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Shivdat S, Zhan T, De Palma A, Zheng WL, Krishnamurthy P, Paneerselvam E, Snider S, Bevers M, O'Reilly UM, Lee JW, Westover MB, Amorim E. Early Burst Suppression Similarity Association with Structural Brain Injury Severity on MRI After Cardiac Arrest. Neurocrit Care 2024:10.1007/s12028-024-02047-6. [PMID: 39043984 DOI: 10.1007/s12028-024-02047-6] [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: 01/30/2024] [Accepted: 06/13/2024] [Indexed: 07/25/2024]
Abstract
BACKGROUND Identical bursts on electroencephalography (EEG) are considered a specific predictor of poor outcomes in cardiac arrest, but its relationship with structural brain injury severity on magnetic resonance imaging (MRI) is not known. METHODS This was a retrospective analysis of clinical, EEG, and MRI data from adult comatose patients after cardiac arrest. Burst similarity in first 72 h from the time of return of spontaneous circulation were calculated using dynamic time-warping (DTW) for bursts of equal (i.e., 500 ms) and varying (i.e., 100-500 ms) lengths and cross-correlation for bursts of equal lengths. Structural brain injury severity was measured using whole brain mean apparent diffusion coefficient (ADC) on MRI. Pearson's correlation coefficients were calculated between mean burst similarity across consecutive 12-24-h time blocks and mean whole brain ADC values. Good outcome was defined as Cerebral Performance Category of 1-2 (i.e., independence for activities of daily living) at the time of hospital discharge. RESULTS Of 113 patients with cardiac arrest, 45 patients had burst suppression (mean cardiac arrest to MRI time 4.3 days). Three study participants with burst suppression had a good outcome. Burst similarity calculated using DTW with bursts of varying lengths was correlated with mean ADC value in the first 36 h after cardiac arrest: Pearson's r: 0-12 h: - 0.69 (p = 0.039), 12-24 h: - 0.54 (p = 0.002), 24-36 h: - 0.41 (p = 0.049). Burst similarity measured with bursts of equal lengths was not associated with mean ADC value with cross-correlation or DTW, except for DTW at 60-72 h (- 0.96, p = 0.04). CONCLUSIONS Burst similarity on EEG after cardiac arrest may be associated with acute brain injury severity on MRI. This association was time dependent when measured using DTW.
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Affiliation(s)
- Shawn Shivdat
- Harvard College, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Tiange Zhan
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alessandro De Palma
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Computing, Imperial College London, London, UK
| | - Wei-Long Zheng
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
| | | | - Ezhil Paneerselvam
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Samuel Snider
- Division of Neurocritical Care, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Matthew Bevers
- Division of Neurocritical Care, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Una-May O'Reilly
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jong Woo Lee
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Division of Epilepsy, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - M Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Edilberto Amorim
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, Zuckerberg San Francisco General Hospital, 1001 Potrero Ave, Building 1, Suite 312, San Francisco, CA, 94110, USA.
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Murphy TW, Cohen SA, Hwang CW, Avery KL, Balakrishnan MP, Balu R, Chowdhury MAB, Crabb DB, Elmelige Y, Maciel CB, Gul SS, Han F, Becker TK. Cardiac arrest: An interdisciplinary scoping review of clinical literature from 2020. J Am Coll Emerg Physicians Open 2022; 3:e12773. [PMID: 35845142 PMCID: PMC9282171 DOI: 10.1002/emp2.12773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 05/15/2022] [Accepted: 06/02/2022] [Indexed: 11/08/2022] Open
Abstract
Objectives The Interdisciplinary Cardiac Arrest Research Review (ICARE) group was formed in 2018 to conduct an annual search of peer-reviewed literature relevant to cardiac arrest. Now in its third year, the goals of the review are to highlight annual updates in the interdisciplinary world of clinical cardiac arrest research with a focus on clinically relevant and impactful clinical and population-level studies from 2020. Methods A search of PubMed using keywords related to clinical research in cardiac arrest was conducted. Titles and abstracts were screened for relevance and sorted into 7 categories: Epidemiology & Public Health Initiatives; Prehospital Resuscitation, Technology & Care; In-Hospital Resuscitation & Post-Arrest Care; Prognostication & Outcomes; Pediatrics; Interdisciplinary Guidelines & Reviews; and a new section dedicated to the coronavirus disease 2019 (COVID-19) pandemic. Screened manuscripts underwent standardized scoring of methodological quality and impact on the respective fields by reviewer teams lead by a subject matter expert editor. Articles scoring higher than 99 percentiles by category were selected for full critique. Systematic differences between editors' and reviewers' scores were assessed using Wilcoxon signed-rank test. Results A total of 3594 articles were identified on initial search; of these, 1026 were scored after screening for relevance and deduplication, and 51 underwent full critique. The leading category was Prehospital Resuscitation, Technology & Care representing 35% (18/51) of fully reviewed articles. Four COVID-19 related articles were included for formal review that was attributed to a relative lack of high-quality data concerning cardiac arrest and COVID-19 specifically by the end of the 2020 calendar year. No significant differences between editor and reviewer scoring were found among review articles (P = 0.697). Among original research articles, section editors scored a median 1 point (interquartile range, 0-3; P < 0.01) less than reviewers. Conclusions Several clinically relevant studies have added to the evidence base for the management of cardiac arrest patients including methods for prognostication of neurologic outcome following arrest, airway management strategy, timing of coronary intervention, and methods to improve expeditious performance of key components of resuscitation such as chest compressions in adults and children.
