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Alkhachroum A, Ganesan SL, Koren JP, Kromm J, Massad N, Reyes RA, Miller MR, Roh D, Agarwal S, Park S, Claassen J. Quantitative EEG-Based Seizure Estimation in Super-Refractory Status Epilepticus. Neurocrit Care 2022; 36:897-904. [PMID: 34791594 PMCID: PMC9987776 DOI: 10.1007/s12028-021-01395-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 11/04/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND The objective of this study was to evaluate the accuracy of seizure burden in patients with super-refractory status epilepticus (SRSE) by using quantitative electroencephalography (qEEG). METHODS EEG recordings from 69 patients with SRSE (2009-2019) were reviewed and annotated for seizures by three groups of reviewers: two board-certified neurophysiologists using only raw EEG (gold standard), two neurocritical care providers with substantial experience in qEEG analysis (qEEG experts), and two inexperienced qEEG readers (qEEG novices) using only a qEEG trend panel. RESULTS Raw EEG experts identified 35 (51%) patients with seizures, accounting for 2950 seizures (3,126 min). qEEG experts had a sensitivity of 93%, a specificity of 61%, a false positive rate of 6.5 per day, and good agreement (κ = 0.64) between both qEEG experts. qEEG novices had a sensitivity of 98.5%, a specificity of 13%, a false positive rate of 15 per day, and fair agreement (κ = 0.4) between both qEEG novices. Seizure burden was not different between the qEEG experts and the gold standard (3,257 vs. 3,126 min), whereas qEEG novices reported higher burden (6066 vs. 3126 min). CONCLUSIONS Both qEEG experts and novices had a high sensitivity but a low specificity for seizure detection in patients with SRSE. qEEG could be a useful tool for qEEG experts to estimate seizure burden in patients with SRSE.
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Affiliation(s)
- Ayham Alkhachroum
- Department of Neurology, Columbia University and NewYork Presbyterian Hospital, New York, NY, USA
- Department of Neurology, University of Miami, Miami, FL, USA
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, USA
| | - Saptharishi Lalgudi Ganesan
- Children's Hospital of Western Ontario, London Health Sciences Centre, London, ON, Canada
- Department of Paediatrics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Julie Kromm
- Departments of Critical Care Medicine and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Nina Massad
- Department of Neurology, Columbia University and NewYork Presbyterian Hospital, New York, NY, USA
| | - Renz A Reyes
- Department of Neurology, Columbia University and NewYork Presbyterian Hospital, New York, NY, USA
| | - Michael R Miller
- Children's Hospital of Western Ontario, London Health Sciences Centre, London, ON, Canada
- Department of Paediatrics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - David Roh
- Department of Neurology, Columbia University and NewYork Presbyterian Hospital, New York, NY, USA
| | - Sachin Agarwal
- Department of Neurology, Columbia University and NewYork Presbyterian Hospital, New York, NY, USA
| | - Soojin Park
- Department of Neurology, Columbia University and NewYork Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University and NewYork Presbyterian Hospital, New York, NY, USA.
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Taran S, Ahmed W, Pinto R, Bui E, Prisco L, Hahn CD, Englesakis M, McCredie VA. Educational initiatives for electroencephalography in the critical care setting: a systematic review and meta-analysis. Can J Anaesth 2021; 68:1214-1230. [PMID: 33709264 PMCID: PMC7952081 DOI: 10.1007/s12630-021-01962-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/18/2021] [Accepted: 01/18/2021] [Indexed: 11/22/2022] Open
Abstract
PURPOSE We systematically reviewed existing critical care electroencephalography (EEG) educational programs for non-neurologists, with the primary goal of reporting the content covered, methods of instruction, overall duration, and participant experience. Our secondary goals were to assess the impact of EEG programs on participants' core knowledge, and the agreement between non-experts and experts for seizure identification. SOURCE Major databases were searched from inception to 30 August 2020. Randomized controlled trials, cohort studies, and descriptive studies were all considered if they reported an EEG curriculum for non-neurologists in a critical care setting. Data were presented thematically for the qualitative primary outcome and a meta-analysis using a random effects model was performed for the quantitative secondary outcomes. PRINCIPAL FINDINGS Twenty-nine studies were included after reviewing 7,486 citations. Twenty-two studies were single centre, 17 were from North America, and 16 were published after 2016. Most EEG studies were targeted to critical care nurses (17 studies), focused on processed forms of EEG with amplitude-integrated EEG being the most common (15 studies), and were shorter than one day in duration (24 studies). In pre-post studies, EEG programs significantly improved participants' knowledge of tested material (standardized mean change, 1.79; 95% confidence interval [CI], 0.86 to 2.73). Agreement for seizure identification between non-experts and experts was moderate (Cohen's kappa = 0.44; 95% CI, 0.27 to 0.60). CONCLUSIONS It is feasible to teach basic EEG to participants in critical care settings from different clinical backgrounds, including physicians and nurses. Brief training programs can enable bedside providers to recognize high-yield abnormalities such as non-convulsive seizures.
