficacious therapies to save lives despite CA being such a lethal disease process. The small population of surviving patients suffer extensive brain damage that results in substantial morbidity. Mitochondrial dysfunction in most organs after CA has been implicated as a major source of injury. Metformin, a first-line treatment for diabetes, has shown promising results in the treatment for other diseases and is known to interact with the mitochondria. For the treatment of CA, prior studies have utilized metformin in a preconditioning manner such that animals are given metformin well before undergoing CA. As the timing of CA is quite difficult to predict, the present study, in a clinically relevant manner, sought to evaluate the therapeutic benefits of metformin administration immediately after resuscitation using a 10 min asphxyial-CA rat model. This is the first study to show that metformin treatment post-CA (a) improves 72 h survival and neurologic function, (b) protects mitochondrial function with a reduction in apoptotic brain injury without activating AMPK, and (c) potentiates earlier normalization of brain electrophysiologic activity. Overall, as an effective and safe drug, metformin has the potential to be an easily translatable intervention for improving survival and preventing brain damage after CA.
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Affiliation(s)
- Muhammad Shoaib
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.,Laboratory for Critical Care Physiology, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA.,Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA
| | - Rishabh C Choudhary
- Laboratory for Critical Care Physiology, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA.,Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA.,Department of Emergency Medicine, Northwell Health, Manhasset, New York, USA
| | - Rupesh K Chillale
- Neural System Laboratory, University of Maryland, College Park, Maryland, USA
| | - Nancy Kim
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.,Laboratory for Critical Care Physiology, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA
| | - Santiago J Miyara
- Laboratory for Critical Care Physiology, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA.,Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA.,Elmezzi Graduate School of Molecular Medicine, Manhasset, New York, USA
| | - Shabirul Haque
- Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA
| | - Tai Yin
- Laboratory for Critical Care Physiology, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA.,Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA
| | - Maya Frankfurt
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.,Molecular Medicine and Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA
| | | | - Stavros Zanos
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA
| | - Junhwan Kim
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.,Laboratory for Critical Care Physiology, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA.,Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA.,Department of Emergency Medicine, Northwell Health, Manhasset, New York, USA.,Molecular Medicine and Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA
| | - Lance B Becker
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.,Laboratory for Critical Care Physiology, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA.,Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, New York, USA.,Department of Emergency Medicine, Northwell Health, Manhasset, New York, USA.,Molecular Medicine and Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA
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Outcome Prediction of Postanoxic Coma: A Comparison of Automated Electroencephalography Analysis Methods. Neurocrit Care 2022; 37:248-258. [PMID: 35233717 PMCID: PMC9343315 DOI: 10.1007/s12028-022-01449-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 01/10/2022] [Indexed: 12/03/2022]
Abstract
Background To compare three computer-assisted quantitative electroencephalography (EEG) prediction models for the outcome prediction of comatose patients after cardiac arrest regarding predictive performance and robustness to artifacts. Methods A total of 871 continuous EEGs recorded up to 3 days after cardiac arrest in intensive care units of five teaching hospitals in the Netherlands were retrospectively analyzed. Outcome at 6 months was dichotomized as “good” (Cerebral Performance Category 1–2) or “poor” (Cerebral Performance Category 3–5). Three prediction models were implemented: a logistic regression model using two quantitative features, a random forest model with nine features, and a deep learning model based on a convolutional neural network. Data from two centers were used for training and fivefold cross-validation (n = 663), and data from three other centers were used for external validation (n = 208). Model output was the probability of good outcome. Predictive performances were evaluated by using receiver operating characteristic analysis and the calculation of predictive values. Robustness to artifacts was evaluated by using an artifact rejection algorithm, manually added noise, and randomly flattened channels in the EEG. Results The deep learning network showed the best overall predictive performance. On the external test set, poor outcome could be predicted by the deep learning network at 24 h with a sensitivity of 54% (95% confidence interval [CI] 44–64%) at a false positive rate (FPR) of 0% (95% CI 0–2%), significantly higher than the logistic regression (sensitivity 33%, FPR 0%) and random forest models (sensitivity 13%, FPR, 0%) (p < 0.05). Good outcome at 12 h could be predicted by the deep learning network with a sensitivity of 78% (95% CI 52–100%) at a FPR of 12% (95% CI 0–24%) and by the logistic regression model with a sensitivity of 83% (95% CI 83–83%) at a FPR of 3% (95% CI 3–3%), both significantly higher than the random forest model (sensitivity 1%, FPR 0%) (p < 0.05). The results of the deep learning network were the least affected by the presence of artifacts, added white noise, and flat EEG channels. Conclusions A deep learning model outperformed logistic regression and random forest models for reliable, robust, EEG-based outcome prediction of comatose patients after cardiac arrest.
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20
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Serban CA, Barborica A, Roceanu AM, Mindruta I, Ciurea J, Pâslaru AC, Zăgrean AM, Zăgrean L, Moldovan M. A method to assess the default EEG macrostate and its reactivity to stimulation. Clin Neurophysiol 2021; 134:50-64. [PMID: 34973517 DOI: 10.1016/j.clinph.2021.12.002] [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: 02/07/2021] [Revised: 08/23/2021] [Accepted: 12/04/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE The default mode network (DMN) is deactivated by stimulation. We aimed to assess the DMN reactivity impairment by routine EEG recordings in stroke patients with impaired consciousness. METHODS Binocular light flashes were delivered at 1 Hz in 1-minute epochs, following a 1-minute baseline (PRE). The EEG was decomposed in a series of binary oscillatory macrostates by topographic spectral clustering. The most deactivated macrostate was labeled the default EEG macrostate (DEM). Its reactivity (DER) was quantified as the decrease in DEM occurrence probability during stimulation. A normalized DER index (DERI) was calculated as DER/PRE. The measures were compared between 14 healthy controls and 32 comatose patients under EEG monitoring following an acute stroke. RESULTS The DEM was mapped to the posterior DMN hubs. In the patients, these DEM source dipoles were 3-4 times less frequent and were associated with an increased theta activity. Even in a reduced 6-channel montage, a DER below 6.26% corresponding to a DERI below 0.25 could discriminate the patients with sensitivity and specificity well above 80%. CONCLUSION The method detected the DMN impairment in post-stroke coma patients. SIGNIFICANCE The DEM and its reactivity to stimulation could be useful to monitor the DMN function at bedside.
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Affiliation(s)
- Cosmin-Andrei Serban
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | - Andrei Barborica
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | | | - Ioana Mindruta
- Neurology Department, University Emergency Hospital, Bucharest, Romania.
| | - Jan Ciurea
- Department of Neurosurgery, Bagdasar-Arseni Emergency Hospital, Bucharest, Romania.
| | - Alexandru C Pâslaru
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Leon Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihai Moldovan
- Termobit Prod SRL, Bucharest, Romania; Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania; Neuroscience, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Neurophysiology, Rigshospitalet, Copenhagen, Denmark.
