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
The study population will consist of adult patients (≥18 years old) admitted to the Intensive Care Unit (ICU) of Chenzhou First People's Hospital with a diagnosis of brain injury. This includes patients with:Severe Traumatic Brain Injury (TBI), Expected ICU stay \>72 hours,Informed consent from legal surrogate.
Cohort
Prospective
Not listed
Glasgow Outcome Scale Extended (GOSE)
Neurological outcome at 3 and 6 months assessed by Glasgow Outcome Scale Extended (GOSE)
28 days mortality
all cause mortality at days 28
Click on the lead sponsor to view all of their trials.
Xingui Dai
Lead sponsor
First People's Hospital of Chenzhou
Sponsor institution
This trial is not recruiting at the moment. You can still explore other options:
