Monitoring burst suppression in critically ill patients: Multi-centric evaluation of a novel method

Publication date: Available online 9 February 2016
Source:Clinical Neurophysiology
Author(s): Franz Fürbass, Johannes Herta, Johannes Koren, M. Brandon Westover, Manfred M. Hartmann, Andreas Gruber, Christoph Baumgartner, Tilmann Kluge
ObjectiveTo develop a computational method to detect and quantify burst suppression patterns (BSP) in the EEGs of critical care patients. A multi-center validation study was performed to assess the detection performance of the method.MethodsThe fully automatic method scans the EEG for discontinuous patterns and shows detected BSP and quantitative information on a trending display in real-time. The method is designed to work without setting any patient specific parameters and to be insensitive to EEG artifacts and periodic patterns. For validation a total of 3982 hours of EEG from 88 patients were analyzed from three centers. Each EEG was annotated by two reviewers to assess the detection performance and the inter-rater agreement.ResultsAverage inter-rater agreement between pairs of reviewers was κ=0.69. On average 22% of the review segments included BSP. An average sensitivity of 90% and a specificity of 84% were measured on the consensus annotations of two reviewers. More than 95% of the periodic patterns in the EEGs were correctly suppressed.ConclusionA fully automatic method to detect burst suppression patterns was assessed in a multi-center study. The method showed high sensitivity and specificity.SignificanceClinically applicable burst suppression detection method validated in a large multi-center study.



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