一种基于肺量计构建的慢性阻塞性肺疾病患者过度充气预测模型
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1.南京医科大学第一附属医院呼吸与危重症医学科,江苏 南京 210029 ; 2.安溪县医院呼吸与危重症医学科,福建 泉州 362046

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R563.1

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国家重点研发计划(2018YFC1311900);江苏省研究生科研与实践创新计划项目(SJCX23_0707)


A risk prediction model for hyperinflation in patients with COPD constructed based on spirometry
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1.Department of Respiratory and Critical Care Medicine,the First Affiliated Hospital of Nanjing Medical University,Nanjing 210029 ; 2.Department of Respiratory and Critical Care Medicine,Anxi County Hospital,Quanzhou 362046 ,China

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    摘要:

    目的:探讨慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)患者的症状、运动能力与肺过度充气的关系,建立基于肺量计测定参数预测COPD患者发生过度充气的列线图模型。方法:招募COPD患者和肺功能正常的对照组进行 6 min步行试验(6-minute walk test,6MWT),再根据《慢性阻塞性肺疾病全球防治倡议》指南将COPD组分为过度充气组(39例) 和非过度充气组(62例)。分析3组临床资料、6MWT和肺功能等资料。使用Boruta法联合LASSO回归筛选变量,通过单因素和多因素Logistic 回归分析COPD过度充气的相关因素,建立预测COPD患者发生过度充气的列线图模型,并评估其预测效果。结果:与非过度充气组相比,COPD伴过度充气组患者6 min步行距离(6-minute walk distance,6MWD)更短,6MWD占预计值百分比(6MWD%pred)更小,平均值为(86.74±12.54)%,并伴随更明显的步行脉氧下降和更重的运动后腿部疲劳症状; 且过度充气组中改良医学委员会呼吸困难指数(modified Medical Research Council dyspnea score,mMRC)≥2和COPD 评估测试(COPD assessment test,CAT)≥10 的患者比例更高。Logistic 回归分析结果提示肺活量(vital capacity,VC)(β=-2.636, OR=0.072,95%CI:0.022~0.232)、最大呼气中期流量占预计值百分比(maximal mid-expiratory flow of predicted,MMEF%pred) (β=-0.147,OR=0.863,95%CI:0.790~0.944)是COPD患者发生过度充气的独立预测因素。过度充气组VC和MMEF%pred的平均值分别为(2.51±0.60)L和(23.05±6.48)%。据此构建的列线图模型预测COPD患者发生过度充气的受试者工作特征(reciever operating characteristic,ROC)曲线的曲线下面积(area under curve,AUC)为0.897(95%CI:0.836~0.957,P < 0.01),校准曲线的平均绝对误差为 0.023。结论:基于肺量计参数 VC 与 MMEF%pred 构建的列线图模型可以预测 COPD 患者发生过度充气;当 COPD患者肺量计检测结果显示存在通气功能障碍,其参数VC和MMEF%pred下降预示其合并过度充气的风险增大。这类患者往往运动耐力下降,症状多,提示需要临床重点关注。

    Abstract:

    Objective:To investigate the relationship between symptoms,exercise capacity and hyperinflation in chronic obstructive pulmonary disease(COPD)patients;and to try to establish a nomogram prediction model based on spirometry to predict the occurrence of hyperinflation in COPD. Methods:COPD patients and controls with normal lung function were recruited to perform the 6-minute walk test(6MWT). The COPD patients were divided into a hyperinflation group(39 cases)and a non-hyperinflation group (62 cases)according to the GOLD guidelines. Clinical data,6MWT and lung function were analysed in the three groups. Variables were screened by the Boruta algorithm combined with LASSO regression,and the variables were analysed by univariate and multivariate logistic regression,to establish a nomogram prediction model of the occurrence of hyperinflation in COPD patients and to assess its predictive effect. Results:Compared to the non-hyperinflation group,patients in the hyperinflation group had a shorter 6-minute walk distance(6MWD),a smaller 6MWD as a percentage of predicted value(6MWD%pred),and a mean 6MWD%pred of (86.74±12.54)%,accompanied by the symptoms of a more severe drop in walking pulse-oximetry and a more severe post-exercise leg fatigue. The hyperinflation group had a higher proportion of patients with mMRC≥2 and CAT ≥10. The results of logistic regression analysis suggested that vital capacity(VC)(β=-2.636,OR=0.072,95% CI:0.022-0.232),Maximal mid-expiratory flow of predicted (MMEF% pred)(β =- 0.147,OR=0.863,95% CI:0.790- 0.944)were independent predictors of the occurrence of hyperinflation in COPD patients. The mean values of VC and MMEF% pred in the hyperinflation group were(2.51 ± 0.60)L and(23.05 ± 6.48)%, respectively. The area under curve(AUC)of the reciever operating characteristic(ROC)curve of the nomogram model was 0.897(95% CI:0.836-0.957,P < 0.01). The mean absolute error of the calibration curve was 0.023. Conclusion:The nomogram model based on the spirometer parameters VC and MMEF% pred can predict the occurrence of hyperinflation in COPD patients. When ventilatory dysfunction was present on spirometry testing in COPD patients,a decrease in the parameters VC and MMEF% pred predicted an increased risk of combined hyperinflation. These patients tend to have reduced exercise tolerance and are multisymptomatic, suggesting the need for clinical focus. This predictive model provides primary community care with an easy-to-implement,method of assessing patients with COPD and facilitates guidance for individualised treatment and rehabilitation.

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王诗绮,陈幼花,徐小俊,孙培莉.一种基于肺量计构建的慢性阻塞性肺疾病患者过度充气预测模型[J].南京医科大学学报(自然科学版),2025,(4):535-543,559

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  • 收稿日期:2024-09-30
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  • 在线发布日期: 2025-04-08
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