Developing a calculable risk prediction model for sternal wound infection after median sternotomy: a retrospective study.

ABSTRACT:

Background

Diagnosing sternal wound infection (SWI) following median sternotomy remains laborious and troublesome, resulting in high mortality rates and great harm to patients. Early intervention and prevention are critical and challenging. This study aimed to develop a simple risk prediction model to identify high-risk populations of SWI and to guide examination programs and intervention strategies.

Methods

A retrospective analysis was conducted on the clinical data obtained from 6715 patients who underwent median sternotomy between January 2016 and December 2020. The least absolute shrink and selection operator (LASSO) regression method selected the optimal subset of predictors, and multivariate logistic regression helped screen the significant factors. The nomogram model

SUBMITTER: Chen Y 

PROVIDER: S-EPMC11401447 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature