Quantitative electroencephalography predicts postoperative delirium in cardiac surgical patients after cardiopulmonary bypass: a prospective observational study - Xue, Yuechuan; Liu, Wanglin; Su, Longxiang; He, Huaiwu; Chen, Huan; Long, Yun (Frontiers in Medicine, 2023)
Objective: Despite its frequency and negative impact, delirium is poorly recognized in postoperative patients after ICU admission, especially in cardiac surgical patients after cardiopulmonary bypass. Postoperative delirium is triggered by a wide variety of acute medical conditions, associated with impaired neuronal network connectivity. The lack of objective biomarkers is the primary cause of delirium early detection. Seeking early biomarkers for tracking POD could potentially assist predicting the onset of delirium and assessing severity of delirium and response to interventions.Methods: QEEGs were recorded in 46 postoperative patients under sedation, of whom 24 had undergone cardiac surgery. Assessment of delirium was performed twice a day to screen for postoperative delirium (POD) using the Confusion Assessment Method for the ICU (CAM-ICU). QEEG data were interpreted clinically by neurophysiologists and processed by open-source EEGLAB to identify features in patients who had or did not have POD after cardiac or non-cardiac surgery.The delirium incidence of post cardiac surgical patients was nine times higher than post non-cardiac surgical patients (41.7% vs. 4.5%; p=0.0046). Patients with delirium had longer duration of mechanical ventilation use (118 hours (78,323) vs. 20 hours (18,23); p<0.0001) and ICU length of stay (7 days (6, 20) vs. 2 days (2, 4); p<0.0001). There was no difference in the depth of anesthesia accessed by RASS scores (p=0.3114) and spectral entropy (p=0.1504). The amplitude-integrated EEG (aEEG) upper limit, the relative power of delta band, and spectral edge frequency 95 (SEF95) showed a statistically significant difference (p=0. 0464, p=0.0417, p=0.0337, respectively) between delirious and non-delirious patients.In a homogenous population of sedated postoperative patients, identified robust qEEG parameters strongly correlated with delirium and could serve as valuable biomarkers for early detection of delirium and assist clinical decision-making.