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Affiliation(s)
- Shaurya Taran
- Interdepartmental Division of Critical Care Medicine, Department of Medicine, Li Ka Shing Knowledge Institute, University of Toronto, 204 Victoria Street, 4th Floor Room 411, Toronto, ON, M5B 1T8, Canada.
| | - Wael Ahmed
- Department of Critical Care Medicine, Sunnybrook Health Sciences Center, Toronto, ON, Canada
| | - Ruxandra Pinto
- Department of Critical Care Medicine, Sunnybrook Health Sciences Center, Toronto, ON, Canada
| | - Esther Bui
- Division of Neurology, University Health Network, Toronto, ON, Canada
| | - Lara Prisco
- Neurosciences Intensive Care Unit, John Radcliffe Hospital, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Cecil D Hahn
- Division of Neurology, The Hospital for Sick Children, and Department of Pediatrics, University of Toronto, Toronto, ON, Canada
| | - Marina Englesakis
- Library and Information Services, University Health Network, Toronto, ON, Canada
| | - Victoria A McCredie
- Interdepartmental Division of Critical Care Medicine, Department of Medicine, Li Ka Shing Knowledge Institute, University of Toronto, 204 Victoria Street, 4th Floor Room 411, Toronto, ON, M5B 1T8, Canada
- Department of Critical Care Medicine, Sunnybrook Health Sciences Center, Toronto, ON, Canada
- Division of Critical Care Medicine, Department of Medicine, University Health Network, Toronto, ON, Canada
- Krembil Research Institute, University Health Network, Toronto, ON, Canada
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Kromm J, Fiest KM, Alkhachroum A, Josephson C, Kramer A, Jette N. Structure and Outcomes of Educational Programs for Training Non-electroencephalographers in Performing and Screening Adult EEG: A Systematic Review. Neurocrit Care 2021; 35:894-912. [PMID: 33591537 DOI: 10.1007/s12028-020-01172-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 12/01/2020] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To qualitatively and quantitatively summarize curricula, teaching methods, and effectiveness of educational programs for training bedside care providers (non-experts) in the performance and screening of adult electroencephalography (EEG) for nonconvulsive seizures and other patterns. METHODS PRISMA methodological standards were followed. MEDLINE, EMBASE, Cochrane, CINAHL, WOS, Scopus, and MedEdPORTAL databases were searched from inception until February 26, 2020 with no restrictions. Abstract and full-text review was completed in duplicate. Studies were included if they were original research; involved non-experts performing, troubleshooting, or screening adult EEG; and provided qualitative descriptions of curricula and teaching methods and/or quantitative assessment of non-experts (vs gold standard EEG performance by neurodiagnostic technologists or interpretation by neurophysiologists). Data were extracted in duplicate. A content analysis and a meta-narrative review were performed. RESULTS Of 2430 abstracts, 35 studies were included. Sensitivity and specificity of seizure identification varied from 38 to 100% and 65 to 100% for raw EEG; 40 to 93% and 38 to 95% for quantitative EEG, and 95 to 100% and 65 to 85% for sonified EEG, respectively. Non-expert performance of EEG resulted in statistically significant reduced delay (86 min, p < 0.0001; 196 min, p < 0.0001; 667 min, p < 0.005) in EEG completion and changes in management in approximately 40% of patients. Non-experts who were trained included physicians, nurses, neurodiagnostic technicians, and medical students. Numerous teaching methods were utilized and often combined, with instructional and hands-on training being most common. CONCLUSIONS Several different bedside providers can be educated to perform and screen adult EEG, particularly for the purpose of diagnosing nonconvulsive seizures. While further rigorous research is warranted, this review demonstrates several potential bridges by which EEG may be integrated into the care of critically ill patients.
