首页|COPD合并肺间质纤维化的列线图预测模型构建

COPD合并肺间质纤维化的列线图预测模型构建

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目的 分析慢性阻塞性肺疾病(COPD)合并肺间质纤维化的影响因素,构建列线图预测模型。方法 回顾性分析2019年1月至2021年2月该院接诊的195例COPD患者的临床资料,收集可能影响COPD患者合并肺间质纤维化的因素,根据有无肺间质纤维化将患者分为两组。多因素logistic回归分析筛选独立影响因素,并构建列线图预测模型。结果 本研究纳入的195例COPD患者中共有50例(25。64%)合并肺间质纤维化。单因素和多因素logistic回归分析显示:吸烟史、COPD病程、急性加重发作频率、血清转化生长因子β1(TGF-β1)、碱性成纤维细胞生长因子(bFGF)、血管紧张素Ⅱ(Ang Ⅱ)为COPD合并肺间质纤维化的独立影响因素(P<0。05)。根据多因素分析结果构建列线图预测模型,其受试者工作特征(ROC)曲线下面积(AUC)为0。956(95%CI:0。930~0。983),Bootstrap法进行内部验证显示平均绝对误差为0。025,预测模型表现与理想模型基本拟合。结论 该研究构建的列线图模型预测COPD合并肺间质纤维化风险具有较高的准确度与区分度。
Establishment of a nomogram prediction model for risk of COPD complicating pulmonary interstitial fibrosis
Objective To analyze the influencing factors of chronic obstructive pulmonary disease(COPD)complicating pulmonary interstitial fibrosis,and to establish a nomogram prediction model.Methods The clinical data of 195 patients with COPD admitted and treated in this hospital from January 2019 to Feb-ruary 2021 were retrospectively analyzed.The factors possibly affecting the patients with COPD complicating pulmonary interstitial fibrosis were collected,and the patients were divided into 2 groups according to whether having pulmonary interstitial fibrosis.The independent risk factors were analyzed and screened by the multi-variate logistic regression.Then the nomogram prediction model was constructed.Results Among the includ-ed 195 cases of COPD in this study,there were 50 cases(25.64%)of complicating pulmonary interstitial fi-brosis.The univariate and multivariate logistic regression analysis results showed that the smoking history,duration of COPD,frequency of acute exacerbations onset,serum transforming growth factor β1(TGF-β1),basic fibroblast growth factor(bFGF)and angiotensin Ⅱ(AngⅡ)were the independent influencing factors of COPD complicating pulmonary interstitial fibrosis(P<0.05).The nomogram model was constructed accord-ing to the results of multivariate analysis results,and the area under the receiver operating characteristic(ROC)curve was 0.956(95%CI:0.930-0.983),the average absolute error of internal verification by the Bootstrap method was 0.025,and the prediction model performance basically fitted the ideal model.Conclusion The nomogram model constructed by this study for predicting the pulmonary interstitial fibrosis in COPD patients has high accuracy and distinction degree.

chronic obstructive pulmonary diseasepulmonary interstitial fibrosismultivariate analy-sisnomogram

莫尚尧、谢勇、杨丽霞、李亚萍、陈熔

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南充市中心医院呼吸与危重症医学科,四川南充 637000

慢性阻塞性肺疾病 肺间质纤维化 多因素分析 列线图

四川省卫生健康科研课题普及项目

19PJ223

2024

重庆医学
重庆市卫生信息中心,重庆市医学会

重庆医学

CSTPCD
影响因子:1.797
ISSN:1671-8348
年,卷(期):2024.53(1)
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