文章摘要
周 健,张兰英,刘钰婷,安 璇,欧阳瑶.基于慢性阻塞性肺疾病患者呼吸功能锻炼行为影响因素的列线图风险模型构建与验证[J].,2024,(11):2134-2139
基于慢性阻塞性肺疾病患者呼吸功能锻炼行为影响因素的列线图风险模型构建与验证
Construction and Validation of Nomogram Risk Model Based on Influencing Factors of Respiratory Function Exercise Behavior in Patients with Chronic Obstructive Pulmonary Disease
投稿时间:2024-02-08  修订日期:2024-02-23
DOI:10.13241/j.cnki.pmb.2024.11.025
中文关键词: 慢性阻塞性肺疾病  呼吸功能锻炼  依从性  影响因素  预测模型
英文关键词: Chronic obstructive pulmonary disease  Respiratory function exercise  Compliance  Influencing factors  Prediction model
基金项目:国家自然科学基金项目(82060005);贵州省科技计划项目(黔科合支撑[2020]4Y141号);遵义市联合基金项目(遵市科合HZ字(2022)255号);遵义市科技支撑计划项目(遵市科合社字(2018)71)
作者单位E-mail
周 健 遵义医科大学附属医院呼吸与危重症医学科 贵州 遵义 563000 zhouj202403@163.com 
张兰英 遵义医科大学附属医院呼吸与危重症医学科 贵州 遵义 563000  
刘钰婷 遵义医科大学附属医院呼吸与危重症医学科 贵州 遵义 563000  
安 璇 遵义医科大学附属医院呼吸与危重症医学科 贵州 遵义 563000  
欧阳瑶 遵义医科大学附属医院呼吸与危重症医学科 贵州 遵义 563000  
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中文摘要:
      摘要 目的:探究慢性阻塞性肺疾病(COPD)患者呼吸功能锻炼行为影响因素,并构建列线图预测模型。方法:选取2021年3月至2023年3月我院COPD患者112例,根据呼吸功能锻炼行为情况分为低依从性组(n=68)和高依从性组(n=44)。采用单因素分析、多因素Logistic回归分析COPD患者呼吸功能锻炼行为低依从性的影响因素,构建预测模型,并采用受试者工作特征(ROC)分析模型预测价值。结果:年龄≥60岁、在职、无家庭支持、活动后呼吸困难、疾病不确定感高、运动自我效能低为COPD患者呼吸功能锻炼行为低依从性的独立危险因素(P<0.05)。年龄、在职、家庭支持、活动后呼吸困难、疾病不确定感、运动自我效能及列线图预测模型的曲线下面积(AUC)分别为0.645、0.645、0.717、0.600、0.660、0.672、0.908,预测模型对COPD患者呼吸功能锻炼低依从性的预测价值更高,当取截断值(cut-off)值为0.498时,其灵敏度为0.912,特异度为0.795。Bootstrap法(B=1000)内部验证显示,修正偏差后的预测曲线与理想线基本重合,一致性指数(C-index)为0.816,表明该模型的预测能力较好。决策曲线显示,阈值概率范围为0.01~0.92,净收益率>0。结论:年龄≥60岁、在职、无家庭支持、活动后呼吸困难、疾病不确定感高、运动自我效能低为COPD患者呼吸功能锻炼行为低依从性的独立危险因素。预测模型有助于评估锻炼依从性并制定干预措施。
英文摘要:
      ABSTRACT Objective: To explore the influencing factors of respiratory function exercise behavior in patients with chronic obstructive pulmonary disease (COPD), and to construct a nomogram prediction model. Methods: 112 COPD patients in our hospital from March 2021 to March 2023 were selected, and patients were divided into low compliance group (n=68) and high compliance group (n=44) according to their respiratory function exercise behavior. The influencing factors of low compliance of respiratory function exercise behavior in COPD patients were analyzed by univariate analysis and multivariate logistic regression analysis, and a prediction model was constructed, the predictive value of the model was analyzed by receiver operating characteristic (ROC). Results: Age≥60 years old, on the job, no family support, dyspnea after activity, high disease uncertainty, and low exercise self-efficacy were independent risk factors for low compliance of respiratory function exercise in COPD patients (P<0.05). The area under the curve (AUC) of age, on the job, family support, dyspnea after activity, disease uncertainty, exercise self-efficacy and nomogram prediction model were 0.645, 0.645, 0.717, 0.600, 0.660, 0.672 and 0.908 respectively, the prediction model had higher predictive value for low compliance of respiratory function exercise in COPD patients, when the cut-off value was 0.498, the sensitivity was 0.912 and the specificity was 0.795. The internal validation of the Bootstrap method (B=1000) showed that the predicted curve after the correction of the deviation was basically coincident with the ideal line, and the consistency index (C-index) was 0.816, indicating that the prediction ability of the model was better. The decision curve shows that the threshold probability range was 0.01~0.92, and the net return rate was>0. Conclusion: Age≥60 years old, on the job, no family support, dyspnea after activity, high uncertainty of disease, and low exercise self-efficacy are independent risk factors for low compliance of respiratory function exercise in COPD patients. The predictive model can help to assess exercise compliance and develop interventions.
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