Prognostic significance of EEG patterns in post-cardiac arrest coma: a 1,000-patient multicenter cohort

Résumé fourni par la source

**Objective.** To quantify the prognostic significance of continuous-EEG (cEEG) patterns for outcome in comatose survivors of cardiac arrest, and how that prognostic value evolves over the first 72 hours, in a large multicenter cohort. **Methods.** Retrospective multicenter cohort of 1,000 comatose post-cardiac- arrest patients undergoing cEEG. For each EEG pattern and time window (24, 48, 72 hours, and the remainder), true-positive and false-positive rates and predictive values for poor outcome (Cerebral Performance Category at discharge) were computed with exact Clopper-Pearson 95% confidence intervals, and temporal trends were assessed by linear regression (significance at α=0.05). **Results.** The dataset and code reproduce the per-pattern prognostic statistics and their temporal trends, identifying which EEG patterns carry reliable (low false-positive) prognostic information and how this changes over time. This project provides the de-identified 1,000-patient dataset (linked to BDSP patient IDs) and the analysis code.

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