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老年COPD患者获得性衰弱风险预测模型构建
作者:樊佳鑫  梅培培 
单位:南京医科大学第一附属医院/江苏省人民医院 老年呼吸科, 江苏 南京 210029
关键词:慢性阻塞性肺疾病  老年患者  获得性衰弱  危险因素  预测模型 
分类号:R563
出版年·卷·期(页码):2025·53·第五期(772-778)
摘要:

目的: 探讨老年慢性阻塞性肺疾病(COPD)患者的获得性衰弱现状,明确其危险因素,以构建预测模型。方法: 回顾性分析本院2021年1月至2024年4月住院治疗的215例老年COPD患者的临床资料,根据是否发生获得性衰弱分为获得性衰弱组(n=102)和非获得性衰弱组(n=113)。比较两组一般资料以及临床相关指标,进一步纳入多因素Logistic回归分析,以构建预测模型。Hosmer-Lemeshow 用以检验评估模型拟合优度,绘制受试者工作特征(ROC)曲线以评估该预测模型的价值。结果: 共纳入215例老年COPD患者,获得性衰弱发生率为47.44%(102/215)。非获得性衰弱组在闭目单脚站立测试(CST)、6 min步行距离(6MWD)、老年人运动功能量表(GLFS)、第1秒用力呼气容积(FEV1)以及用力肺活量(FVC)检查指标上的表现优于获得性衰弱组,差异有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,年龄、体育活动等级量表(PARS-3)评分、共病情况、睡眠障碍、COPD病程、营养风险、降钙素原(PCT)、C反应蛋白(CRP)以及中性粒细胞与淋巴细胞比值(NLR)是老年COPD患者获得性衰弱的独立影响因素(P<0.05)。根据以上影响因素构建预测模型,其Homer-Lemeshow检验拟合优度(χ2=9.047, P=0.483)显示校准度良好;AUC=0.817(0.729~0.905),灵敏度为 0.784,特异度为 0.818。结论: 老年COPD患者并发获得性衰弱会显著降低其运动能力,影响其呼吸功能;基于临床、实验室相关指标构建的风险预测模型有助于临床护理人员对高风险患者进行及时干预,从而改善患者的功能状态和生活质量。

Objective: To investigate the current status of acquired weakness in elderly patients with chronic obstructive pulmonary disease(COPD), identify its risk factors, and develop a predictive model. Methods: A retrospective analysis was conducted on the clinical data of 215 elderly COPD patients hospitalized in our hospital from January 2021 to April 2024. Patients were divided into a acquired frailty group(n=102) and a non-acquired frailty group(n=113) based on the presence of acquired frailty. The general characteristics and clinical-related indicators were compared between the two groups, and factors which had statistic significance were incorporated into multivariate Logistic regression analysis to construct a predictive model. The Hosmer-Lemeshow test was used to assess the goodness-of-fit of the model, and the receiver operating characteristic(ROC) curve was plotted to evaluate the predictive value of the model. Results: Among the 215 elderly COPD patients, the prevalence of acquired frailty was 47.44%(102/215). The non-acquired frailty group showed significantly better performance in closed-eyed standing test(CST), 6-minute walking distance(6MWD), geriatric locomotive function scale(GLFS), forced expiratory volume in 1 second(FEV1, and forced vital capacity(FVC) compared to the acquired frailty group(P<0.05). Multivariate Logistic regression analysis identified age, physical activity rank scale (PARS-3), comorbidities, sleep disorder, COPD duration, nutritional risk, procalcitonin(PCT), C-reactive protein(CRP), and neutrophil-to-lymphocyte ratio(NLR) as independent risk factors for acquired frailty in elderly COPD patients(P<0.05). A predictive model was constructed based on these influencing factors. The Hosmer-Lemeshow test indicated good calibration (χ2=9.047, P=0.483). The AUC was 0.817(95%CI 0.729-0.905), with a sensitivity of 0.784, and a specificity of 0.818. Conclusion: Acquired frailty can significantly reduce physical performance and adversely affect respiratory function in elderly COPD patients. The risk prediction model based on clinical and laboratory indicators facilitates early identification of high-risk patients, enabling timely interventions by clinical care providers to improve patients' functional status and quality of life.

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