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21
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Neuroprognostication after Cardiac Arrest: Who Recovers? Who Progresses to Brain Death? Semin Neurol 2021; 41:606-618. [PMID: 34619784 DOI: 10.1055/s-0041-1733789] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Approximately 15% of deaths in developed nations are due to sudden cardiac arrest, making it the most common cause of death worldwide. Though high-quality cardiopulmonary resuscitation has improved overall survival rates, the majority of survivors remain comatose after return of spontaneous circulation secondary to hypoxic ischemic injury. Since the advent of targeted temperature management, neurologic recovery has improved substantially, but the majority of patients are left with neurologic deficits ranging from minor cognitive impairment to persistent coma. Of those who survive cardiac arrest, but die during their hospitalization, some progress to brain death and others die after withdrawal of life-sustaining treatment due to anticipated poor neurologic prognosis. Here, we discuss considerations neurologists must make when asked, "Given their recent cardiac arrest, how much neurologic improvement do we expect for this patient?"
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EEG patterns and their correlations with short- and long-term mortality in patients with hypoxic encephalopathy. Clin Neurophysiol 2021; 132:2851-2860. [PMID: 34598037 DOI: 10.1016/j.clinph.2021.07.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 06/29/2021] [Accepted: 07/20/2021] [Indexed: 11/21/2022]
Abstract
OBJECTIVE To analyze the association between electroencephalographic (EEG) patterns and overall, short- and long-term mortality in patients with hypoxic encephalopathy (HE). METHODS Retrospective, mono-center analysis of 199 patients using univariate log-rank tests (LR) and multivariate cox regression (MCR). RESULTS Short-term mortality, defined as death within 30-days post-discharge was 54.8%. Long-term mortality rates were 69.8%, 71.9%, and 72.9%, at 12-, 24-, and 36-months post-HE, respectively. LR revealed a significant association between EEG suppression (SUP) and short-term mortality, and identified low voltage EEG (LV), burst suppression (BSP), periodic discharges (PD) and post-hypoxic status epilepticus (PSE) as well as missing (aBA) or non-reactive background activity (nrBA) as predictors for overall, short- and long-term mortality. MCR indicated SUP, LV, BSP, PD, aBA and nrBA as significantly associated with overall and short-term mortality to varying extents. LV and BSP were significant predictors for long-term mortality in short-term survivors. Rhythmic delta activity, stimulus induced rhythmic, periodic or ictal discharges and sharp waves were not significantly associated with a higher mortality. CONCLUSION The presence of several specific EEG patterns can help to predict overall, short- and long-term mortality in HE patients. SIGNIFICANCE The present findings may help to improve the challenging prognosis estimation in HE patients.
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Association of Standard Electroencephalography Findings With Mortality and Command Following in Mechanically Ventilated Patients Remaining Unresponsive After Sedation Interruption. Crit Care Med 2021; 49:e423-e432. [PMID: 33591021 DOI: 10.1097/ccm.0000000000004874] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
CONTEXT Delayed awakening after sedation interruption is frequent in critically ill patients receiving mechanical ventilation. OBJECTIVES We aimed to investigate the association of standard electroencephalography with mortality and command following in this setting. DESIGN, SETTING, AND PATIENTS In a single-center study, we retrospectively analyzed standard electroencephalography performed in consecutive mechanically ventilated patients remaining unresponsive (comatose/stuporous or unable to follow commands) after sedation interruption. Standard electroencephalography parameters (background activity, continuity, and reactivity) were reassessed by neurophysiologists, blinded to patients' outcome. Patients were categorized during follow-up into three groups based on their best examination as: 1) command following, 2) unresponsive, or 3) deceased. Cause-specific models were used to identify independent standard electroencephalography parameters associated with main outcomes, that is, mortality and command following. Follow-up was right-censored 30 days after standard electroencephalography. MEASUREMENTS AND MAIN RESULTS Main standard electroencephalography parameters recorded in 121 unresponsive patients (median time between sedation interruption and standard electroencephalography: 2 d [interquartile range, 1-4 d]) consisted of a background frequency greater than 4 Hz in 71 (59%), a discontinuous background in 19 (16%), and a preserved reactivity in 98/120 (82%) patients. At 30 days, 66 patients (55%) were command following, nine (7%) were unresponsive, and 46 (38%) had died. In a multivariate analysis adjusted for nonneurologic organ failure, a reactive standard electroencephalography with a background frequency greater than 4 Hz was independently associated with a reduced risk of death (cause-specific hazard ratio, 0.38; CI 95%, 0.16-0.9). By contrast, none of the standard electroencephalography parameters were independently associated with command following. Sensitivity analyses conducted after exclusion of 29 patients with hypoxic brain injury revealed similar findings. CONCLUSIONS In patients remaining unresponsive after sedation interruption, a pattern consisting of a reactive standard electroencephalography with a background frequency greater than 4 Hz was associated with decreased odds of death. None of the standard electroencephalography parameters were independently associated with command following.
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Bouchereau E, Sharshar T, Legouy C. Delayed awakening in neurocritical care. Rev Neurol (Paris) 2021; 178:21-33. [PMID: 34392974 DOI: 10.1016/j.neurol.2021.06.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 02/07/2023]
Abstract
Delayed awakening is defined as a persistent disorder of arousal or consciousness 48 to 72h after sedation interruption in critically ill patients. Delayed awakening is either a component of coma or delirium. It results in longer hospital stays and increased mortality. It is therefore a diagnostic, therapeutic and prognostic emergency. In severe brain injured patients, delayed awakening may be related to the primary neurological injury or to secondary systemic insults related to organ failure associated with intensive care. In the present review, we propose diagnostic, therapeutic and prognostic algorithms for managing delayed awaking in neuro-ICU brain injured patients.
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Affiliation(s)
- E Bouchereau
- G.H.U Paris Psychiatry & Neurosciences, department of Neurocritical care, Service d'Anesthésie-Réanimation Neurochirurgicale, 1, rue Cabanis, 75674 Paris Cedex 14, France; INSERM U1266, FHU NeuroVasc, Institut de Psychiatrie et Neuroscience de Paris, Paris, France
| | - T Sharshar
- G.H.U Paris Psychiatry & Neurosciences, department of Neurocritical care, Service d'Anesthésie-Réanimation Neurochirurgicale, 1, rue Cabanis, 75674 Paris Cedex 14, France; INSERM U1266, FHU NeuroVasc, Institut de Psychiatrie et Neuroscience de Paris, Paris, France.
| | - C Legouy
- G.H.U Paris Psychiatry & Neurosciences, department of Neurocritical care, Service d'Anesthésie-Réanimation Neurochirurgicale, 1, rue Cabanis, 75674 Paris Cedex 14, France
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25
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Eltrass AS, Ghanem NH. A new automated multi-stage system of non-local means and multi-kernel adaptive filtering techniques for EEG noise and artifacts suppression. J Neural Eng 2021; 18. [PMID: 33545699 DOI: 10.1088/1741-2552/abe397] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Accepted: 02/05/2021] [Indexed: 11/11/2022]
Abstract
Context.Electroencephalography (EEG) signals are contaminated with diverse types of noises and artifacts, which greatly distort EEG recording and increase the difficulty in obtaining accurate diagnosis.Objective.This paper investigates, for the first time, multi-kernel normalized least mean square with coherence-based sparsification (MKNLMS-CS) algorithm for suppressing different artifact components, and the 1D patch-based non-local means (NLM) algorithm for eliminating white and colored noises.Approach.A novel multi-stage system based on combining the NLM algorithm with the MKNLMS-CS algorithm is proposed for eliminating different noise and artifact sources by targeting each noise or artifact component in a single stage.Main Results.The proposed approach is applied to clinical real EEG data, and the results reveal the superior performance of the proposed system in removing white and colored noises, suppressing different artifact components, preserving the important and tiny features of the original EEG signal, and keeping the morphology of EEG frequency components.Significance.The proposed multi-stage design succeeds not only to suppress different artifact components and noise sources under low and high noise conditions, but also to achieve accurate sleep spindle detection from the filtered high-quality EEG signals. This demonstrates the usefulness of the proposed approach for obtaining high-resolution EEG signal from noisy and contaminated EEG recordings.
