AUTHOR=Liu Yuhan , Fan Yunping , Yang Xuping , Gan Haibin , Li Xiaohua , Luo Yanrong , Pang Qianyun , Yang Tingjun 

TITLE=Nomogram for predicting postoperative pulmonary infection in elderly patients undergoing major orthopedic surgery

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1537697

DOI=10.3389/fmed.2025.1537697

ISSN=2296-858X

ABSTRACT=ObjectiveThe incidence of pulmonary infection following major orthopedic surgery in the elderly is high, significantly affecting prognosis. Identifying high-risk factors and stratifying patient risk more effectively is an urgent problem that needs to be addressed. This study aims to develop a nomogram for predicting postoperative pulmonary infection (PPI) in elderly patients undergoing major orthopedic surgery.MethodsData from preoperative variables, surgical procedures, and anesthesia factors of 814 elderly patients who underwent major orthopedic surgery between January 2020 and October 2023 were retrospectively collected to develop a nomogram. The primary outcome was PPI. Stata 16 and R 4.1.2 software were used for statistical analysis.ResultsMultivariate logistic regression revealed that gender (OR = 2.336, 95% CI1.135–4.807, p = 0.021), preoperative pulmonary disease (OR = 6.042, 95% CI 2.849–12.814, p = 0.000), preoperative sedation and analgesia (OR = 0.159, 95% CI 0.037–0.689, p = 0.014), intraoperative infusion volume ≥ 1,200 mL (OR = 2.530, 95% CI 1.166–5.489, p = 0.019) were identified as independent risk factors for PPI in elderly orthopedic patients. The risk factors in the nomogram included ASA, gender, preoperative pulmonary disease, cognitive impairment, and non-preoperative sedation and analgesia, and intraoperative infusion. Area under the curve (AUC) of the nomogram was 0.834, the slope was 1.000, and the net benefit of the decision curve analysis (DCA) curve was 0.01–0.60.ConclusionResearchers have developed and validated a predictive nomogram for PPI in elderly patients undergoing major orthopedic surgery, identifying 6 key variables, which can be used to predict PPI of aged patients undergoing major orthopedic surgery and identify high risk groups.