Construction and validation of nomogram to predict surgical site infection after hysterectomy: a retrospective study.

ABSTRACT: This study aimed to develop a predictive tool for surgical site infections (SSI) following hysterectomy and propose strategies for their prevention and control. We conducted a retrospective analysis at a tertiary maternity and child specialist hospital in Zhejiang Province, focusing on patients who underwent hysterectomy between January 2018 and December 2023 for gynecological malignancies or benign reproductive system diseases resistant to medical treatment. Risk factors associated with surgical site infections (SSI) following hysterectomy were identified using LASSO regression analysis on data from 2018 to 2022 as the training set. Independent risk factors were then used to develop a nomogram. The model was validated using data from 2023 as the validation set. Model performance was asses

SUBMITTER: Shao H 

PROVIDER: S-EPMC11375043 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature