Background: Postoperative delirium is associated with an increased risk of morbidity and mortality, especially in the elderly. Delirium in the postanaesthesia care unit (PACU) could predict adverse clinical outcomes. Methods: We investigated a potential link between intraoperative EEG patterns and PACU delirium as well as an association of PACU delirium with perioperative outcomes, readmission and length of hospital stay. The risk factors for PACU delirium were also explored. Data were collected from 626 patients receiving general anaesthesia for procedures that would not interfere with frontal EEG recording. Results: Of the 626 subjects enrolled, 125 tested positive for PACU delirium. Whilst age, renal failure, and pre-existing neurological disease were associated with PACU delirium in the univariable analysis, the multivariable analysis revealed the importance of information derived from the EEG, anaesthetic technique, anaesthesia duration, and history of stroke or neurodegenerative disease. The occurrence of EEG burst suppression during maintenance [odds ratio (OR)¼1.86 (1.13e3.05)] and the type of EEG emergence trajectory may be predictive of PACU delirium. Specifically, EEG emergence trajectories lacking significant spindle power were strongly associated with PACU delirium, especially in cases that involved ketamine or nitrous oxide [OR¼6.51 (3.00e14.12)]. Additionally, subjects with PACU delirium were at an increased risk for readmission [OR¼2.17 (1.13e4.17)] and twice as likely to stay >6 days in the hospital.Conclusions: Specific EEG patterns were associated with PACU delirium. These findings provide valuable information regarding how the brain reacts to surgery and anaesthesia that may lead to strategies to predict PACU delirium and identify key areas of investigation for its prevention.

This study evaluates the capability of pupillary parameters to detect and predict delirium in the post-anesthesia care unit (PACU-D) following general anesthesia. PACU-D may complicate and prolong the patient's postoperative course, consequently increasing hospital costs. After institutional approval, 47 patients undergoing surgical interventions with general anesthesia were included in the study. We measured the pupillary reflexes at signing of informed consent, during surgery 20 min after intubation and when the primary inhaled anesthetic was turned off, and 15 and 45 min after PACU admittance and upon discharge from the PACU. We evaluated patients for delirium using the confusion assessment method for the intensive care unit (CAM-ICU) score after 15 and 60 min in the PACU. We chose receiver operating curve (ROC) and area under the curve (AUC) to compare the performance of non-pupillary parameters to pupillary parameters, such as pupil diameter, percent constriction, and dilation velocity, to detect and predict PACU-D. Percent constriction (AUC = 0.93, optimal threshold = 18.5%) and dilation velocity (AUC = 0.93, optimal threshold = 0.35 mm/s) showed excellent ability to detect and predict delirium persisting throughout the PACU stay. These pupillary measures showed superior performance compared to other pupillary measures and features commonly associated with delirium, e.g., age (AUC = 0.73), total opioids (AUC = 0.56), or length of surgery (AUC = 0.40). Our results suggest that pupillometry and the parameters derived from the recording may identify delirious patients in the PACU. This information can help to efficiently structure their care in a timely manner, and potentially avoid adverse complications for the patient and financial consequences for the hospital.