Ontology highlight
ABSTRACT: Background
As the number of HIV-infected patients increased, the number of patients requiring general surgery has subsequently increased. However, impairment of immune function due to HIV infection increases the risk of postoperative surgical-site infection and significant harm to patient health. This study aimed to examine the risk factors for surgical-site infection after general surgery.Methods
The patients' data were from Zunyi fourth hospital medical information system. Machine learning based Boruta algorithm were used for variable screening. Univariable and multivariable logistic regression and restricted cubic spline analysis were performed to examine the relationship between significant variables and surgical-site infection.Results
A total of 125 general sur
SUBMITTER: Chen Y
PROVIDER: S-EPMC11562515 | biostudies-literature | 2024 Nov
REPOSITORIES: biostudies-literature