{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T21:32:01Z","timestamp":1775079121123,"version":"3.50.1"},"reference-count":68,"publisher":"American Society of Tropical Medicine and Hygiene","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,4,1]]},"abstract":"<jats:title>ABSTRACT.<\/jats:title>\n                  <jats:p>Electroencephalography (EEG) is a diagnostic and prognostic tool used worldwide in the clinical care of comatose patients. Scalability of EEG use in resource-limited settings is constrained by multiple factors, including the lack of neurophysiologist interpreters. Although machine learning offers a path to creation of automated interpretation algorithms, development is constrained by the need for independent inputs from multiple neurophysiologists. Development may be accelerated if independent inputs have high concurrence. We assessed interrater reliability of key EEG variables from studies recorded from febrile comatose African children to better understand the need for numbers of inputs required in the development of future machine learning-driven EEG interpretation algorithms. Two independent electrophysiologists interpreted 171 electroencephalograms from children in febrile coma using standard methods. Interrater reliability was highest for the presence of electrographic seizures, with overall agreement of 96.5% and kappa of 0.781 (95% CI: 0.612\u20130.950). Electroencephalography variables commonly used in prognostication for cerebral malaria, a common cause of febrile coma, also had high agreement rates. Electroencephalography interpretation in Malawian children with febrile coma offers high interrater reliability in key variables used to guide clinical care and estimate prognosis. This suggests that automated interpretation methods could be developed using limited numbers of human expert trainers, accelerating development of data-driven diagnostic and prognostic algorithms for resource-limited locations. Deployment of automated EEG diagnostic and prognostic interpretation algorithms for use in high-disease-burden, low-resource settings would aid in the clinical care of febrile comatose children, increasing the possibility of favorable clinical outcomes.<\/jats:p>","DOI":"10.4269\/ajtmh.25-0685","type":"journal-article","created":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T13:47:13Z","timestamp":1773841633000},"page":"774-779","source":"Crossref","is-referenced-by-count":0,"title":["Interrater Reliability of Electroencephalogram Interpretations in Febrile Comatose African Children: Implications for Automated Interpretation Algorithm Creation"],"prefix":"10.4269","volume":"114","author":[{"given":"Mrinmayee","family":"Takle","sequence":"first","affiliation":[{"name":"Division of Neurology, The George Washington University\/Children\u2019s National Hospital, Washington, District of Columbia;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Andrews","sequence":"additional","affiliation":[{"name":"Division of Neurology, The George Washington University\/Children\u2019s National Hospital, Washington, District of Columbia;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tesfaye","family":"Zelleke","sequence":"additional","affiliation":[{"name":"Division of Neurology, The George Washington University\/Children\u2019s National Hospital, Washington, District of Columbia;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dana B.","family":"Harrar","sequence":"additional","affiliation":[{"name":"Division of Neurology, The George Washington University\/Children\u2019s National Hospital, Washington, District of Columbia;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Barber","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Study Methodology, Children\u2019s National Research Institute, Washington, District of Columbia;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizabeth","family":"Kalanga","sequence":"additional","affiliation":[{"name":"Blantyre Malaria Project, Kamuzu University of Health Sciences, Blantyre, Malawi;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gladys W. K.","family":"Mkandawire","sequence":"additional","affiliation":[{"name":"Blantyre Malaria Project, Kamuzu University of Health Sciences, Blantyre, Malawi;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cynthia","family":"Manyozo","sequence":"additional","affiliation":[{"name":"Blantyre