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Affiliation(s)
- Travis W. Murphy
- Division of Critical Care MedicineDepartment of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
- Cardiothoracic Critical CareMiami Transplant InstituteUniversity of MiamiMiamiFloridaUSA
- Department of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Scott A. Cohen
- Department of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Charles W. Hwang
- Department of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - K. Leslie Avery
- Division of Pediatric Critical CareDepartment of PediatricsUniversity of FloridaGainesvilleFloridaUSA
| | | | - Ramani Balu
- Division of Neurocritical CareDepartment of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - David B. Crabb
- Department of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Yasmeen Elmelige
- Department of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Carolina B. Maciel
- Division of Neurocritical CareDepartment of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of NeurologyYale UniversityNew HavenConnecticutUSA
- Division of Neurocritical CareDepartment of NeurologyUniversity of FloridaGainesvilleFloridaUSA
| | - Sarah S. Gul
- Department of SurgeryYale UniversityNew HavenConnecticutUSA
| | - Francis Han
- Department of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
- Lake Erie College of Osteopathic MedicineBradentonFloridaUSA
| | - Torben K. Becker
- Division of Critical Care MedicineDepartment of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
- Department of Emergency MedicineUniversity of FloridaGainesvilleFloridaUSA
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Bronder J, Cho SM, Geocadin RG, Ritzl EK. Revisiting EEG as part of the multidisciplinary approach to post-cardiac arrest care and prognostication: A review. Resusc Plus 2022; 9:100189. [PMID: 34988537 PMCID: PMC8693464 DOI: 10.1016/j.resplu.2021.100189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/24/2021] [Accepted: 11/26/2021] [Indexed: 11/01/2022] Open
Abstract
Since the 1960s, EEG has been used to assess the neurologic function of patients in the hours and days after cardiac arrest. Accurate and reliable prognostication after cardiac arrest is vital for tailoring aggressive patient care for those with a high likelihood of recovery and setting appropriate goals of care for those who have a high likelihood of a poor outcome. Attempts to define EEG's role in this process has evolved over the years. In this review, we provide important historical context about EEG's use, it's perceived unreliability in the post-cardiac arrest patient in the past and provide a detailed analysis of how this role has changed recently. A review of the 71 most recent and highest quality studies demonstrates that the introduction of a uniform classification and a timed approach to EEG analysis have positioned EEG as a complementary tool in the multimodal approach for prognostication. The review was created and intended for medical staff in the intensive care units and emphasizes EEG patterns and timing which portend both favorable and poor prognoses. Also, the review addresses the overall quality of the existing studies and discusses future directions to address the knowledge gaps in this field.
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Affiliation(s)
- Jay Bronder
- Epilepsy Fellow, Department of Neurology, Johns Hopkins Hospital, 600 N. Wolfe St / Meyer 2-147, Baltimore, MD 21287-7247, USA
| | - Sung-Min Cho
- Neuroscience Critical Care Division, Departments of Neurology, Neurosurgery, and Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Baltimore, MD 21287, USA
| | - Romergryko G. Geocadin
- Professor of Neurology, Anesthesiology-Critical Care, Neurosurgery, and Joint Appointment in Medicine, The Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Phipps 455, Baltimore, MD 21287, USA
| | - Eva Katharina Ritzl
- Department of Neurology and Anesthesia and Critical Care Medicine, Johns Hopkins Hospital, 1800 Orleans Street, Suite 3329, Baltimore, MD 21287, USA
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Critical care EEG standardized nomenclature in clinical practice: Strengths, limitations, and outlook on the example of prognostication after cardiac arrest. Clin Neurophysiol Pract 2022; 6:149-154. [PMID: 35112033 PMCID: PMC8790140 DOI: 10.1016/j.cnp.2021.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 01/08/2021] [Accepted: 03/03/2021] [Indexed: 11/21/2022] Open
Abstract
Optimal use of the ACNS nomenclature implies integration of clinical information. Knowledge of pathophysiological mechanisms of EEG patterns may help interpretation. Standardized therapeutic procedures for critical care patients are needed.
