ID 145 – NeuroTrend: Prospective validation of rhythmic and periodic pattern detection method for Scalp

Abstract

NeuroTrend is a computational method that automatically analyses long-term scalp EEGs in the ICU according to ACNS standardized critical care EEG terminology (CCET). At present, it is a screening aid to facilitate the review process and optimize resources. A prospective multi-center study was performed in two neuro-ICUs including 68 patients who were subjected to continuous video-EEG (cEEG). Two reviewers independently annotated the first minute of each hour in the cEEG according to CCET and electrographic seizures. The matching annotations (2911 segments) were then used as gold standard condition to test sensitivity and specificity of the rhythmic and periodic pattern detection of NeuroTrend. Inter-rater agreement was substantial for main term 1 and main term 2 of the CCET. The overall detection sensitivity of NeuroTrend was 94% with high detection rates for periodic discharges (PD 81%) and rhythmic delta activity (RDA 82%). The overall specificity was 67% due to false positive detections of RDA in cases of general slowing. In contrast, for PDs a detection specificity of 88% was reached. NeuroTrend is suitable as a screening tool for cEEG in the ICU and will raise the efficiency of long-term EEG-monitoring in the ICU. Pattern differentiation between RDA and general slowing still needs improvement.