ArticleCritical care explorations2022
VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes.
Article in Critical care explorations, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Resting-state EEG for continuous prognostic monitoring and prediction of coma recovery after acute brain injury.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026Article
- Predicting delirium in critically Ill COVID-19 patients using EEG-derived data: a machine learning approach.GeroScience · 2026Observational
- Delirium versus encephalopathy: a call for precise terminology.Intensive care medicine · 2026Article
- Inter-Rater Reliability of EEG-Based Encephalopathy Grading.Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society · 2026Article
- Electrographic Features of Catatonia With or Without Comorbid Delirium.The Journal of neuropsychiatry and clinical neurosciences · 2026Article
- Bedside EEG for rapid diagnosis of delirium.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026Review
- Associations between anaesthetic dose-adjusted intraoperative EEG alpha power, processing speed, and postoperative delirium: analysis of data from three prospective studies.British journal of anaesthesia · 2025Article
- Prevalence of clinical electroencephalography findings in stroke patients with delirium.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2024Article
- Electroencephalography as a tool for assessing delirium in hospitalized patients: A single-center tertiary hospital experience.Journal of central nervous system disease · 2024Article
- Automated detection of immune effector cell-associated neurotoxicity syndrome via quantitative EEG.Annals of clinical and translational neurology · 2023Observational
- EEG-based grading of immune effector cell-associated neurotoxicity syndrome.Scientific reports · 2022Observational
- Machine-learning model predicting postoperative delirium in older patients using intraoperative frontal electroencephalographic signatures.Frontiers in aging neuroscience · 2022Article
- Postoperative delirium in geriatric patients with hip fractures.Frontiers in aging neuroscience · 2022Review
- Requesting That Delirium Achieve Parity With Acute Encephalopathy in the MS-DRG System.Journal of the Academy of Consultation-Liaison PsychiatryArticle
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
To develop a physiologic grading system for the severity of acute encephalopathy manifesting as delirium or coma, based on EEG, and to investigate its association with clinical outcomes.
designThis prospective, single-center, observational cohort study was conducted from August 2015 to December 2016 and October 2018 to December 2019.
settingAcademic medical center, all inpatient wards. PATIENTS/SUBJECTS: Adult inpatients undergoing a clinical EEG recording; excluded if deaf, severely aphasic, developmentally delayed, non-English speaking (if noncomatose), or if goals of care focused primarily on comfort measures. Four-hundred six subjects were assessed; two were excluded due to technical EEG difficulties.
interventionsNone. MEASUREMENTS AND MAIN
resultsA machine learning model, with visually coded EEG features as inputs, was developed to produce scores that correlate with behavioral assessments of delirium severity (Confusion Assessment Method-Severity [CAM-S] Long Form [LF] scores) or coma; evaluated using Spearman R correlation; area under the receiver operating characteristic curve (AUC); and calibration curves. Associations of Visual EEG Confusion Assessment Method Severity (VE-CAM-S) were measured for three outcomes: functional status at discharge (via Glasgow Outcome Score [GOS]), inhospital mortality, and 3-month mortality. Four-hundred four subjects were analyzed (mean [sd] age, 59.8 yr [17.6 yr]; 232 [57%] male; 320 [79%] White; 339 [84%] non-Hispanic); 132 (33%) without delirium or coma, 143 (35%) with delirium, and 129 (32%) with coma. VE-CAM-S scores correlated strongly with CAM-S scores (Spearman correlation 0.67 [0.62-0.73];
conclusionsVE-CAM-S is a physiologic grading scale for the severity of symptoms in the setting of delirium and coma, based on visually assessed electroencephalography features. VE-CAM-S scores are strongly associated with clinical outcomes.
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