• Srdjan Dragovic, Gerhard Schneider, Paul S García, Dominik Hinzmann, Jamie Sleigh, Stephan Kratzer, and Matthias Kreuzer.
• Department for Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany.
• Anesthesiology. 2023 Dec 1; 139 (6): 757768757-768.

BackgroundProcessed electroencephalography (EEG) is used to monitor the level of anesthesia, and it has shown the potential to predict the occurrence of delirium. While emergence trajectories of relative EEG band power identified post hoc show promising results in predicting a risk for a delirium, they are not easily transferable into an online predictive application. This article describes a low-resource and easily applicable method to differentiate between patients at high risk and low risk for delirium, with patients at low risk expected to show decreasing EEG power during emergence.MethodsThis study includes data from 169 patients (median age, 61 yr [49, 73]) who underwent surgery with general anesthesia maintained with propofol, sevoflurane, or desflurane. The data were derived from a previously published study. The investigators chose a single frontal channel, calculated the total and spectral band power from the EEG and calculated a linear regression model to observe the parameters' change during anesthesia emergence, described as slope. The slope of total power and single band power was correlated with the occurrence of delirium.ResultsOf 169 patients, 32 (19%) showed delirium. Patients whose total EEG power diminished the most during emergence were less likely to screen positive for delirium in the postanesthesia care unit. A positive slope in total power and band power evaluated by using a regression model was associated with a higher risk ratio (total, 2.83 [95% CI, 1.46 to 5.51]; alpha/beta band, 7.79 [95% CI, 2.24 to 27.09]) for delirium. Furthermore, a negative slope in multiple bands during emergence was specific for patients without delirium and allowed definition of a test for patients at low risk.ConclusionsThis study developed an easily applicable exploratory method to analyze a single frontal EEG channel and to identify patterns specific for patients at low risk for delirium.Copyright © 2023 American Society of Anesthesiologists. All Rights Reserved.

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