DOI: 10.1097/md.0000000000050255 ISSN: 0025-7974

Construction and validation of a predictive model for postoperative pneumonia in elderly patients with hip fractures

Daxue Zhang, Jian Kang, Yongli Zhang, Shiwei Yang, Xuchun Li

To identify independent risk factors for postoperative pneumonia (POP) in elderly patients with hip fractures and to develop a nomogram for predicting its occurrence, we conducted a multicenter retrospective cohort study of elderly patients (≥ 60 years) who underwent hip fracture surgery at 3 hospitals in Shenzhen, China. Data were collected from medical records. Univariate and multivariate logistic regression analyses, combined with least absolute shrinkage and selection operator regression, were used to identify independent risk factors for POP. A nomogram prediction model was constructed. Model performance was evaluated using the area under the receiver operating characteristic curve for discrimination and the Hosmer–Lemeshow test for calibration. Internal validation was performed using the bootstrap method with 500 resamples. A total of 976 patients were included, with a mean age of 77.46 ± 8.85 years; 73.26% were female. POP occurred in 64 patients (6.56%). Multivariable logistic regression analysis identified a higher white blood cell count, a lower lymphocyte count, a lower albumin level, a history of chronic obstructive pulmonary disease or heart failure, and postoperative intensive care unit admission as independent risk factors for POP (all P  < .05). Age was also an independent predictor. The model demonstrated an area under the curve of 0.795 for the development cohort and 0.792 for the internal validation cohort. The Hosmer–Lemeshow test showed good calibration ( P  = .9695 and 0.3644, respectively). A nomogram based on 7 readily available clinical factors can predict POP in elderly hip fracture patients with moderate accuracy. This internally validated model may assist clinicians in identifying high-risk patients, but further external validation is required before clinical implementation.

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