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Affiliation(s)
- Ahmed S Eltrass
- Electrical Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, Egypt
| | - Noha H Ghanem
- Electrical Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, Egypt
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Du L, Zheng K, Feng L, Cao Y, Niu Z, Song Z, Liu Z, Liu X, Xiang X, Zhou Q, Xiong H, Chen F, Zhang G, Ma Q. The first national survey on practices of neurological prognostication after cardiac arrest in China, still a lot to do. Int J Clin Pract 2021; 75:e13759. [PMID: 33098255 DOI: 10.1111/ijcp.13759] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 10/04/2020] [Indexed: 02/05/2023] Open
Abstract
AIMS To investigate current awareness and practices of neurological prognostication in comatose cardiac arrest (CA) patients. METHODS An anonymous questionnaire was distributed to 1600 emergency physicians in 75 hospitals which were selected randomly from China between January and July 2018. RESULTS 92.1% respondents fulfilled the survey. The predictive value of brain stem reflex, motor response and myoclonus was confirmed by 63.5%, 44.6% and 31.7% respondents, respectively. Only 30.7% knew that GWR value < 1.1 indicated poor prognosis and only 8.1% know the most commonly used SSEP N20. Status epilepticus, burst suppression and suppression were considered to predict poor outcome by only 35.0%, 27.4% and 20.9% respondents, respectively. Only 46.7% knew NSE and only 24.7% knew S-100. Only a few respondents knew that neurological prognostication should be performed later than 72 hours from CA either in TTM or non-TTM patients. In practice, the most commonly used method was clinical examination (85.4%). Only 67.9% had used brain CT for prognosis and 18.4% for MRI. NSE (39.6%) was a little more widely used than S-100β (18.0%). However, SSEP (4.4%) and EEG (11.4%) were occasionally performed. CONCLUSIONS Neurological prognostication in CA survivors had not been well understood and performed by emergency physicians in China. They were more likely to use clinical examination rather than objective tools, especially SSEP and EEG, which also illustrated that multimodal approach was not well performed in practice.
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Affiliation(s)
- Lanfang Du
- Emergency Department, The Peking University Third Hospital, Beijing, China
| | - Kang Zheng
- Emergency Department, The Peking University Third Hospital, Beijing, China
| | - Lu Feng
- Emergency Department, The Peking University Third Hospital, Beijing, China
| | - Yu Cao
- Emergency Department, West China Hospital, Chengdu City, China
| | - Zhendong Niu
- Emergency Department, West China Hospital, Chengdu City, China
| | - Zhenju Song
- Emergency Department, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhi Liu
- Emergency Department, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xiaowei Liu
- Emergency Department, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xudong Xiang
- Emergency Department, Second Xiangya Hospital, Central South University, Changsha, China
| | - Qidi Zhou
- Emergency Department, Peking University Shenzhen Hospital, Shenzhen City, China
| | - Hui Xiong
- Emergency Department, Peking University First Hospital, Beijing, China
| | - Fengying Chen
- Emergency Department, The Affiliated Hospital of Innor Mongolia Medical University, Huherhaote City, China
| | - Guoqiang Zhang
- Emergency Department, China-Japan Friendship Hospital, Beijing, China
| | - Qingbian Ma
- Emergency Department, The Peking University Third Hospital, Beijing, China
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Carrasco-Gómez M, Keijzer HM, Ruijter BJ, Bruña R, Tjepkema-Cloostermans MC, Hofmeijer J, van Putten MJAM. EEG functional connectivity contributes to outcome prediction of postanoxic coma. Clin Neurophysiol 2021; 132:1312-1320. [PMID: 33867260 DOI: 10.1016/j.clinph.2021.02.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 01/19/2021] [Accepted: 02/09/2021] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest. METHODS Prospective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as "good" (Cerebral Performance Category [CPC] 1-2) or "poor" (CPC 3-5). RESULTS We included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34-56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0-54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50-77%) at 100% specificity. CONCLUSION Functional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma. SIGNIFICANCE Functional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.
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Affiliation(s)
- Martín Carrasco-Gómez
- Laboratory of Cognitive and Computational Neuroscience (LNCyC), Centre for Biomedical Technology, Universidad Politécnica de Madrid, Spain; Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.
| | - Hanneke M Keijzer
- Department of Neurology, Rijnstate Hospital, Arnhem, the Netherlands; Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Barry J Ruijter
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, the Netherlands
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (LNCyC), Centre for Biomedical Technology, Universidad Politécnica de Madrid, Spain; Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Marleen C Tjepkema-Cloostermans
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, the Netherlands; Neurocentrum, Medisch SpectrumTwente, Enschede, the Netherlands
| | - Jeannette Hofmeijer
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, the Netherlands; Department of Neurology, Rijnstate Hospital, Arnhem, the Netherlands
| | - Michel J A M van Putten
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, the Netherlands; Neurocentrum, Medisch SpectrumTwente, Enschede, the Netherlands
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Ata F, Bint I Bilal A, Tajelsir Abdalla Osman O, Arif MA, Elhassan M, hamid T, Al Suwaidi J, Choudry H, Abushahba G. Reversible hypoxic‐ischemic encephalopathy post prolonged out‐of‐hospital cardiac arrest: A case series. Clin Case Rep 2021; 9:1529-1533. [DOI: https:/doi.org/10.1002/ccr3.3820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 01/05/2021] [Indexed: 08/30/2023] Open
Affiliation(s)
- Fateen Ata
- Department of Internal Medicine Hamad General HospitalHamad Medical Corporation Doha Qatar
| | - Ammara Bint I Bilal
- Department of Radiology Hamad General HospitalHamad Medical Corporation Doha Qatar
| | | | - Muhammad Awais Arif
- Department of Cardiology Heart HospitalHamad Medical Corporation. Doha Qatar
| | - Mawahib Elhassan
- Department of Cardiology Heart HospitalHamad Medical Corporation. Doha Qatar
| | - Tahir hamid
- Department of Cardiology Heart HospitalHamad Medical Corporation. Doha Qatar
| | - Jassim Al Suwaidi
- Department of Cardiology Heart HospitalHamad Medical Corporation. Doha Qatar
| | - Hassan Choudry
- Pediatric Gastroenterology Johns Hopkins Medical Institute Baltimore MD USA
| | - Galal Abushahba
- Department of Cardiology Royal Lancaster Infirmary HospitalMorecambe University Lancaster UK
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29
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Ata F, Bint I Bilal A, Tajelsir Abdalla Osman O, Arif MA, Elhassan M, hamid T, Al Suwaidi J, Choudry H, Abushahba G. Reversible hypoxic-ischemic encephalopathy post prolonged out-of-hospital cardiac arrest: A case series. Clin Case Rep 2021; 9:1529-1533. [PMID: 33768882 PMCID: PMC7981696 DOI: 10.1002/ccr3.3820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 12/29/2020] [Accepted: 01/05/2021] [Indexed: 11/13/2022] Open
Abstract
This article highlights the possibility of positive outcomes associated with prolonged CPR and anoxic brain injury contesting the idea that such patients will invariably end up in a persistent vegetative state.
