Abnormal cortical activity in postoperative delirium based on EEG microstate: a cross-sectional study

Abstract

Abstract Objective This study aims to investigate the characteristics of resting-state electroencephalogram (EEG) microstate in elderly postoperative delirium patients and non-delirium patients, to increase understanding of the pathophysiology and phenomenology of postoperative delirium. Methods Resting-state EEG data and clinically relevant information were collected from 10 postoperative delirium patients and 18 postoperative non-delirium patients. The EEG microstate characteristic parameters of the two groups were compared, and Pearson analysis was used to analyze the correlation between the microstate characteristic parameters of the delirium group and the maximal concentration of intraoperative blood glucose. Results Intergroup comparisons of microstate characterization parameters found that microstate D duration was significantly higher in the delirium group than in the non-delirium group (P< 0.05), whereas frequency of occurrence and temporal coverage were significantly lower than in the non-delirium group (P< 0.05). Within-group comparisons of microstate feature parameters found that microstate D duration was prolonged and frequency of occurrence and temporal coverage decreased in the delirium group. A comparison of microstate transition characteristics found significant differences between the two groups for transitions from microstate B to microstate D, from microstate C to microstate B, and from microstate D to microstate B (P < 0.05). Correlation analysis found a significant positive correlation between intraoperative maximal blood glucose and the frequency of occurrence (P = 0.01) and temporal coverage (P = 0.006) of microstate C. Conclusions Our results suggest that postoperative delirium has an impact on the EEG microstates during the resting-state. Changes in these microstates may be associated with altered cognition and consciousness in individuals experiencing delirium. Therefore, EEG microstate analysis holds potential clinical value for predicting and aiding in the diagnosis of postoperative delirium.