We discuss the achievements of the ACNS critical care EEG nomenclature proposed in 2013 and, from a clinical angle, outline some limitations regarding translation into treatment implications. While the recently proposed updated 2021 version of the nomenclature will probable improve some uncertainty areas, a refined understanding of the mechanisms at the origin of the EEG patterns, and a multimodal integration of the nomenclature to the clinical context may help improving the rationale supporting therapeutic procedures. We illustrate these aspects on prognostication after cardiac arrest.
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Key Words
- ACNS, American Clinical Neurophysiology Society
- American Clinical Neurophysiology Society (ACNS) Standardized Terminology
- BIRD, Brief potentially ictal rhythmic discharge
- BS, Burst suppression
- Burst suppression
- CA, Cardiac arrest
- Cardiac arrest (CA)
- DWI, diffusion-weighted MRI
- ESI, electric source imaging
- GPD
- GPD, generalized periodic discharge
- GRDA, generalized rhythmic delta activity
- ICU, Intensive care unit
- ICU-EEG, intensive care unit-electroencephalography
- IIC, Ictal-Interictal Continuum
- Ictal-Interictal Continuum
- LPD, Lateralized periodic discharge
- MEG, Magneto-electroencephalography
- NCSE, Non-Convulsive Status Epilepticus
- NSE, Serum neuron-specific enolase
- PET, Positron emission tomography
- Prognostication assessment
- SE, Status epilepticus
- SPECT, Single Photon Emission Computed Tomography
- SSEP, Somatosensory evoked potentials
- WLST, Withdraw of life sustaining treatment
- fMRI, functional MRI
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Aufderheide TP, Kalra R, Kosmopoulos M, Bartos JA, Yannopoulos D. Enhancing cardiac arrest survival with extracorporeal cardiopulmonary resuscitation: insights into the process of death. Ann N Y Acad Sci 2022; 1507:37-48. [PMID: 33609316 PMCID: PMC8377067 DOI: 10.1111/nyas.14580] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/30/2021] [Accepted: 02/02/2021] [Indexed: 01/03/2023]
Abstract
Extracorporeal cardiopulmonary resuscitation (ECPR) is an emerging method of cardiopulmonary resuscitation to improve outcomes from cardiac arrest. This approach targets patients with out-of-hospital cardiac arrest previously unresponsive and refractory to standard treatment, combining approximately 1 h of standard CPR followed by venoarterial extracorporeal membrane oxygenation (VA-ECMO) and coronary artery revascularization. Despite its relatively new emergence for the treatment of cardiac arrest, the approach is grounded in a vast body of preclinical and clinical data that demonstrate significantly improved survival and neurological outcomes despite unprecedented, prolonged periods of CPR. In this review, we detail the principles behind VA-ECMO-facilitated resuscitation, contemporary clinical approaches with outcomes, and address the emerging new understanding of the process of death and capability for neurological recovery.
