Development and validation of a prediction tool for intraoperative blood transfusion in brain tumor resection surgery: a retrospective analysis.

ABSTRACT: Early identification of a patient with a high risk of blood transfusion during brain tumor resection surgery is difficult but critical for implementing preoperative blood-saving strategies. This study aims to develop and validate a machine learning prediction tool for intraoperative blood transfusion in brain tumor resection surgery. A total of 541 patients who underwent brain tumor resection surgery in our hospital from January 2019 to December 2021 were retrospectively enrolled in this study. We incorporated demographics, preoperative comorbidities, and laboratory risk factors. Features were selected using the least absolute shrinkage and selection operator (LASSO). Eight machine learning algorithms were benchmarked to identify the best model to predict intraoperative blood transfusion.

SUBMITTER: Xiao S 

PROVIDER: S-EPMC10575918 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature