• Erik Westhall, Ingmar Rosén, Andrea O Rossetti, Anne-Fleur van Rootselaar, Troels Wesenberg Kjaer, Hans Friberg, Janneke Horn, Niklas Nielsen, Susann Ullén, and Tobias Cronberg.
• Department of Clinical Sciences, Division of Clinical Neurophysiology, Lund University, Lund, Sweden. Electronic address: erik.westhall@med.lu.se.
• Clin Neurophysiol. 2015 Dec 1; 126 (12): 2397-404.

ObjectiveEEG is widely used to predict outcome in comatose cardiac arrest patients, but its value has been limited by lack of a uniform classification. We used the EEG terminology proposed by the American Clinical Neurophysiology Society (ACNS) to assess interrater variability in a cohort of cardiac arrest patients included in the Target Temperature Management trial. The main objective was to evaluate if malignant EEG-patterns could reliably be identified.MethodsFull-length EEGs from 103 comatose cardiac arrest patients were interpreted by four EEG-specialists with different nationalities who were blinded for patient outcome. Percent agreement and kappa (κ) for the categories in the ACNS EEG terminology and for prespecified malignant EEG-patterns were calculated.ResultsThere was substantial interrater agreement (κ 0.71) for highly malignant patterns and moderate agreement (κ 0.42) for malignant patterns. Substantial agreement was found for malignant periodic or rhythmic patterns (κ 0.72) while agreement for identifying an unreactive EEG was fair (κ 0.26).ConclusionsThe ACNS EEG terminology can be used to identify highly malignant EEG-patterns in post cardiac arrest patients in an international context with high reliability.SignificanceThe establishment of strict criteria with high transferability between interpreters will increase the usefulness of routine EEG to assess neurological prognosis after cardiac arrest.Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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