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

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

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06187792
Enrollment
200
Registered
2024-01-03
Start date
2023-10-04
Completion date
2025-09-30
Last updated
2024-01-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

ICU Delirium

Keywords

Delirium, Predicting delirium, Automated Infrared Pupillometry (AIP), Pupil Parameters, Intensive Care Delirium Screening Checklist (ICDSC)

Brief summary

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.

Detailed description

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.

Interventions

None listed

Sponsors

National Taiwan University Hospital
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Patients admitted to the intensive care unit from internal and surgical departments. * Ages 18 and above.

Exclusion criteria

* Acute brain injury (hemorrhagic, ischemic stroke). * Other brain-related diseases (brain tumor, brain infection, oculomotor nerve paralysis, etc.). * Ophthalmic diseases that prevent monitoring of pupil measurements. * Patients with pre-hospital cardiac arrest or in-hospital cardiac arrest. * Estimated stay in the intensive care unit not exceeding 72 hours. * Refusal to participate in this study.

Design outcomes

Primary

MeasureTime frameDescription
Constructing a model based on pupillary parameters and delirium:2023/09/1-2025/08/30By analyzing the relationship between pupillary parameters and delirium, identifying the optimal cut-off point, and constructing a formula.

Countries

Taiwan

Contacts

Primary ContactMing-Chen Chiang
jane.c0203@gmail.com(886) 02-23123456

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026