Quantitative electroencephalography predicts postoperative delirium in adult cardiac surgical patients from a prospective observational study.

The diagnostic and prognostic value of quantitative electroencephalogram (qEEG) in the the onset of postoperative delirium (POD) remains an area of inquiry. We aim to determine whether qEEG could assist in the diagnosis of early POD in cardiac surgery patients. We prospectively studied a cohort of cardiac surgery patients undergoing qEEG for evaluation of altered mental status. Delirium was assessed with the Confusion Assessment Method for the intensive care unit (CAM-ICU). The qEEG were interpreted by clinician, and reports were reviewed to identify features such as amplitude-integrated EEG (aEEG), relative band energy in ɑ/β/θ/δ frequencies, α variability and spectral entropy. The raw EEG was also preprocessed offline for nonlinear analysis including Multi-scale Entropy analysis (MSE) and Detrended Fluctuation Analysis (DFA). Linear regression was performed to quantify associations among EEG findings, delirium, and clinical outcomes. Receiver operating characteristic (ROC) analysis was used to assess the accuracy of the qEEG as POD prediction index. Meanwhile, a comprehensive comparison of dynamic complexity across time scales and DFA exponent α was conducted between the non-delirium and delirium groups. Among those recruited initially (n = 64), 60 patients were evaluated and 29 patients (48.3%) met delirium criteria. When comparing delirious and non-delirious participants, significant differences were found in terms of age (p = 0.03), APACHE II scores (p = 0.004), lactate (p = 0.03), and hospital days (p = 0.048). Multivariate regression analysis revealed that the first quartile (Q1) and fourth quartile (Q4) of peak or valley value of F3-P3/F4-P4 derivation (for example, Q1 of peak value for F3-P3 derivation: OR 12.4, 95% CI 1.72-89.76, p = 0.012) showed a higher association with the incidence of POD. ROC analysis demonstrated qEEG could predict POD with high sensitivity and specificity, yielding an overall good accuracy. For instance, the peak value of F3-P3 derivation (the area under the curve of 0.81), as a predictor of POD showed a sensitivity of 90% and specificity pf 72% (p < 0.001). Furthermore, the MSE curves indicated that the non-delirium group exhibited higher complexity values at fine scales, while the delirium group had significantly higher complexity at coarse scales. The DFA comparison results revealed that long-term fractal exponent alpha2 values were higher in delirium patients than in non-delirium patients, with significant differences observed at the F4-P4 electrodes (p = 0.04). The qEEG can reliably predict delirium after heart cardiac surgery. It is helpful for clinicians to early diagnose and manage these patients.Trial registration: Clinical Trials.gov Identifier, NCT03351985. Registered 1 December 2017.