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Affiliation(s)
- Tom P. Aufderheide
- Department of Emergency Medicine, Medical College of Wisconsin, Milwaukee, WI
| | - Rajat Kalra
- Center for Resuscitation Medicine, University of Minnesota Medical School, Minneapolis, MN,Cardiovascular Division, University of Minnesota, Minneapolis, MN
| | - Marinos Kosmopoulos
- Center for Resuscitation Medicine, University of Minnesota Medical School, Minneapolis, MN
| | - Jason A. Bartos
- Center for Resuscitation Medicine, University of Minnesota Medical School, Minneapolis, MN,Cardiovascular Division, University of Minnesota, Minneapolis, MN
| | - Demetris Yannopoulos
- Center for Resuscitation Medicine, University of Minnesota Medical School, Minneapolis, MN,Cardiovascular Division, University of Minnesota, Minneapolis, MN
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Awakening from post anoxic coma with burst suppression with identical bursts. Resusc Plus 2021; 7:100151. [PMID: 34386780 PMCID: PMC8342773 DOI: 10.1016/j.resplu.2021.100151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/14/2021] [Accepted: 07/02/2021] [Indexed: 11/20/2022] Open
Abstract
Background Electroencephalography (EEG) is commonly used after cardiac arrest. Burst suppression with identical bursts (BSIB) has been reported as a perfectly specific predictor of poor outcome but published case series are small. We describe two patients with BSIB who awakened from coma after cardiac arrest. Methods We identified two out-of-hospital cardiac arrest (OHCA) patients with coma and BSIB. We determined the etiology of arrest, presenting neurological examination, potential confounders to neurological assessment, neurodiagnostics and time to awakening. We reviewed and interpreted EEGs using 2021 American Clinical Neurophysiology Society guidelines. We quantified identicality of bursts by calculating pairwise correlation coefficients between the first 500 ms of each aligned burst. Results In case one we present a 62-year-old man with OHCA secondary to septic shock. EEG showed burst suppression pattern, with bursts consisted of high amplitude generalized spike waves in lock-step with myoclonus (inter-burst correlation = 0.86). He followed commands 3 days after arrest, when repeat EEG showed a continuous, variable and reactive background without epileptiform activity. Case two was a 49-year-old woman with OHCA secondary to polysubstance overdose. Initial EEG revealed burst suppression with high amplitude generalized polyspike-wave bursts with associated myoclonus. She followed commands on post-arrest day 4, when repeat EEG showed a continuous, variable and reactive background with frequent runs of bifrontal predominant sharply contoured rhythmic delta activity. Conclusion These cases highlight the perils of prognosticating with a single modality in comatose cardiac arrest patients.
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Kim YM, Jeung KW, Kim WY, Park YS, Oh JS, You YH, Lee DH, Chae MK, Jeong YJ, Kim MC, Ha EJ, Hwang KJ, Kim WS, Lee JM, Cha KC, Chung SP, Park JD, Kim HS, Lee MJ, Na SH, Kim ARE, Hwang SO. 2020 Korean Guidelines for Cardiopulmonary Resuscitation. Part 5. Post-cardiac arrest care. Clin Exp Emerg Med 2021; 8:S41-S64. [PMID: 34034449 PMCID: PMC8171174 DOI: 10.15441/ceem.21.025] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 03/07/2021] [Accepted: 03/19/2021] [Indexed: 12/20/2022] Open
Affiliation(s)
- Young-Min Kim
- Department of Emergency Medicine, The Catholic University of Korea College of Medicine, Seoul, Korea
| | - Kyung Woon Jeung
- Department of Emergency Medicine, Chonnam National University College of Medicine, Gwangju, Korea
| | - Won Young Kim
- Department of Emergency Medicine, Asan Medical Center, Ulsan University College of Medicine, Seoul, Korea
| | - Yoo Seok Park
- Department of Emergency Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Joo Suk Oh
- Department of Emergency Medicine, The Catholic University of Korea College of Medicine, Seoul, Korea
| | - Yeon Ho You
- Department of Emergency Medicine, Chungnam National University College of Medicine, Daejeon, Korea
| | - Dong Hoon Lee
- Department of Emergency Medicine, Chung-Ang University College of Medicine, Seoul, Korea
| | - Minjung Kathy Chae
- Department of Emergency Medicine, Ajou University College of Medicine, Suwon, Korea
| | - Yoo Jin Jeong
- Department of Emergency Medicine, Chonnam National University College of Medicine, Gwangju, Korea
| | - Min Chul Kim
- Department of Internal Medicine, Chonnam National University College of Medicine, Gwangju, Korea
| | - Eun Jin Ha
- Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Korea
| | - Kyoung Jin Hwang
- Department of Neurology, Kyung Hee University College of Medicine, Seoul, Korea
| | - Won-Seok Kim
- Department of Rehabilitation Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jae Myung Lee
- Department of General Surgery, Korea University College of Medicine, Seoul, Korea
| | - Kyoung-Chul Cha
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Sung Phil Chung
- Department of Emergency Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - June Dong Park
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Korea
| | - Han-Suk Kim
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Korea
| | - Mi Jin Lee
- Department of Emergency Medicine, Kyoungbook University College of Medicine, Daegu, Korea
| | - Sang-Hoon Na
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Ai-Rhan Ellen Kim
- Department of Pediatrics, Ulsan University College of Medicine, Seoul, Korea
| | - Sung Oh Hwang
