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Construction of a Prognostic Model for Severe Brain-Injured Patients Based on Integrated Metabolic-Neurological Monitoring
Sponsor: Xingui Dai
Summary
This is a prospective, observational cohort study aimed at constructing a machine learning-based prognostic model for severe brain-injured patients. The study will synchronously collect continuous glucose monitoring (CGM), electroencephalography (EEG), near-infrared spectroscopy (fNIRS), transcranial Doppler (TCD), and serum neuronal injury biomarkers (NSE, S100β) within 72 hours post-injury. The goal is to investigate the correlation between glycemic variability (GV) and neurological function and to develop an integrated model for early prediction of 3-6 month neurological outcomes (GOSE score).
Official title: Construction of a Prognostic Model for Severe Brain-Injured Patients Based on Integrated Metabolic-Neurological Monitoring: A Prospective Observational Study
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
50
Start Date
2025-10-01
Completion Date
2026-12-31
Last Updated
2025-09-30
Healthy Volunteers
Not specified