Application of a standardized EEG pattern classification in the assessment of neurological prognosis after cardiac arrest: A retrospective analysis

IntroductionElectroencephalogram (EEG) is used in the neurological prognostication after cardiac arrest. “Highly malignant” EEG patterns classified according to Westhall have a high specificity for poor outcome when applied within protocols of recent studies. However, their predictive performance everyday clinical practice has not been investigated. We studied prognostic accuracy and interrater agreement standardized were analysed compared patient cohort at tertiary centre involved original study pattern classification.MethodsComatose patients treated out-of-hospital arrest included. Poor was defined as Cerebral Performance Category 3–5. Two senior consultants one resident neurophysiology, blinded data outcome, independently reviewed registrations categorised “highly malignant”, “malignant” or “benign”. These categories hospital discharge. Interrater assessed using Cohen’s Kappa.ResultsIn total, 62 The median (IQR) time 59 (42–91) h return spontaneous circulation. found 52 (84%) patients. In 21 least raters considered contain pattern, all with (42% sensitivity, 100% specificity). varied from kappa 0.62 0.29.Conclusion“Highly predict practice. may vary substantially even between experienced interpreters.