Prediction for Perioperative Stroke Using Intraoperative Parameters.

ABSTRACT:

Background

Perioperative stroke is a severe complication following surgery. To identify patients at risk for perioperative stroke, several prediction models based on the preoperative factors were suggested. Prediction models often focus on preoperative patient characteristics to assess stroke risk. However, most existing models primarily base their predictions on the patient's baseline characteristics before surgery. We aimed to develop a machine-learning model incorporating both pre- and intraoperative variables to predict perioperative stroke.

Methods and results

This study included patients who underwent noncardiac surgery at 2 hospitals with the data of 15 752 patients from Seoul National University Hospital used for development and temporal internal validation, and the

SUBMITTER: Oh MY 

PROVIDER: S-EPMC11963952 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature