Predictive modeling of perioperative blood transfusion in lumbar posterior interbody fusion using machine learning.

ABSTRACT: Background: Accurate estimation of perioperative blood transfusion risk in lumbar posterior interbody fusion is essential to reduce the number, cost, and complications associated with blood transfusions. Machine learning algorithms have the potential to outperform traditional prediction methods in predicting perioperative blood transfusion. This study aimed to construct a machine learning-based perioperative transfusion risk prediction model for lumbar posterior interbody fusion in order to improve the efficacy of surgical decision-making. Methods: We retrospectively collected clinical data on 1905 patients who underwent lumbar posterior interbody fusion surgery at the Second Hospital of Shanxi Medical University between January 2021 and March 2023. All the data was randomly

SUBMITTER: Lang FF 

PROVIDER: S-EPMC10767743 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature