Machine learning-based prediction of post-induction hypotension: identifying risk factors and enhancing anesthesia management.
Journal:
BMC medical informatics and decision making
PMID:
39987101
Abstract
BACKGROUND: Post-induction hypotension (PIH) increases surgical complications including myocardial injury, acute kidney injury, delirium, stroke, prolonged hospitalization, and endangerment of the patient's life. Machine learning is an effective tool to analyze large amounts of data and identify perioperative complication factors. This study aims to identify risk factors for PIH and develop predictive models to support anesthesia management.