Malaria Project, Kamuzu University of Health Sciences, Blantyre, Malawi;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monica","family":"Sapuwa","sequence":"additional","affiliation":[{"name":"Blantyre Malaria Project, Kamuzu University of Health Sciences, Blantyre, Malawi;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charlotte","family":"Fuller","sequence":"additional","affiliation":[{"name":"The Brain Infection and Inflammation Group Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael J.","family":"Griffiths","sequence":"additional","affiliation":[{"name":"The Brain Infection and Inflammation Group Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom;"},{"name":"Centre for Child and Adolescent Health Research, Faculty of Medicine and Health, University of Sydney, Sydney, Australia;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen T. J.","family":"Ray","sequence":"additional","affiliation":[{"name":"Blantyre Malaria Project, Kamuzu University of Health Sciences, Blantyre, Malawi;"},{"name":"Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom;"},{"name":"Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Douglas G.","family":"Postels","sequence":"additional","affiliation":[{"name":"Division of Neurology, The George Washington University\/Children\u2019s National Hospital, Washington, District of Columbia;"},{"name":"Blantyre Malaria Project, Kamuzu University of Health Sciences, Blantyre, Malawi;"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2795","reference":[{"key":"b1","series-title":"Lancet Glob Health","first-page":"e1043","article-title":"The aetiologies, mortality, and disability of non-traumatic coma in African children: A systematic review and 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populations predict outcomes","volume":"17","author":"Postels","year":"2018"},{"key":"b11","series-title":"Pediatr Neurol","first-page":"96","article-title":"Using EEG in resource-limited areas: Comparing qualitative and quantitative interpretation methods in cerebral malaria","volume":"126","author":"Andrews","year":"2022"},{"key":"b12","series-title":"J Clin Neurophysiol","first-page":"136","article-title":"Theta-alpha variability on admission EEG is associated with outcome in pediatric cerebral malaria","volume":"40","author":"Andrews","year":"2023"},{"key":"b13","series-title":"Epilepsy Behav","first-page":"107536","article-title":"EEG markers predictive of epilepsy risk in pediatric cerebral malaria\u2014A feasibility study","volume":"113","author":"Patel","year":"2020"},{"key":"b14","series-title":"Epilepsia","first-page":"2955","article-title":"Periodic and rhythmic patterns in critically ill children: Incidence, interrater agreement, and 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clinical trial validity","volume":"56","author":"Hussain","year":"2015"},{"key":"b19","series-title":"J Clin Neurophysiol","first-page":"230","article-title":"A multicenter training and interrater reliability study of the BASED score for infantile epileptic spasms syndrome","volume":"42","author":"Mytinger","year":"2025"},{"key":"b20","series-title":"Epileptic Disord","first-page":"827","article-title":"Unveiling variability: A systematic review of reproducibility in visual EEG analysis, with focus on seizures","volume":"26","author":"Aanestad","year":"2024"},{"key":"b21","series-title":"J Clin Neurophysiol","first-page":"1","article-title":"American Clinical Neurophysiology Society\u2019s standardized critical care EEG terminology: 2021 version","volume":"38","author":"Hirsch","year":"2021"},{"key":"b22","series-title":"J Clin Neurophysiol","first-page":"15","article-title":"Interobserver reproducibility of electroencephalogram interpretation in critically ill children","volume":"28","author":"Abend","year":"2011"},{"key":"b23","series-title":"J Clin Neurophysiol","first-page":"534","article-title":"Interrater agreement of EEG interpretation after pediatric cardiac arrest using standardized critical care EEG terminology","volume":"34","author":"Abend","year":"2017"},{"key":"b24","series-title":"Early Hum Dev","first-page":"105011","article-title":"Inter-rater reliability of amplitude-integrated EEG for the detection of neonatal seizures","volume":"143","author":"Rakshasbhuvankar","year":"2020"},{"key":"b25","series-title":"Epilepsia","first-page":"77","article-title":"Hypsarrhythmia