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Affiliation(s)
- Fateen Ata
- Department of Internal MedicineHamad General HospitalHamad Medical CorporationDohaQatar
| | - Ammara Bint I Bilal
- Department of RadiologyHamad General HospitalHamad Medical CorporationDohaQatar
| | | | | | - Mawahib Elhassan
- Department of CardiologyHeart HospitalHamad Medical Corporation.DohaQatar
| | - Tahir hamid
- Department of CardiologyHeart HospitalHamad Medical Corporation.DohaQatar
| | - Jassim Al Suwaidi
- Department of CardiologyHeart HospitalHamad Medical Corporation.DohaQatar
| | - Hassan Choudry
- Pediatric GastroenterologyJohns Hopkins Medical InstituteBaltimoreMDUSA
| | - Galal Abushahba
- Department of CardiologyRoyal Lancaster Infirmary HospitalMorecambe UniversityLancasterUK
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Kommentar zur Intensiv-EEG-Klassifikation der Amerikanischen Gesellschaft
für Klinische Neurophysiologie. KLIN NEUROPHYSIOL 2020. [DOI: 10.1055/a-1250-6275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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He R, Fan J, Wang H, Zhong Y, Ma J. Differentiating Responders and Non-responders to rTMS Treatment for Disorder of Consciousness Using EEG After-Effects. Front Neurol 2020; 11:583268. [PMID: 33329325 PMCID: PMC7714935 DOI: 10.3389/fneur.2020.583268] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/26/2020] [Indexed: 12/17/2022] Open
Abstract
Background: It is controversial whether repetitive transcranial magnetic stimulation (rTMS) has potential benefits in improving the awareness of patients with disorder of consciousness (DOC). We hypothesized that rTMS could improve consciousness only in DOC patients who have measurable brain responses to rTMS. Objective: In this study, we aimed to investigate the EEG after-effects induced by rTMS in DOC patients and attempted to propose a prediction algorithm to discriminate between DOC patients who would respond to rTMS treatment from those who would not. Methods: Twenty-five DOC patients were enrolled in this study. Over 4 weeks, each patient received 20 sessions of 20 Hz rTMS that was applied over the left dorsolateral prefrontal cortex (DLPFC). For each patient, resting-state EEG was recorded before and immediately after one session of rTMS to assess the neurophysiologic modification induced by rTMS. The coma recovery scale revised (CRS-R) was used to define responders with improved consciousness. Results: Of the 25 DOC patients, 10 patients regained improved consciousness and were classified as responders. The responders were characterized by more preserved alpha power and a significant reduction of delta power induced by rTMS. The analysis of receiver operating characteristic (ROC) curves showed that the algorithm calculated from the relative alpha power and the relative delta power had a high accuracy in identifying DOC patients who were responders. Conclusions: DOC patients who had more preserved alpha power and a significant reduction in the delta band that was induced by rTMS are likely to regain improved consciousness, which provides a tool to identify DOC patients who may benefit in terms of therapeutic consciousness.
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Affiliation(s)
- Renhong He
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Department of Rehabilitation Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jianzhong Fan
- Department of Rehabilitation Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Huijuan Wang
- Department of Rehabilitation Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuhua Zhong
- Department of Rehabilitation Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jianhua Ma
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
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Carton-Leclercq A, Lecas S, Chavez M, Charpier S, Mahon S. Neuronal excitability and sensory responsiveness in the thalamo-cortical network in a novel rat model of isoelectric brain state. J Physiol 2020; 599:609-629. [PMID: 33095909 DOI: 10.1113/jp280266] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 10/21/2020] [Indexed: 01/04/2023] Open
Abstract
KEY POINTS The neuronal and network properties that persist during an isoelectric coma remain largely unknown. We developed a new in vivo rat model to assess cell excitability and sensory responsiveness in the thalamo-cortical pathway during an isoflurane-induced isoelectric brain state. The isoelectric electrocorticogram reflected a complete interruption of spontaneous synaptic and firing activities in cortical and thalamic neurons. Cell excitability and sensory responses in the thalamo-cortical network persisted at a reduced level in the isoelectric condition and returned to control values after resumption of background brain activity. These findings could lead to a reassessment of the functional status of the drug-induced isoelectric state: a latent state in which individual neurons and networks retain to some extent the ability of being activated by external inputs. ABSTRACT The neuronal and network properties that persist in an isoelectric brain completely deprived of spontaneous electrical activity remain largely unexplored. Here, we developed a new in vivo rat model to examine cell excitability and sensory responsiveness in somatosensory thalamo-cortical networks during the interruption of endogenous brain activity induced by high doses of isoflurane. Electrocorticograms (ECoGs) from the barrel cortex were captured simultaneously with either intracellular recordings of subjacent cortical pyramidal neurons or extracellular records of the related thalamo-cortical neurons. Isoelectric ECoG periods reflected the disappearance of spontaneous synaptic and firing activities in cortical and thalamic neurons. This was associated with a sustained membrane hyperpolarization and a reduced intrinsic excitability in deep-layer cortical neurons, without significant changes in their membrane input resistance. Concomitantly, we found that whisker-evoked potentials in the ECoG and synaptic responses in cortical neurons were attenuated in amplitude and increased in latency. Impaired responsiveness in the barrel cortex paralleled with a lowering of the sensory-induced firing in thalamic cells. The return of endogenous brain electrical activities, after reinstatement of a control isoflurane concentration, led to the recovery of cortical neurons excitability and sensory responsiveness. These findings demonstrate the persistence of a certain level of cell excitability and sensory integration in the isoelectric state and the full recovery of cortico-thalamic functions after restoration of internal cerebral activities.