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Affiliation(s)
- Julie Kromm
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Room 04112, Foothills Medical Centre, McCaig Tower, 3134 Hospital Drive NW, Calgary, Alberta, T2N 5A1, Canada. .,Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Canada. .,Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Canada.
| | - Kirsten M Fiest
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Room 04112, Foothills Medical Centre, McCaig Tower, 3134 Hospital Drive NW, Calgary, Alberta, T2N 5A1, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Ayham Alkhachroum
- Neurocritical Care Division, Miller School of Medicine, University of Miami, Miami, USA
| | - Colin Josephson
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Andreas Kramer
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Room 04112, Foothills Medical Centre, McCaig Tower, 3134 Hospital Drive NW, Calgary, Alberta, T2N 5A1, Canada.,Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Nathalie Jette
- Department of Neurology, Icahn School of Medicine, Mount Sinai, New York, USA
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Lobo FA, Vacas S, Rossetti AO, Robba C, Taccone FS. Does electroencephalographic burst suppression still play a role in the perioperative setting? Best Pract Res Clin Anaesthesiol 2020; 35:159-169. [PMID: 34030801 DOI: 10.1016/j.bpa.2020.10.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 10/21/2020] [Accepted: 10/27/2020] [Indexed: 12/18/2022]
Abstract
With the widespread use of electroencephalogram [EEG] monitoring during surgery or in the Intensive Care Unit [ICU], clinicians can sometimes face the pattern of burst suppression [BS]. The BS pattern corresponds to the continuous quasi-periodic alternation between high-voltage slow waves [the bursts] and periods of low voltage or even isoelectricity of the EEG signal [the suppression] and is extremely rare outside ICU and the operative room. BS can be secondary to increased anesthetic depth or a marker of cerebral damage, as a therapeutic endpoint [i.e., refractory status epilepticus or refractory intracranial hypertension]. In this review, we report the neurophysiological features of BS to better define its role during intraoperative and critical care settings.
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Affiliation(s)
- Francisco Almeida Lobo
- Anesthesiology Department, Centro Hospitalar de Trás-os-Montes e Alto Douro, Avenida da Noruega, Lordelo, 5000-508, Vila Real, Portugal.
| | - Susana Vacas
- Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Reagan UCLA Medical Center, 757 Westwood Plaza #3325, Los Angeles, CA, 90095, USA.
| | - Andrea O Rossetti
- Department of Neurology, Lausanne University Hospital and University of Lausanne, CH-1011, Lausanne, Switzerland.
| | - Chiara Robba
- Azienda Ospedaliera Universitaria San Martino di Genova, Largo Rosanna Benzi,15, 16100, Genova, Italy.
| | - Fabio Silvio Taccone
- Hopital Érasme, Université Libre de Bruxelles, Department of Intensive Care Medicine, Route de Lennik, 808 1070, Brussels, Belgium.
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Abstract
The growing use of continuous video-EEG recording in the inpatient setting, in particular in patients with varying degrees of encephalopathy, has yielded a window to the brain with an excellent temporal resolution. This increasingly available tool has become more than an instrument to detect nonconvulsive seizures (its primary use), and clinical indications span from ischemia detection in acute brain injuries, neuroprognostication of comatose patients, to monitoring the degree of encephalopathy. In this context, abnormal findings such as periodic discharges and rhythmic delta activity were increasingly recognized; however, significant subjectivity remained in the interpretation of these findings pertaining to key features regarding their spatial involvement, prevalence of occurrence, duration, associated morphologic features, and behavior. In 2005, the American Clinical Neurophysiology Society proposed standardized definitions and classification of electroencephalographic rhythmic and periodic patterns. This was subsequently revised in 2011 and in 2012 and is now being used by centers worldwide, with the final version published in early 2013 as an official guideline of the ACNS. The resulting uniform terminology has allowed for significant advances in the understanding of the pathophysiology, epileptogenic potential, and overall clinical implication of these patterns. Investigators across multiple institutions are now able to collaborate while exploring diagnostic and therapeutic algorithms to these patterns, an effort that may soon provide definitive evidence guiding treating clinicians on the management of these patients.
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Koren JP, Herta J, Fürbass F, Pirker S, Reiner-Deitemyer V, Riederer F, Flechsenhar J, Hartmann M, Kluge T, Baumgartner C. Automated Long-Term EEG Review: Fast and Precise Analysis in Critical Care Patients. Front Neurol 2018; 9:454. [PMID: 29973906 PMCID: PMC6020775 DOI: 10.3389/fneur.2018.00454] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Accepted: 05/29/2018] [Indexed: 12/27/2022] Open
Abstract
Background: Ongoing or recurrent seizure activity without prominent motor features is a common burden in neurological critical care patients and people with epilepsy during ICU stays. Continuous EEG (CEEG) is the gold standard for detecting ongoing ictal EEG patterns and monitoring functional brain activity. However CEEG review is very demanding and time consuming. The purpose of the present multirater, EEG expert reviewer study, is to test and assess the clinical feasibility of an automatic EEG pattern detection method (Neurotrend). Methods: Four board certified EEG reviewers used Neurotrend to annotate 76 CEEG datasets à 6 h (in total 456 h of EEG) for rhythmic and periodic EEG patterns (RPP), unequivocal ictal EEG patterns and burst suppression. All reviewers had a predefined time limit of 5 min (± 2 min) per CEEG dataset and were compared to a predefined gold standard (conventional EEG review with unlimited time). Subanalysis of specific features of RPP was conducted as well. We used Gwet's AC1 and AC2 coefficients to calculate interrater agreement (IRA) and multirater agreement (MRA). Also, we determined individual performance measures for unequivocal ictal EEG patterns and burst suppression. Bonferroni-Holmes correction for multiple testing was applied to all statistical tests. Results: Mean review time was 3.3 min (± 1.9 min) per CEEG dataset. We found substantial IRA for unequivocal ictal EEG patterns (0.61–0.79; mean sensitivity 86.8%; mean specificity 82.2%, p < 0.001) and burst suppression (0.68–0.71; mean sensitivity 96.7%; mean specificity 76.9% p < 0.001). Two reviewers showed substantial IRA for RPP (0.68–0.72), whereas the other two showed moderate agreement (0.45–0.54), compared to the gold standard (p < 0.001). MRA showed almost perfect agreement for burst suppression (0.86) and moderate agreement for RPP (0.54) and unequivocal ictal EEG patterns (0.57). Conclusions: We demonstrated the clinical feasibility of an automatic critical care EEG pattern detection method on two levels: (1) reasonable high agreement compared to the gold standard, (2) reasonable short review times compared to previously reported EEG review times with conventional EEG analysis.
