ArticleClinical interventions in aging2025
Risk Factors and Prediction Model for Postoperative Pneumonia Following Hip Arthroplasty in Older Adults.
Article in Clinical interventions in aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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6 authors.
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Abstract
Background: Postoperative pneumonia is one of the most common complications following hip arthroplasty in older adults. It often results in delayed recovery, prolonged hospital stays, and increased perioperative mortality rates. Objective: To analyze the risk factors for postoperative pneumonia in older adults undergoing hip arthroplasty and develop a nomogram-based prediction model using perioperative variables. Methods: A retrospective analysis was performed on 308 older adults who underwent hip arthroplasty. Relevant clinical data were collected and recorded. Univariate and multivariate logistic stepwise regression analyses were conducted to identify the risk factors for postoperative pneumonia in this population. A risk prediction model for postoperative pneumonia was then developed and visualized using a nomogram. Results: Among the 308 older adults, 46 developed postoperative pneumonia, with an incidence rate of approximately 14.94%. Multivariate logistic regression analysis revealed that American Society of Anesthesiologists (ASA) classification, intensive care unit (ICU) admission, preoperative anemia, creatine kinase-MB (CKMB), brain natriuretic peptide (BNP), and postoperative aspartate aminotransferase (AST) were independent risk factors for postoperative pneumonia in elderly patients (P<0.05). The final prediction model for postoperative pneumonia was: P = 1 / [1 + e^(-3.690 + 0.982×ASA + 0.982×ICU + 0.806×Preoperative Anemia + 1.494×CKMB + 0.843×BNP + 0.917×Postoperative AST)], with Hosmer-Lemeshow χ² = 5.989 (P = 0.541). Receiver operating characteristic curve analysis showed an area under the curve of 0.792 (95% CI: 0.761-0.823). The Brier score of the calibration curve was 0.103 (close to 0), and decision curve analysis indicated that the threshold probability of the model ranged from 0.01 to 0.8, with net benefits greater than 0 across all probabilities, suggesting the model has good accuracy and clinical utility. Conclusion: We identified six important predictors-ASA grade, ICU admission, preoperative anemia, CKMB, BNP, and postoperative AST levels-and developed a risk prediction model for postoperative pneumonia following hip arthroplasty in older adults, providing a valuable reference for its prevention in this population.
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