Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis

Objective: In critical care, continuous EEG (cEEG) monitoring is useful for delirium diagnosis. Although visual cEEG analysis is most commonly used, automatic cEEG analysis has shown promising results in small samples. Here we aimed to compare visual versus automatic cEEG analysis for delirium diagnosis in septic patients. Methods: We obtained cEEG recordings from 102 septic patients who were scored for delirium six times daily. A total of 1252 cEEG blocks were visually analyzed, of which 805 blocks were also automatically analyzed. Results: Automatic cEEG analyses revealed that delirium was associated with 1) high mean global field power (p < 0.005), mainly driven by delta activity; 2) low average coherence across all electrode pairs and all frequencies (p < 0.01); 3) lack of intrahemispheric (fronto-temporal and temporo-occipital regions) and interhemispheric coherence (p < 0.05); and 4) lack of cEEG reactivity (p < 0.005). Classification accuracy was assessed by receiver operating characteristic (ROC) curve analysis, revealing a slightly higher area under the curve for visual analysis (0.88) than automatic analysis (0.74) (p < 0.05). Conclusions: Automatic cEEG analysis is a useful supplement to visual analysis, and provides additional cEEG diagnostic classifiers. Significance: Automatic cEEG analysis provides useful information in septic patients. (C) 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Automated summary

This study compared visual and automatic cEEG analysis for delirium diagnosis in septic patients. Automatic cEEG analysis revealed delirium-related features, but visual analysis had slightly higher classification accuracy. Automatic cEEG analysis provides additional information for delirium diagnosis.