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Affiliation(s)
- Johannes P Koren
- Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria.,Department of Neurology, General Hospital Hietzing With Neurological Center Rosenhügel, Vienna, Austria
| | - Johannes Herta
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Franz Fürbass
- Center for Health and Bioresources, AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | - Susanne Pirker
- Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria.,Department of Neurology, General Hospital Hietzing With Neurological Center Rosenhügel, Vienna, Austria
| | - Veronika Reiner-Deitemyer
- Department of Neurology, General Hospital Hietzing With Neurological Center Rosenhügel, Vienna, Austria
| | - Franz Riederer
- Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria.,Department of Neurology, General Hospital Hietzing With Neurological Center Rosenhügel, Vienna, Austria
| | - Julia Flechsenhar
- Department of Neurology, General Hospital Hietzing With Neurological Center Rosenhügel, Vienna, Austria.,Epilepsie-Zentrum Berlin-Brandenburg, Ev. Krankenhaus Königin Elisabeth Herzberge, Berlin, Germany
| | - Manfred Hartmann
- Center for Health and Bioresources, AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | - Tilmann Kluge
- Center for Health and Bioresources, AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | - Christoph Baumgartner
- Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria.,Department of Neurology, General Hospital Hietzing With Neurological Center Rosenhügel, Vienna, Austria.,Medical Faculty, Sigmund Freud University, Vienna, Austria
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West N, McBeth PB, Brodie SM, van Heusden K, Sunderland S, Dumont GA, Griesdale DEG, Ansermino JM, Görges M. Feasibility of continuous sedation monitoring in critically ill intensive care unit patients using the NeuroSENSE WAV CNS index. J Clin Monit Comput 2018; 32:1081-91. [PMID: 29464512 DOI: 10.1007/s10877-018-0115-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 02/16/2018] [Indexed: 10/18/2022]
Abstract
Sedation in the intensive care unit (ICU) is challenging, as both over- and under-sedation are detrimental. Current methods of assessment, such as the Richmond Agitation Sedation Scale (RASS), are measured intermittently and rely on patients' behavioral response to stimulation, which may interrupt sleep/rest. A non-stimulating method for continuous sedation monitoring may be beneficial and allow more frequent assessment. Processed electroencephalography (EEG) monitors have not been routinely adopted in the ICU. The aim of this observational study was to assess the feasibility of using the NeuroSENSE™ monitor for EEG-based continuous sedation assessment. With ethical approval, ICU patients on continuous propofol sedation were recruited. Depth-of-hypnosis index (WAVCNS) values were obtained from the NeuroSENSE. Bedside nurses, blinded to the NeuroSENSE, performed regular RASS assessments and maintained the sedation regimen as per standard of care. Participants were monitored throughout the duration of their propofol infusion, up to 24 h. Fifteen patients, with median [interquartile range] age of 57 [52-62.5] years were each monitored for a duration of 9.0 [5.7-20.1] h. Valid WAVCNS values were obtained for 89% [66-99] of monitoring time and were widely distributed within and between individuals, with 6% [1-31] spent < 40 (very deep), and 3% [1-15] spent > 90 (awake). Significant EEG suppression was detected in 3/15 (20%) participants. Observed RASS matched RASS goals in 36/89 (40%) assessments. The WAVCNS variability, and incidence of EEG suppression, highlight the limitations of using RASS as a standalone sedation measure, and suggests potential benefit of adjunct continuous brain monitoring.
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