Research on the Development and Validation of an Early Prediction Model for Delirium

Shanghai Jiao Tong University

Status: Not yet enrolling

Conditions: Prediction Models; Delirium; Machine Learning

Study type: Observational

Funder types: Other

Identifiers

NCT07337356

ZWQ21886-2025-EC-579

Details and patient eligibility

About

Delirium has a high incidence rate and significantly affects patient prognosis. Diagnosis often relies on manual assessment, which is subject to strong subjectivity, high rates of missed diagnosis, and poor stability. This study employs non-contact identification technology based on machine vision analysis to quantitatively analyze characteristic biological feature data such as micro-expressions. It then investigates the correlation between these features and delirium subtypes. By integrating clinical phenotypic data and using machine learning algorithms, a multi-modal early prediction model for delirium is constructed to meet the clinical need for early warning of delirium subtypes and enhance the efficacy of delirium identification.

Enrollment: 795 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age ≥ 18 years, expected ICU stay ≥ 24 hours, and informed consent to participate in this study;

Exclusion criteria

• Patients with severe facial trauma/deformities that prevent complete expression acquisition, and patients with a history of emotional problems (such as anxiety, depression, etc.).

Trial design

795 participants in 2 patient groups

observational

Description:

1. Meets the delirium diagnostic criteria specified in the Diagnostic and Statistical Manual of Mental Disorders (5th Edition) (DSM-5), which requires the concurrent presence of: ① disturbance in awareness (reduced clarity of awareness of the environment) ; ② change in cognition (e.g., memory impairment, disorientation); 2. Undergoes consecutive daily assessments for 7 days using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) at three time points (8:00, 14:00, 20:00) with an interval of ≥ 6 hours between each assessment, with at least two positive results;

control

Description:

Admitted to the ICU during the same period, with negative results on consecutive daily CAM-ICU assessments for 3 days (three assessments per day as the observational group).