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).
Diagnosis of severe TBI, large-volume stroke, or HIE
Expected ICU stay >72 hours
Informed consent from legal surrogate
Terminal organ failure
Pre-existing severe neurological disease
Skull defect preventing monitoring
Pregnancy or lactation
Xingui Dai
Lead sponsor
First People's Hospital of Chenzhou
Sponsor institution