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Summary: Background: Epileptiform activity is associated with worse patient outcomes, including increased risk of disability and death. However, the effect of epileptiform activity on neurological outcome is confounded by the feedback between treatment with antiseizure medications and epileptiform activity burden. We aimed to quantify the heterogeneous effects of epileptiform activity with an interpretability-centred approach. Methods: We did a retrospective, cross-sectional study of patients in the intensive care unit who were admitted to Massachusetts General Hospital (Boston, MA, USA). Participants were aged 18 years or older and had electrographic epileptiform activity identified by a clinical neurophysiologist or epileptologist. The outcome was the dichotomised modified Rankin Scale (mRS) at discharge and the exposure was epileptiform activity burden defined as mean or maximum proportion of time spent with epileptiform activity in 6 h windows in the first 24 h of electroencephalography. We estimated the change in discharge mRS if everyone in the dataset had experienced a specific epileptiform activity burden and were untreated. We combined pharmacological modelling with an interpretable matching method to account for confounding and epileptiform activity–antiseizure medication feedback. The quality of the matched groups was validated by the neurologists. Findings: Between Dec 1, 2011, and Oct 14, 2017, 1514 patients were admitted to Massachusetts General Hospital intensive care unit, 995 (66%) of whom were included in the analysis. Compared with patients with a maximum epileptiform activity of 0 to less than 25%, patients with a maximum epileptiform activity burden of 75% or more when untreated had a mean 22·27% (SD 0·92) increased chance of a poor outcome (severe disability or death). Moderate but long-lasting epileptiform activity (mean epileptiform activity burden 2% to

IMPORTANCE:. The clinical significance of epileptiform abnormalities (EAs) specific to toxic-metabolic encephalopathy (TME) is unknown. OBJECTIVES:. To quantify EA burden in patients with TME and its association with neurologic outcomes. DESIGN, SETTING, AND PARTICIPANT:. This is a retrospective study. A cohort of patients with TME and EA (positive) were age, Sequential Organ Failure Assessment Score, Acute Physiology and Chronic Health Evaluation II (APACHE-II) score matched to a cohort of TME patients without EA (control). Univariate analysis compared EA-positive patients against controls. Multivariable logistical regression adjusting for underlying disease etiology was performed to examine the relationship between EA burden and probability of poor neurologic outcome (modified Rankin Score [mRS] 4–6) at discharge. Consecutive admissions to inpatient floors or ICUs that underwent continuous electroencephalography (cEEG) monitoring at a single center between 2012 and 2019. Inclusion criteria were 1) patients with TME diagnosis, 2) age greater than 18 years, and 3) greater than or equal to 16 hours of cEEG. Patients with acute brain injury and cardiac arrest were excluded. MAIN OUTCOMES AND MEASURES:. Poor neurologic outcome defined by mRS (mRS 4–6). RESULTS:. One hundred sixteen patients were included, 58 with EA and 58 controls without EA, where matching was performed on age and APACHE-II score. The median age was 66 (Q1–Q3, 57–75) and median APACHE II score was 18 (Q1–Q3, 13–22). Overall cohort discharge mortality was 22% and 70% had a poor neurologic outcome. Peak EA burden was defined as the 12-hour window of recording with the highest prevalence of EAs. In multivariable analysis adjusted for Charlson Comorbidity Index and primary diagnosis, presence of EAs was associated with poor outcome (odds ratio 3.89; CI [1.05–14.2], p = 0.041). Increase in peak EA burden from 0% to 100% increased probability of poor discharge neurologic outcome by 30%. CONCLUSIONS AND RELEVANCE:. Increasing burden of EA is associated with worse discharge outcomes in patients with TME. Future studies are needed to determine whether short-term treatment with anti-seizure medications while medically treating the underlying metabolic derangement improves outcomes.

OBJECTIVES:. 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. DESIGN:. This prospective, single-center, observational cohort study was conducted from August 2015 to December 2016 and October 2018 to December 2019. SETTING:. Academic 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. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. A 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]; p < 0.001) and showed excellent discrimination between levels of delirium (CAM-S LF = 0 vs ≥ 4, AUC 0.85 [0.78–0.92], calibration slope of 1.04 [0.87–1.19] for CAM-S LF ≤ 4 vs ≥ 5). VE-CAM-S scores were strongly associated with important clinical outcomes including inhospital mortality (AUC 0.79 [0.72–0.84]), 3-month mortality (AUC 0.78 [0.71–0.83]), and GOS at discharge (0.76 [0.69–0.82]). CONCLUSIONS:. VE-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.