Functional MRI-based machine learning strategy for prediction of postoperative delirium in cardiac surgery patients: A secondary analysis of a prospective observational study.
Journal:
Journal of clinical anesthesia
PMID:
39951939
Abstract
STUDY OBJECTIVE: Delirium is a common complication after cardiac surgery and is associated with poor prognosis. An effective delirium prediction model could identify high-risk patients who might benefit from targeted prevention strategies. We introduce machine learning models that employ resting-state functional MRI datasets obtained before surgery to predict postoperative delirium.