Prospective Observational Multimodal Neuromonitoring During High-Risk Adult Surgery
NCT07577726
Anesthesia, Brain Diseases
Dallas, Texas, United States
View Trial DetailsNCT Number: NCT07198490
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).
Trial opening soon.
Get Notified18 year and older
All sexes
Observational
This study intends to enroll 50 adult patients with brain injury admitted to the ICU. Multimodal monitoring data will be collected prospectively. Machine learning algorithms will be used to integrate the data and build a predictive model. The study will test whether integrated metabolic-neurological monitoring outperforms traditional single-parameter prognostic methods.
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 3 and 6 months
Neurological outcome at 3 and 6 months assessed by Glasgow Outcome Scale Extended (GOSE)
Time frame: 28 days
all cause mortality at days 28
Contact information is provided by the study sponsor or research team.
Xingui Dai
Other
Construction of a Prognostic Model for Severe Brain-Injured Patients Based on Integrated Metabolic-Neurological Monitoring: A Prospective Observational Study
Acronym: CPM-Brain
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