Ontology highlight
ABSTRACT: Objective
Prolonged length of stay (LOS) following orthopedic surgery places a significant strain on healthcare systems. However, effective tools for predicting LOS in patients undergoing clean (Class I) orthopedic surgery are lacking. This study aims to identify factors influencing length of stay in orthopedic Class I incision surgery and construct a predictive nomogram based on these factors.Methods
Retrospective analysis of patients undergoing orthopedic Class I incision surgery in Taihe Hospital from January 1, 2018 to October 31, 2023. Patients meeting the inclusion criteria were enrolled. Using prolonged length of stay (LOS > 7 days) as the primary outcome, we performed univariate analysis followed by binary logistic regression to identify risk factors. An individual
SUBMITTER: Fu B
PROVIDER: S-EPMC12833462 | biostudies-literature | 2025
REPOSITORIES: biostudies-literature