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Affiliation(s)
- Antoine Carton-Leclercq
- Institut du Cerveau, ICM, INSERM UMRS 1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - Sarah Lecas
- Institut du Cerveau, ICM, INSERM UMRS 1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France.,Sorbonne University, UPMC Université Paris, Paris, France
| | - Mario Chavez
- Institut du Cerveau, ICM, INSERM UMRS 1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - Stéphane Charpier
- Institut du Cerveau, ICM, INSERM UMRS 1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France.,Sorbonne University, UPMC Université Paris, Paris, France
| | - Séverine Mahon
- Institut du Cerveau, ICM, INSERM UMRS 1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France
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Cassina T, Clivio S, Putzu A, Villa M, Moccetti T, Fortuna D, Casso G. Neurological outcome and modifiable events after out-of-hospital cardiac arrest in patients managed in a tertiary cardiac centre: A ten years register. Med Intensiva 2020; 44:409-419. [DOI: 10.1016/j.medin.2019.05.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 05/08/2019] [Accepted: 05/18/2019] [Indexed: 01/30/2023]
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Meyer M, Fuest S, Krain D, Juenemann M, Braun T, Thal SC, Schramm P. Evaluation of a new wireless technique for continuous electroencephalography monitoring in neurological intensive care patients. J Clin Monit Comput 2020; 35:765-770. [PMID: 32488677 DOI: 10.1007/s10877-020-00533-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/19/2020] [Indexed: 10/24/2022]
Abstract
A novel wireless eight-channel electroencephalography (EEG) headset specially developed for ICUs was tested in regard of comparability with standard 10/20 EEG systems. The continuous EEG (cEEG) derivations via CerebAir EEG headset (Nihon Kohden Europe, Rosbach, Germany) and internationally standardized 10/20 reference EEGs as the diagnostic standard were performed in a mixed collective on a neurointensive care unit (neuro-ICU). The derivations were verified for comparability in detection of EEG background activity, epileptiform discharges, and seizure patterns. Fifty-two patients with vigilance reduction following serious neurological or metabolic diseases were included, and both methods were applied and further analyzed in 47. EEG background activity matched in 24 of 45 patients (53%; p = 0.126), epileptiform discharges matched in 32 (68%) patients (p = 0.162), and seizure activity matched in 98%. Overall, in 89% of the patients, cEEG detected the same or additional ICU-relevant EEG patterns. The tested wireless cEEG headset is a useful monitoring tool in patients with consciousness disorders. The present study indicates that long-term measurements with the wireless eight-channel cEEG lead to a higher seizure and epileptiform discharge detection compared to intermittent 10/20 EEG derivations in the ICU setting.
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Affiliation(s)
- Marco Meyer
- Department of Geriatrics, Jung-Stilling Hospital Siegen, Wichernstrasse 40, 57074, Siegen, Germany.
| | - Sven Fuest
- Department of Neurology, Universitaetsklinikum Giessen & Marburg Standort Marburg, Baldingerstrasse, 35033, Marburg, Germany
| | - Dominique Krain
- Department of Neurology, Universitaetsklinikum Giessen & Marburg Standort Giessen, Klinikstrasse 33, 35385, Giessen, Germany
| | - Martin Juenemann
- Department of Neurology, Universitaetsklinikum Giessen & Marburg Standort Giessen, Klinikstrasse 33, 35385, Giessen, Germany
| | - Tobias Braun
- Department of Neurology, Universitaetsklinikum Giessen & Marburg Standort Giessen, Klinikstrasse 33, 35385, Giessen, Germany
| | - Serge C Thal
- Department of Anesthesiology, Helios Universitaetsklinikum Wuppertal University Witten/Herdecke, Heusnerstraße 40, 42283, Wuppertal, Germany
| | - Patrick Schramm
- Department of Anesthesiology, Johannes Gutenberg Universitaet, Universitaetsmedizin Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
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Elmer J, Coppler PJ, Solanki P, Westover MB, Struck AF, Baldwin ME, Kurz MC, Callaway CW. Sensitivity of Continuous Electroencephalography to Detect Ictal Activity After Cardiac Arrest. JAMA Netw Open 2020; 3:e203751. [PMID: 32343353 PMCID: PMC7189220 DOI: 10.1001/jamanetworkopen.2020.3751] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
IMPORTANCE Epileptiform electroencephalographic (EEG) patterns are common after resuscitation from cardiac arrest, are associated with patient outcome, and may require treatment. It is unknown whether continuous EEG monitoring is needed to detect these patterns or if brief intermittent monitoring is sufficient. If continuous monitoring is required, the necessary duration of observation is unknown. OBJECTIVE To quantify the time-dependent sensitivity of continuous EEG for epileptiform event detection, and to compare continuous EEG to several alternative EEG-monitoring strategies for post-cardiac arrest outcome prediction. DESIGN, SETTING, AND PARTICIPANTS This observational cohort study was conducted in 2 academic medical centers between September 2010 and January 2018. Participants included 759 adults who were comatose after being resuscitated from cardiac arrest and who underwent 24 hours or more of EEG monitoring. MAIN OUTCOMES AND MEASURES Epileptiform EEG patterns associated with neurological outcome at hospital discharge, such as seizures likely to cause secondary injury. RESULTS Overall, 759 patients were included in the analysis; 281 (37.0%) were female, and the mean (SD) age was 58 (17) years. Epileptiform EEG activity was observed in 414 participants (54.5%), of whom only 26 (3.4%) developed potentially treatable seizures. Brief intermittent EEG had an estimated 66% (95% CI, 62%-69%) to 68% (95% CI, 66%-70%) sensitivity for detection of prognostic epileptiform events. Depending on initial continuity of the EEG background, 0 to 51 hours of monitoring were needed to achieve 95% sensitivity for the detection of prognostic epileptiform events. Brief intermittent EEG had a sensitivity of 7% (95% CI, 4%-12%) to 8% (95% CI, 4%-12%) for the detection of potentially treatable seizures, and 0 to 53 hours of continuous monitoring were needed to achieve 95% sensitivity for the detection of potentially treatable seizures. Brief intermittent EEG results yielded similar information compared with continuous EEG results when added to multivariable models predicting neurological outcome. CONCLUSIONS AND RELEVANCE Compared with continuous EEG monitoring, brief intermittent monitoring was insensitive for detection of epileptiform events. Monitoring EEG results significantly improved multimodality prediction of neurological outcome, but continuous monitoring appeared to add little additional information compared with brief intermittent monitoring.
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Affiliation(s)
- Jonathan Elmer
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Patrick J. Coppler
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Pawan Solanki
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | | | - Maria E. Baldwin
- Department of Neurology, Pittsburgh VA Medical Center, Pittsburgh, Pennsylvania
| | - Michael C. Kurz
- Department of Emergency Medicine, University of Alabama at Birmingham School of Medicine
| | - Clifton W. Callaway
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
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Barbella G, Lee JW, Alvarez V, Novy J, Oddo M, Beers L, Rossetti AO. Prediction of regaining consciousness despite an early epileptiform EEG after cardiac arrest. Neurology 2020; 94:e1675-e1683. [DOI: 10.1212/wnl.0000000000009283] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 11/16/2019] [Indexed: 11/15/2022] Open
Abstract
ObjectiveAfter cardiac arrest (CA), epileptiform EEG, occurring in about 1/3 of patients, often but not invariably heralds poor prognosis. We tested the hypothesis that a combination of specific EEG features identifies patients who may regain consciousness despite early epileptiform patterns.MethodsWe retrospectively analyzed a registry of comatose patients post-CA (2 Swiss centers), including those with epileptiform EEG. Background and epileptiform features in EEGs 12–36 hours or 36–72 hours from CA were scored according to the American Clinical Neurophysiology Society nomenclature. Best Cerebral Performance Category (CPC) score within 3 months (CPC 1–3 vs 4–5) was the primary outcome. Significant EEG variables were combined in a score assessed with receiver operating characteristic curves, and independently validated in a US cohort; its correlation with serum neuron-specific enolase (NSE) was also tested.ResultsOf 488 patients, 107 (21.9%) had epileptiform EEG <72 hours; 18 (17%) reached CPC 1–3. EEG 12–36 hours background continuity ≥50%, absence of epileptiform abnormalities (p< 0.00001 each), 12–36 and 36–72 hours reactivity (p< 0.0001 each), 36–72 hours normal background amplitude (p= 0.0004), and stimulus-induced discharges (p= 0.0001) correlated with favorable outcome. The combined 6-point score cutoff ≥2 was 100% sensitive (95% confidence interval [CI], 78%–100%) and 70% specific (95% CI, 59%–80%) for CPC 1–3 (area under the curve [AUC], 0.98; 95% CI, 0.94–1.00). Increasing score correlated with NSE (ρ = −0.46,p= 0.0001). In the validation cohort (41 patients), the score was 100% sensitive (95% CI, 60%–100%) and 88% specific (95% CI, 73%–97%) for CPC 1–3 (AUC, 0.96; 95% CI, 0.91–1.00).ConclusionPrognostic value of early epileptiform EEG after CA can be estimated combining timing, continuity, reactivity, and amplitude features in a score that correlates with neuronal damage.
