Constructing a Model of Pupillary Parameters in Predicting Delirium Among Critically Ill Patients in the Intensive Unit

Delirium is commonly observed in critically ill patients in intensive care units (ICUs), imposing significant burdens on both patients and the healthcare system. Existing assessment tools have certain limitations. Studies have indicated a correlation between pupil parameters and neurological disorders including delirium. Automated Infrared Pupillometry, widely used in neurological disorders, is employed in this study to assess its accuracy and predictive power in evaluating delirium among critically ill patients. The aim is to investigate the accuracy and predictive capability of these parameters in assessing delirium, while identifying the optimal cut-off points. The research findings will contribute to enhancing early detection and prevention of delirium in ICU settings.

Delirium is an acute impairment of attention and cognitive function commonly observed in critically ill patients in intensive care units (ICUs). It leads to long-term cognitive impairment and increased risk of mortality for patients, while also causing distress for healthcare providers and family members, imposing substantial burdens on patients, families, and healthcare systems. Although there are assessment tools and predictive models available for detecting delirium, they have certain limitations. Recent studies have indicated an association between delirium and the neurotransmitter acetylcholine (ACh). Acetylcholine not only regulates consciousness and cognitive wakefulness but also modulates pupil constriction and light reflex. In clinical practice, the Automated Infrared Pupillometry (AIP) has emerged as a robust tool for assessing acetylcholine, aiding in early delirium detection. However, more research is needed to clearly establish their relationship. This study aims to investigate the accuracy and predictive power of Automated Infrared Pupillometry in assessing delirium among critically ill patients. It involves collecting pupil parameters from critically ill patients and examining the correlation between delirium and pupil parameters using the Intensive Care Delirium Screening Checklist (ICDSC). The goal is to explore the accuracy and predictive capability of these parameters in evaluating delirium, identifying optimal cut-off points. The findings will contribute to enhancing early detection and prevention of delirium in intensive care settings.