Automated pupillometry for detection of delirium in surgical intensive care patients.

Background: Delirium is a frequent and serious complication in critically ill patients and associated with adverse outcomes. Automated pupillometry has emerged as a potential diagnostic tool for the detection of delirium. However, pupillometric parameters are also influenced by pain, potentially confounding their relationship to delirium. The aim of this study was to evaluate the association between automated pupillometry parameters and delirium in patients with high risk of pain (surgical patients) admitted to intensive care units (ICU). Methods: This prospective multicenter observational study included adult surgical patients admitted to an ICU between April 2023 and August 2025. Delirium was assessed every 6 h after admission using CAM-ICU. Automated pupillometry together with pain intensity scores (VAS, CPOT, BPS) were performed concurrent with CAM-ICU. To account for repeated measurements within individual patients, a generalized linear mixed-effects model (GLMM) with patient as a random effect was used to evaluate the association between pupillometric parameters and diagnosed delirium. Results: Forty-nine patients were included, yielding 417 measurements, of which 48 (12%) were done in patients who were simultaneously CAM-ICU positive. Among pupillometric variables, only average pupillary latency (LAT avg) was significantly shorter in patients with delirium ( Conclusion: In surgical ICU patients, shortened pupillary light reflex latency is associated with delirium. Automated pupillometry may serve as a useful tool for detection of delirium in this population. Clinical trial registration: https://clinicaltrials.gov/study/ Identifier: NCT05811208.