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Jiang M, Su Y, Liu G, Huang H, Tian F. EEG pattern predicts awakening of comatose patients after cardiopulmonary resuscitation. Resuscitation 2019; 151:33-38. [PMID: 31785371 DOI: 10.1016/j.resuscitation.2019.11.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 10/14/2019] [Accepted: 11/01/2019] [Indexed: 10/25/2022]
Abstract
OBJECTIVE To explore the value of electroencephalogram (EEG) pattern in predicting awakening of comatose patients after cardiopulmonary resuscitation (CPR). METHODS A retrospective cohort study was conducted on comatose patients after CPR in the neuro-critical care unit of Xuanwu Hospital, Capital Medical University, from 2002 to 2018. The included patients received clinical evaluation, and the Glasgow coma scale (GCS) score was recorded. Bedside EEG monitoring was performed for visual grading and reactivity detection. The 3-month prognostic assessment was performed using the Glasgow outcome scale (GOS). The patients were dichotomized into the awakening group (GOS 3-5) and the unawakening group (GOS 1-2). RESULTS A total of 160 patients were included. There was no significant difference in the baseline data between the two groups except that the GCS score of the awakening group was higher (P = 0.000). Different EEG patterns were used to predict awakening from coma. As a result, the slow wave pattern showed the highest accuracy (73.1%, 95% CI: 0.66-0.79), and the sensitivity and specificity reached 61.3% (95% CI: 0.48-0.73) and 80.6% (95% CI: 0.71-0.88), respectively. Compared with EEG reactivity, the slow wave pattern was more sensitive in predicting awakening. It was also more specific than GCS in predicting awakening. The slow wave pattern within different time frame after coma was used to predict the prognosis of awakening, suggesting that the accuracy (100%, 95% CI: 0.75-1.00), sensitivity (100%, 95% CI: 0.46-1.00), and specificity (100%, 95% CI: 0.63-1.00) of predicting awakening within 8-14 days were the highest. CONCLUSIONS The slow wave pattern of EEG had a good predictive value for awakening in comatose patients after CPR, and the highest accuracy occurred within 8-14 days from coma.
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Affiliation(s)
- Mengdi Jiang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yingying Su
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
| | - Gang Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Huijin Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Fei Tian
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
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[Impact of a prognostic investigation protocol in post-resuscitation care set in intensive-care unit]. Presse Med 2019; 48:1373-1381. [PMID: 31757731 DOI: 10.1016/j.lpm.2019.09.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 09/28/2019] [Accepted: 09/30/2019] [Indexed: 11/22/2022] Open
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Inhaling Hydrogen Ameliorates Early Postresuscitation EEG Characteristics in an Asphyxial Cardiac Arrest Rat Model. BIOMED RESEARCH INTERNATIONAL 2019; 2019:6410159. [PMID: 31737671 PMCID: PMC6815975 DOI: 10.1155/2019/6410159] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 08/19/2019] [Indexed: 11/17/2022]
Abstract
Background Electroencephalography (EEG) is commonly used to assess the neurological prognosis of comatose patients after cardiac arrest (CA). However, the early prognostic accuracy of EEG may be affected by postresuscitation interventions. Recent animal studies found that hydrogen inhalation after CA greatly improved neurological outcomes by selectively neutralizing highly reactive oxidants, but the effect of hydrogen inhalation on EEG recovery and its prognostication value are still unclear. The present study investigated the effects of hydrogen inhalation on early postresuscitation EEG characteristics in an asphyxial CA rat model. Methods Cardiopulmonary resuscitation was initiated after 5 min of untreated CA in 40 adult female Sprague-Dawley rats. Animals were randomized for ventilation with 98% oxygen plus 2% hydrogen (H2) or 98% oxygen plus 2% nitrogen (Ctrl) under normothermia for 1 h. EEG characteristics were continuously recorded for 4 h, and the relationships between quantitative EEG characteristics and 96 h neurological outcomes were investigated. Results No differences in baseline and resuscitation data were observed between groups, but the survival rate was significantly higher in the H2 group than in the Ctrl group (90% vs. 40%, P < 0.01). Compared to the Ctrl group, the H2 group showed a shorter burst onset time (21.85 [20.00-23.38] vs. 25.70 [22.48-30.05], P < 0.01) and time to normal trace (169.83 [161.63-208.55] vs. 208.39 [186.29-248.80], P < 0.01). Additionally, the burst suppression ratio (0.66 ± 0.09 vs. 0.52 ± 0.17, P < 0.01) and weighted-permutation entropy (0.47 ± 0.16 vs. 0.34 ± 0.13, P < 0.01) were markedly higher in the H2 group. The areas under the receiver operating characteristic curves for the 4 EEG characteristics in predicting survival were 0.82, 0.84, 0.88, and 0.83, respectively. Conclusions In this asphyxial CA rat model, the improved postresuscitation EEG characteristics for animals treated with hydrogen are correlated with the better 96 h neurological outcome and predicted survival.
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Abstract
Background Currently, continuous electroencephalographic monitoring (cEEG) is the only available diagnostic tool for continuous monitoring of brain function in intensive care unit (ICU) patients. Yet, the exact relevance of routinely applied ICU cEEG remains unclear, and information on the implementation of cEEG, especially in Europe, is scarce. This study explores current practices of cEEG in adult Dutch ICU departments focusing on organizational and operational factors, development over time and factors perceived relevant for abstaining its use. Methods A national survey on cEEG in adults among the neurology and adult intensive care departments of all Dutch hospitals (n = 82) was performed. Results The overall institutional response rate was 78%. ICU cEEG is increasingly used in the Netherlands (in 37% of all hospitals in 2016 versus in 21% in 2008). Currently in 88% of university, 55% of teaching and 14% of general hospitals use ICU cEEG. Reasons for not performing cEEG are diverse, including perceived non-feasibility and lack of data on the effect of cEEG use on patient outcome. Mostly, ICU cEEG is used for non-convulsive seizures or status epilepticus and prognostication. However, cEEG is never or rarely used for monitoring cerebral ischemia and raised intracranial pressure in traumatic brain injury. Review and reporting practices differ considerably between hospitals. Nearly all hospitals perform non-continuous review of cEEG traces. Methods for moving toward continuous review of cEEG traces are available but infrequently used in practice. Conclusions cEEG is increasingly used in Dutch ICUs. However, cEEG practices vastly differ between hospitals. Future research should focus on uniform cEEG practices including unambiguous EEG interpretation to facilitate collaborative research on cEEG, aiming to provide improved standard patient care and robust data on the impact of cEEG use on patient outcome.
