F78. Standardized EEG interpretation after ACNS nomenclature in patients after cardiac arrest: Correlation with other prognostic predictors. (May 2018)

• Record Type: Journal Article
• Authors: Beuchat, Isabelle; Solari, Daria; Novy, Jan; Oddo, Mauro; Rossetti, Andrea O.
• Is Part Of: Clinical neurophysiology. Volume 129(2018)Supplement 1
• Page Start: e96
• Publication Date: 2018-05
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2018.04.241
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Introduction: Standardized EEG patterns ("highly malignant", "malignant" and "benign") have been recently defined according to the current American Clinical Neurophysiology Society (ACNS) nomenclature, demonstrating a good correlation with poor and good outcome in patients after cardiac arrest (CA). However, this approach has been described only in patients receiving EEG after target temperature management (TTM), and the relationship to other widely used outcome predictors remains unknown. The aim of this study was to investigate the relationship between categorized EEG and other outcome predictors, during and after TTM, and under different temperature targets. Methods: We analyzed a prospective adult CA registry between January 2014 and June 2017. EEG at day 1 and 2 after CA were classified into pre-defined categories of "highly malignant" or "benign". Correlation between EEG categories and other clinical, (brainstem reflexes including automated pupillometry, early myoclonus), biochemical (peak serum NSE), and neurophysiological (SSEP) outcome predictors, and functional outcome at three months (Cerebral Performance Categories -CPC 1–2: good outcome, CPC 3–5: poor outcome) were assessed. Results: We studied 203 CA episodes corresponding to 202 patients; 31.5% were treated targeting 33 °C, 60.6% targeting 36 °C, and 7.9% had spontaneous temperature. "Highly malignant" EEG patterns were found in 36.7% at day 1 and in 21.7% at day 2, while 19.2% presented "benign" EEG at day 1, and 33.2% at day 2. "Highly malignant" EEG patterns predicted poor prognosis with 91% (95%CI: 83–97%) specificity and 63% sensitivity (95% CI: 53–72%). "Benign" EEG sensitivity to predict good prognosis was 35% (25%CI 26–46%), with 89% (75–97%) positive predictive value. "Highly malignant" and "benign" patterns showed a robust correlation with all predictors of prognosis ( p < 0.007 in each, apart from "benign" EEG and automated pupillometry). Results were similar between EEGs recorded at day 1 or day 2, and across TTM targets. Conclusion: Standardized EEG categorization after CA shows strong correlations with other outcome predictors, without major variation across EEG recording time or TTM target, underscoring their prognostic role in a multimodal approach.