Xiang Bingbing, Zhang Jingyuan, Deng Chaoyi, Yang Han, Qian Liu, Zhang Wensheng
Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
Department of Anesthesiology, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650000, People's Republic of China.
Clin Interv Aging. 2025 May 31;20:763-775. doi: 10.2147/CIA.S521087. eCollection 2025.
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.
To analyze the risk factors for postoperative pneumonia in older adults undergoing hip arthroplasty and develop a nomogram-based prediction model using perioperative variables.
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.
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.
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.
术后肺炎是老年患者髋关节置换术后最常见的并发症之一。它常导致恢复延迟、住院时间延长和围手术期死亡率增加。
分析老年髋关节置换患者术后肺炎的危险因素，并使用围手术期变量建立基于列线图的预测模型。
对308例接受髋关节置换术的老年患者进行回顾性分析。收集并记录相关临床数据。进行单因素和多因素逻辑逐步回归分析，以确定该人群术后肺炎的危险因素。然后使用列线图建立并可视化术后肺炎的风险预测模型。
在308例老年患者中，46例发生术后肺炎，发生率约为14.94%。多因素逻辑回归分析显示，美国麻醉医师协会（ASA）分级、入住重症监护病房（ICU）、术前贫血、肌酸激酶-MB（CKMB）、脑钠肽（BNP）和术后天门冬氨酸氨基转移酶（AST）是老年患者术后肺炎的独立危险因素（P<0.05）。术后肺炎的最终预测模型为：P = 1 / [1 + e^(-3.690 + 0.982×ASA + 0.982×ICU + 0.806×术前贫血 + 1.494×CKMB + 0.843×BNP + 0.917×术后AST)]，Hosmer-Lemeshow χ² = 5.989（P = 0.541）。受试者工作特征曲线分析显示曲线下面积为0.792（95%CI：0.761-0.823）。校准曲线的Brier评分为0.103（接近0），决策曲线分析表明该模型的阈值概率范围为0.01至0.8，所有概率下的净效益均大于0，表明该模型具有良好的准确性和临床实用性。
我们确定了六个重要预测因素——ASA分级、入住ICU、术前贫血、CKMB、BNP和术后AST水平，并建立了老年髋关节置换术后肺炎的风险预测模型，为该人群的肺炎预防提供了有价值的参考。