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Chen B, Chen G, Dai C, Wang P, Zhang L, Huang Y, Li Y. Comparison of Quantitative Characteristics of Early Post-resuscitation EEG Between Asphyxial and Ventricular Fibrillation Cardiac Arrest in Rats. Neurocrit Care 2019; 28:247-256. [PMID: 28484928 DOI: 10.1007/s12028-017-0401-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Quantitative electroencephalogram (EEG) analysis has shown promising results in studying brain injury and functional recovery after cardiac arrest (CA). However, whether the quantitative characteristics of EEG, as potential indicators of neurological prognosis, are influenced by CA causes is unknown. The purpose of this study was designed to compare the quantitative characteristics of early post-resuscitation EEG between asphyxial CA (ACA) and ventricular fibrillation CA (VFCA) in rats. METHODS Thirty-two Sprague-Dawley rats of both sexes were randomized into either ACA or VFCA group. Cardiopulmonary resuscitation was initiated after 5-min untreated CA. Characteristics of early post-resuscitation EEG were compared, and the relationships between quantitative EEG features and neurological outcomes were investigated. RESULTS Compared with VFCA, serum level of S100B, neurological deficit score and brain histopathologic damage score were dramatically higher in the ACA group. Quantitative measures of EEG, including onset time of EEG burst, time to normal trace, burst suppression ratio, and information quantity, were significantly lower for CA caused by asphyxia and correlated with the 96-h neurological outcome and survival. CONCLUSIONS Characteristics of earlier post-resuscitation EEG differed between cardiac and respiratory causes. Quantitative measures of EEG not only predicted neurological outcome and survival, but also have the potential to stratify CA with different causes.
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Affiliation(s)
- Bihua Chen
- School of Biomedical Engineering, Third Military Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China
| | - Gang Chen
- School of Biomedical Engineering, Third Military Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China
| | - Chenxi Dai
- School of Biomedical Engineering, Third Military Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China
| | - Pei Wang
- School of Biomedical Engineering, Third Military Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China
| | - Lei Zhang
- Emergency Department, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China
| | - Yuanyuan Huang
- Neurology Department, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China
| | - Yongqin Li
- School of Biomedical Engineering, Third Military Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China.
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42
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Lee JW. Good Outcome in Cardiac Arrest Patients in Refractory Status Epilepticus: A Result of Aggressive Treatment or EEG Reclassification. Epilepsy Curr 2019; 19:168-170. [PMID: 31035819 PMCID: PMC6610381 DOI: 10.1177/1535759719843323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
[Box: see text]
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43
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Honorato-Cia C, Martinez-Simon A. The anesthesiologist and the EEG: Current uses and future trends in the operating room. TRENDS IN ANAESTHESIA AND CRITICAL CARE 2019. [DOI: 10.1016/j.tacc.2018.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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44
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Abstract
BACKGROUND We previously validated simplified electroencephalogram (EEG) tracings obtained by a bispectral index (BIS) device against standard EEG. This retrospective study now investigated whether BIS EEG tracings can predict neurological outcome after cardiac arrest (CA). METHODS Bilateral BIS monitoring (BIS VISTA™, Aspect Medical Systems, Inc. Norwood, USA) was started following intensive care unit admission. Six, 12, 18, 24, 36 and 48 h after targeted temperature management (TTM) at 33 °C was started, BIS EEG tracings were extracted and reviewed by two neurophysiologists for the presence of slow diffuse rhythm, burst suppression, cerebral inactivity and epileptic activity (defined as continuous, monomorphic, > 2 Hz generalized sharp activity or continuous, monomorphic, < 2 Hz generalized blunt activity). At 180 days post-CA, neurological outcome was determined using cerebral performance category (CPC) classification (CPC1-2: good and CPC3-5: poor neurological outcome). RESULTS Sixty-three out-of-hospital cardiac arrest patients were enrolled for data analysis of whom 32 had a good and 31 a poor neurological outcome. Epileptic activity within 6-12 h predicted CPC3-5 with a positive predictive value (PPV) of 100%. Epileptic activity within time frames 18-24 and 36-48 h showed a PPV for CPC3-5 of 90 and 93%, respectively. Cerebral inactivity within 6-12 h predicted CPC3-5 with a PPV of 57%. In contrast, cerebral inactivity between 36 and 48 h predicted CPC3-5 with a PPV of 100%. The pattern with the worst predictive power at any time point was burst suppression with PPV of 44, 57 and 40% at 6-12 h, at 18-24 h and at 36-48 h, respectively. Slow diffuse rhythms at 6-12 h, at 18-24 h and at 36-48 h predicted CPC1-2 with PPV of 74, 76 and 80%, respectively. CONCLUSION Based on simplified BIS EEG, the presence of epileptic activity at any time and cerebral inactivity after the end of TTM may assist poor outcome prognostication in successfully resuscitated CA patients. A slow diffuse rhythm at any time after CA was indicative for a good neurological outcome.
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Benarous L, Gavaret M, Soda Diop M, Tobarias J, de Ghaisne de Bourmont S, Allez C, Bouzana F, Gainnier M, Trebuchon A. Sources of interrater variability and prognostic value of standardized EEG features in post-anoxic coma after resuscitated cardiac arrest. Clin Neurophysiol Pract 2019; 4:20-26. [PMID: 30847430 PMCID: PMC6389540 DOI: 10.1016/j.cnp.2018.12.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2017] [Revised: 12/03/2018] [Accepted: 12/05/2018] [Indexed: 12/02/2022] Open
Abstract
We identified a new approach to improve the prognostic value of EEG patterns. Interrater agreement was evaluated and reported for each different EEG pattern. Causes for discrepancy were elucidated to improve interrater concordance.
Objectives To assess interrater variability and prognostic value of simple EEG features based on the recent American Clinical Neurophysiology Society (ACNS) classification in post cardiac arrest comatose patients. Methods All patients admitted for a resuscitated cardiac arrest in a university hospital were prospectively included in the study. EEG interpretation was made by 3 independent neurophysiologists (2 senior and 1 junior) blind to the outcome. Kappa score and prognostic performances were estimated for each EEG pattern and discrepancies were analyzed. Results 122 cardiac arrest patients were admitted of whom 48 went through a full neurologic evaluation. Eighty-one percent had an unfavorable outcome. Burst suppression, paroxystic seizure activity, and non-reactive EEG were strongly associated with an unfavorable evolution. Kappa score between the senior neurophysiologists was excellent or substantial while it was only fair or slight between the junior and senior neurophysiologists. Reactivity, discontinuity and electrographic seizure were patterns particularly subject to discrepancy. Conclusions Bedside EEG is an excellent tool for predicting outcome of post-anoxic coma through simple EEG features. However, the interrater variability emphasizes the need to be well trained for the standardized methods of evaluating EEG parameters. Significance A second look at complex patterns seems mandatory. The development of automated tools could help to improve the reliability of EEG interpretation.
