Using multiple indicators to predict the risk of surgical site infection after ORIF of tibia fractures: a machine learning based study.

ABSTRACT:

Objective

Surgical site infection (SSI) are a serious complication that can occur after open reduction and internal fixation (ORIF) of tibial fractures, leading to severe consequences. This study aimed to develop a machine learning (ML)-based predictive model to screen high-risk patients of SSI following ORIF of tibial fractures, thereby aiding in personalized prevention and treatment.

Methods

Patients who underwent ORIF of tibial fractures between January 2018 and October 2022 at the Department of Emergency Trauma Surgery at Ganzhou People's Hospital were retrospectively included. The demographic characteristics, surgery-related variables and laboratory indicators of patients were collected in the inpatient electronic medical records. Ten different machine learning algorith

SUBMITTER: Ying H 

PROVIDER: S-EPMC10338008 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature