Prediction of Postoperative Pain and Side Effects of Patient-Controlled Analgesia in Pediatric Orthopedic Patients Using Machine Learning: A Retrospective Study.

ABSTRACT: Background/Objectives: Appropriate postoperative management, especially in pediatric patients, can be challenging for anesthesiologists. This retrospective study used machine learning to investigate the effects and complications of patient-controlled analgesia (PCA) in children undergoing orthopedic surgery. Methods: The medical records of children who underwent orthopedic surgery in a single tertiary hospital and received intravenous and epidural PCA were analyzed. Predictive models were developed using machine learning, and various demographic, anesthetic, and surgical factors were investigated to predict postoperative pain and complications associated with PCA. Results: Data from 1968 children were analyzed. Extreme gradient boosting effectively predicted moderate p

SUBMITTER: Joe YE 

PROVIDER: S-EPMC11899821 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature