Objective: To assess the value of background continuity and amplitude fluctuations of the EEG for the prediction of outcome of comatose patients after cardiac arrest.
Methods: In a prospective cohort study, we analyzed EEGs recorded in the first 72 h after cardiac arrest. We defined the background continuity index (BCI) as the fraction of EEG not spent in suppressions (amplitudes < 10 µV for ≥ 0.5 s), and the burst-suppression amplitude ratio (BSAR) as the mean amplitude ratio between non-suppressed and suppressed segments. Outcome was assessed at 6 months and categorized as "good" (Cerebral Performance Category 1-2) or "poor" (CPC 3-5).
Results: Of the 559 patients included, 46% had a good outcome. Combinations of BCI and BSAR resulted in the highest prognostic accuracies. Good outcome could be predicted at 24 h with 57% sensitivity (95% confidence interval (CI): 48-67) at 90% specificity (95%-CI: 86-95). Poor outcome could be predicted at 12 h with 50% sensitivity (95%-CI: 42-56) at 100% specificity (95%-CI: 99-100).
Conclusions: EEG background continuity and the amplitude ratio between bursts and suppressions reliably predict the outcome of postanoxic coma.
Significance: The presented features provide an objective, rapid, and reliable tool to assist in EEG interpretation in the Intensive Care Unit.
Keywords: Background continuity; Burst-suppression; Electroencephalography; Generalized periodic discharges; Postanoxic encephalopathy; Quantitative EEG.
Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.