Predictors of Low Risk for Delirium during Anesthesia Emergence.

Abstract

Processed 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. In this article we describe 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. We included data from 169 patients (median age: 61 [49, 73]), who underwent surgery with general anesthesia, maintained either with propofol, sevoflurane, or desflurane. The data were derived from a previously published study. We chose a single frontal channel and 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. Of 169 patients, 32 (19%) showed delirium. We observed that patients whose total EEG power diminished the most during emergence were less likely to screen positive for delirium in the PACU. A positive slope in total power and band power evaluated by using a regression model was associated with a higher risk-ratio (total: RR 2.83 (95%CI: 1.46 to 5.51) alpha/beta band: RR 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 to define a test for patients at low risk. In this study we 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.