assessment exhibits poor interrater reliability: a threat to clinical trial validity","volume":"56","author":"Hussain","year":"2015"},{"key":"b26","series-title":"Epilepsia Open","first-page":"176","article-title":"Interrater reliability of interictal EEG waveforms in Lennox\u2013Gastaut Syndrome","volume":"9","author":"Hu","year":"2024"},{"key":"b27","series-title":"Epilepsy Res","first-page":"93","article-title":"Improving the inter-rater agreement of hypsarrhythmia using a simplified EEG grading scale for children with infantile spasms","volume":"116","author":"Mytinger","year":"2015"},{"key":"b28","series-title":"Epilepsy Behav","first-page":"102","article-title":"EEG interpretation reliability and interpreter confidence: A large single-center study","volume":"32","author":"Grant","year":"2014"},{"key":"b29","series-title":"Neurology","first-page":"843","article-title":"Interrater reliability of EEG-video monitoring","volume":"73","author":"Benbadis","year":"2009"},{"key":"b30","series-title":"Neurology","first-page":"e1737","article-title":"Interrater reliability of expert electroencephalographers identifying seizures and rhythmic and periodic patterns in EEGs","volume":"100","author":"Jing","year":"2023"},{"key":"b31","series-title":"JAMA 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study","volume":"13","author":"Ray","year":"2025"},{"key":"b6","series-title":"Am J Trop Med Hyg","first-page":"809","article-title":"Using electroencephalography to assess coma etiology in children with retinopathy-negative cerebral malaria","volume":"113","author":"Takle","year":"2025"},{"key":"b7","series-title":"Neurocrit Care","first-page":"618","article-title":"Review of noninvasive neuromonitoring modalities in children II: EEG, qEEG","volume":"39","author":"Benedetti","year":"2023"},{"key":"b8","series-title":"Arch Dis Child","first-page":"343","article-title":"Continuous EEG monitoring in Kenyan children with non-traumatic coma","volume":"97","author":"Gwer","year":"2012"},{"key":"b9","series-title":"Neurology","first-page":"e1307","article-title":"Admission clinical and EEG features associated with mortality and long-term neurologic and cognitive outcomes in pediatric cerebral malaria","volume":"101","author":"Clark","year":"2023"},{"key":"b10","series-title":"Malar J","first-page":"208","article-title":"Admission EEG findings in diverse paediatric cerebral malaria populations predict outcomes","volume":"17","author":"Postels","year":"2018"},{"key":"b11","series-title":"Pediatr Neurol","first-page":"96","article-title":"Using EEG in resource-limited areas: Comparing qualitative and quantitative interpretation methods in cerebral malaria","volume":"126","author":"Andrews","year":"2022"},{"key":"b12","series-title":"J Clin Neurophysiol","first-page":"136","article-title":"Theta-alpha variability on admission EEG is associated with outcome in pediatric cerebral malaria","volume":"40","author":"Andrews","year":"2023"},{"key":"b13","series-title":"Epilepsy Behav","first-page":"107536","article-title":"EEG markers predictive of epilepsy risk in pediatric cerebral malaria\u2014A feasibility study","volume":"113","author":"Patel","year":"2020"},{"key":"b14","series-title":"Epilepsia","first-page":"2955","article-title":"Periodic and rhythmic patterns in 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assessment exhibits poor interrater reliability: A threat to clinical trial validity","volume":"56","author":"Hussain","year":"2015"},{"key":"b19","series-title":"J Clin Neurophysiol","first-page":"230","article-title":"A multicenter training and interrater reliability study of the BASED score for infantile epileptic spasms syndrome","volume":"42","author":"Mytinger","year":"2025"},{"key":"b20","series-title":"Epileptic Disord","first-page":"827","article-title":"Unveiling variability: A systematic review of reproducibility in visual EEG analysis, with focus on seizures","volume":"26","author":"Aanestad","year":"2024"},{"key":"b21","series-title":"J Clin Neurophysiol","first-page":"1","article-title":"American Clinical Neurophysiology Society\u2019s standardized critical care EEG terminology: 2021 version","volume":"38","author":"Hirsch","year":"2021"},{"key":"b22","series-title":"J Clin Neurophysiol","first-page":"15","article-title":"Interobserver reproducibility of 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