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COMPLETED
NCT07536854

Early Delirium Prediction Via Serial EEG Trajectories and Machine Learning

Sponsor: Ajou University School of Medicine

View on ClinicalTrials.gov

Summary

The goal of this observational study is to develop a machine learning model that can predict delirium in trauma patients before it clinically appears. The study focuses on analyzing brainwave (EEG) patterns collected over several days in the trauma ICU. By comparing different recording conditions-such as having eyes open versus closed-researchers aim to identify the most effective way to monitor brain health and detect early signs of delirium in critically ill patients.

Official title: Longitudinal Frontal EEG Trajectories Reveal Divergent Cortical Dynamics in Delirium After Severe Trauma

Key Details

Gender

All

Age Range

18 Years - 65 Years

Study Type

OBSERVATIONAL

Enrollment

73

Start Date

2024-04-01

Completion Date

2025-04-30

Last Updated

2026-04-17

Healthy Volunteers

No

Locations (1)

Ajou University Hospital

Suwon, Kyonggi-do, South Korea