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Affiliation(s)
- L Benarous
- Service de Réanimation des Urgences et médicale, Hôpital de la Timone, Marseille, France
| | - M Gavaret
- Service de Neurophysiologie Clinique, Hôpital de la Timone, Marseille, France
| | - M Soda Diop
- Service de Neurophysiologie Clinique, Hôpital de la Timone, Marseille, France
| | - J Tobarias
- Service de Réanimation des Urgences et médicale, Hôpital de la Timone, Marseille, France
| | | | - C Allez
- Service de Réanimation des Urgences et médicale, Hôpital de la Timone, Marseille, France
| | - F Bouzana
- Service de Réanimation des Urgences et médicale, Hôpital de la Timone, Marseille, France
| | - M Gainnier
- Service de Réanimation des Urgences et médicale, Hôpital de la Timone, Marseille, France
| | - A Trebuchon
- Service de Neurophysiologie Clinique, Hôpital de la Timone, Marseille, France
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Clinical neurophysiology of altered states of consciousness: Encephalopathy and coma. HANDBOOK OF CLINICAL NEUROLOGY 2019; 161:73-88. [PMID: 31307621 DOI: 10.1016/b978-0-444-64142-7.00041-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The neurophysiologist will commonly encounter patients with encephalopathy/delirium (altered consciousness with impaired cognition, usually with sleep-wake cycle alteration and lethargy) or coma (an eyes-closed state of unresponsiveness) in the hospital setting. Assessing the background frequency of the EEG, as well as the presence or absence of other features (reactivity, periodic discharges such as triphasic waves), can provide insight into the patient's underlying condition and in some cases may provide prognostic information. The literature of postanoxic arrest EEG patterns continues to expand. Other neurophysiologic tests, such as somatosensory evoked potentials, auditory mismatch negativity, and even EMG, may also play a role in assessing brain function; distinguishing among a locked-in state, minimally conscious state, persistent vegetative state, and waking/unresponsive states; and assessing the potential for recovery after brain injury.
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Walter U, Fernández-Torre JL, Kirschstein T, Laureys S. When is “brainstem death” brain death? The case for ancillary testing in primary infratentorial brain lesion. Clin Neurophysiol 2018; 129:2451-2465. [DOI: 10.1016/j.clinph.2018.08.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 06/20/2018] [Accepted: 08/25/2018] [Indexed: 12/19/2022]
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EEG Characteristics in Cooled and Rewarmed Periods in Post-cardiac Arrest Therapeutic Hypothermia Patients. J Clin Neurophysiol 2018. [PMID: 28644823 DOI: 10.1097/wnp.0000000000000375] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
PURPOSE Continuous video EEG is a tool to assess brain function in injuries, including cardiac arrest (CA). In post-CA therapeutic hypothermia (TH) studies, some EEG features are linked to poor prognosis, but the evolvement of EEG characteristics during two temperature phases and its significance is unclear. We systematically analyzed EEG characteristics in cooled and rewarmed phases of post-CA therapeutic hypothermia patients and investigated their correlation to patient outcome. METHODS This is a retrospective study of EEG analyses, from a single academic center, of 20 patients who underwent CA and therapeutic hypothermia. For each patient, three 30-minute EEG segments in cooled and rewarmed phases were analyzed for continuity, frequency, interictal epileptiform discharges, and seizures. Mortality at the time of discharge was used as outcome. RESULTS Rewarming was associated with the emergence of interictal epileptiform discharges, 2.6 times as likely compared with the cooled period (P = 0.03), and was not affected by systemic factors. Continuity, frequency, and discrete seizures were unaffected by temperature and did not show variance within each temperature phase. There was a trend toward the emergence of interictal epileptiform discharges upon rewarming and mortality, but it was not statistically significant. CONCLUSIONS Increased interictal epileptiform discharges with rewarming in post-CA therapeutic hypothermia patients may suggest poor prognosis, but a larger scale prospective study is needed.
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Song M, Yang Y, He J, Yang Z, Yu S, Xie Q, Xia X, Dang Y, Zhang Q, Wu X, Cui Y, Hou B, Yu R, Xu R, Jiang T. Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics. eLife 2018; 7:36173. [PMID: 30106378 PMCID: PMC6145856 DOI: 10.7554/elife.36173] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Accepted: 08/03/2018] [Indexed: 01/04/2023] Open
Abstract
Disorders of consciousness are a heterogeneous mixture of different diseases or injuries. Although some indicators and models have been proposed for prognostication, any single method when used alone carries a high risk of false prediction. This study aimed to develop a multidomain prognostic model that combines resting state functional MRI with three clinical characteristics to predict one year-outcomes at the single-subject level. The model discriminated between patients who would later recover consciousness and those who would not with an accuracy of around 88% on three datasets from two medical centers. It was also able to identify the prognostic importance of different predictors, including brain functions and clinical characteristics. To our knowledge, this is the first reported implementation of a multidomain prognostic model that is based on resting state functional MRI and clinical characteristics in chronic disorders of consciousness, which we suggest is accurate, robust, and interpretable. Severe brain injury can lead to disorders of consciousness (DOC), such as a coma. Some patients regain consciousness after injury, while others do not. Those who do not recover are unable to communicate or move in purposeful ways, and need long-term care. It can be difficult for physicians to predict which patients will mend. This is mainly based on their observations of the patient’s behavior over time. But such perceptions are subjective and vulnerable to errors. More accurate and objective methods are needed. Several studies suggest that the cause of the injury, the age of the person at the time of injury, and how long the person has had a DOC may predict recovery. Recent studies have shown that using a brain-imaging tool called resting state functional magnetic resonance imaging (fMRI) to measure communication between different parts of the brain may help to calculate the likelihood of recovery. Now, Song, Yang et al. show that combining resting state fMRI with three pieces of clinical information may help to better predict who will improve. Song et al. created a computer model that forecasts recovery from DOC based on fMRI results, the cause of the person’s injury, their age at the time of injury, and how long they have had impaired consciousness. The model could tell which patients would regain consciousness 88% of the time for 112 patients from two medical centers. It also identified several patients who got better despite initial predictions from doctors that they would not. The experiments show that combining multiple types of information can better predict which patients with DOC will convalesce. Larger studies are needed to confirm that the computer model is reliable. If they do, the model may one day help physicians and families to better plan and manage patients’ care.
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Affiliation(s)
- Ming Song
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Yi Yang
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Jianghong He
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Zhengyi Yang
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Shan Yu
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Qiuyou Xie
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China
| | - Xiaoyu Xia
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Yuanyuan Dang
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Qiang Zhang
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Xinhuai Wu
- Department of Radiology, PLA Army General Hospital, Beijing, China
| | - Yue Cui
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Bing Hou
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Ronghao Yu
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China
| | - Ruxiang Xu
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Tianzi Jiang
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China.,Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Queensland Brain Institute, University of Queensland, Brisbane, Australia
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Abstract
With the development of modern international medicine, the subject of disorders of consciousness (DOCs) has begun to be raised in mainland China. Much progress has been made to date in several specialties related to the management of chronic DOC patients in China. In this article, we briefly review the present status of DOC studies in China, specifically concerning diagnosis, prognosis, therapy, and rehabilitation. The development of DOC-related scientific organizations and activities in China are introduced. Some weaknesses that need improvement are also noted. The current program provides a good foundation for future development.
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Affiliation(s)
- Jizong Zhao
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050, China.
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