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - on behalf of the Steering Committee of 2020 Korean Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care
- Department of Emergency Medicine, The Catholic University of Korea College of Medicine, Seoul, Korea
- Department of Emergency Medicine, Chonnam National University College of Medicine, Gwangju, Korea
- Department of Emergency Medicine, Asan Medical Center, Ulsan University College of Medicine, Seoul, Korea
- Department of Emergency Medicine, Yonsei University College of Medicine, Seoul, Korea
- Department of Emergency Medicine, Chungnam National University College of Medicine, Daejeon, Korea
- Department of Emergency Medicine, Chung-Ang University College of Medicine, Seoul, Korea
- Department of Emergency Medicine, Ajou University College of Medicine, Suwon, Korea
- Department of Internal Medicine, Chonnam National University College of Medicine, Gwangju, Korea
- Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Korea
- Department of Neurology, Kyung Hee University College of Medicine, Seoul, Korea
- Department of Rehabilitation Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
- Department of General Surgery, Korea University College of Medicine, Seoul, Korea
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Korea
- Department of Emergency Medicine, Kyoungbook University College of Medicine, Daegu, Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
- Department of Pediatrics, Ulsan University College of Medicine, Seoul, Korea
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Peluso L, Legros B, Caroyer S, Taccone FS, Gaspard N. Falsely predictive EEG and clinical signs after post-anoxic brain injury under sevoflurane anesthesia. Clin Neurophysiol 2021; 132:1080-1082. [PMID: 33765473 DOI: 10.1016/j.clinph.2021.02.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 02/09/2021] [Accepted: 02/12/2021] [Indexed: 12/01/2022]
Affiliation(s)
- Lorenzo Peluso
- Department of Intensive Care Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Benjamin Legros
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Sarah Caroyer
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Fabio Silvio Taccone
- Department of Intensive Care Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
| | - Nicolas Gaspard
- Department of Neurology Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium
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Abstract
PURPOSE OF REVIEW Randomized controlled trials investigating the initial pharmacological treatment of status epilepticus have been recently published. Furthermore, status epilepticus arising in comatose survivors after cardiac arrest has received increasing attention in the last years. This review offers an updated assessment of status epilepticus treatment in these different scenarios. RECENT FINDINGS Initial benzodiazepines underdosing is common and correlates with development of status epilepticus refractoriness. The recently published ESETT trial provides high-level evidence regarding the equivalence of fosphenytoin, valproate, and levetiracetam as a second-line option. Myoclonus or epileptiform transients on electroencephalography occur in up to 1/3 of patients surviving a cardiac arrest. Contrary to previous assumptions regarding an almost invariable association with death, at least 1/10 of them may awaken with reasonably good prognosis, if treated. Multimodal prognostication including clinical examination, EEG, somatosensory evoked potentials, biochemical markers, and neuroimaging help identifying patients with a chance to recover consciousness, in whom a trial with antimyoclonic compounds and at times general anesthetics is indicated. SUMMARY There is a continuous, albeit relatively slow progress in knowledge regarding different aspect of status epilepticus; recent findings refine some treatment strategies and help improving patients' outcomes. Further high-quality studies are clearly needed to further improve the management of these patients, especially those with severe, refractory status epilepticus forms.
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Detection of Epileptic Seizures Using Wavelet Transform, Peak Extraction and PSR from EEG Signals. Symmetry (Basel) 2020. [DOI: 10.3390/sym12081239] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In this study, techniques were proposed for the detection of epileptic seizures from electroencephalogram (EEG) signals using the wavelet transform (WT), peak extraction and phase–space reconstruction (PSR) based Euclidean distances. In the first step, the wavelet coefficients were extracted after eliminating the noise from the EEG signals using a WT, which is a widely used signal processing technique. In the second step, the peaks were extracted from the wavelet coefficients. In the third step, the continuous peaks that were extracted were mapped to 3D coordinates using PSR. In the fourth step, the Euclidean distances between the mapped 3D coordinates and the origin were obtained. The features of the Euclidean distances obtained were extracted using statistical techniques. The final features extracted were used as inputs to the neural network with weighted fuzzy membership (NEWFM). NEWFM contains the bounded sum of weighted fuzzy memberships (BSWFMs) that can reveal the differences in the graphic characteristics between normal EEG signals and epileptic-seizure EEG signals. The BSWFMs can easily be embedded in a portable device to detect epileptic seizures from EEG signals in real life.
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