Development of a machine learning model to predict intraoperative transfusion and guide type and screen ordering.

ABSTRACT:

Study objective

To develop an algorithm to predict intraoperative Red Blood Cell (RBC) transfusion from preoperative variables contained in the electronic medical record of our institution, with the goal of guiding type and screen ordering.

Design

Machine Learning model development on retrospective single-center hospital data.

Setting

Preoperative period and operating room.

Patients

The study included patients ≥18 years old who underwent surgery during 2019-2022 and excluded those who refused transfusion, underwent emergency surgery, or surgery for organ donation after cardiac or brain death.

Intervention

Prediction of intraoperative transfusion vs. no intraoperative transfusion.

Measurements

The outcome variable was intraoperative transfusion of

SUBMITTER: Zapf MAC 

PROVIDER: S-EPMC10623374 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature