Impulse oscillometry-derived equation for prediction of abnormal FEV1/FVC ratio for COPD screening in Chinese population: a multicenter cross-sectional study

作者：Meishan Liu, Xin Yao, Yiwei Shi, Huiguo Liu, Liang Chen, Yong Lü, Chunmei Zhang, Xinran Zhang, Lirong Liang, Xiaohong Chang, Li An, Kian Fan Chung, Janwillem Kocks, Kewu Huang · 发表于：The Lancet Regional Health - Western Pacific · 年份：2025 · DOI：10.1016/j.lanwpc.2025.101501 · 被引用次数：3 · 研究领域：Chronic Obstructive Pulmonary Disease (COPD) Research、Respiratory and Cough-Related Research、Inhalation and Respiratory Drug Delivery

Background The diagnosis of chronic obstructive pulmonary disease (COPD) is based on spirometry that requires a forced expiratory manoeuvre, which is laborious and difficult for mass screening. Impulse oscillometry (IOS) is easier than spirometry and performed with tidal breathing. We sought to develop an equation for predicting forced expiratory volume in 1 s (FEV 1 )/forced vital capacity (FVC) and screening COPD using IOS parameters. Methods Data from patients who simultaneously underwent spirometry and IOS were obtained from databases at five tertiary hospitals in China. Multivariable linear regression analysis was used to develop a predictive model for pre-bronchodilator (BD) FEV 1 /FVC. Model performance was analyzed against spirometric criteria of airflow obstruction (AO, defined as pre-BD FEV 1 /FVC < 0.7) and COPD (post-BD FEV 1 /FVC < 0.7). Findings Using 15,113 patients and externally validated with 9586 patients, the model estimated FEV 1 /FVC ratio could identified AO and spirometry-defined COPD in internal (AUC = 0.822 and 0.849, respectively) and external (AUC = 0.790 and 0.828, respectively) validation. A clinical algorithm was constructed to classify patients into three different groups: estimated FEV 1 /FVC < 0.7: likely COPD; estimated FEV 1 /FVC ≥ 0.7 and ≤0.73: suspicious for COPD; estimated FEV 1 /FVC > 0.73: unlikely COPD. The sensitivity and specificity for detecting spirometry-defined COPD were 88.0% and 77.0%, respectively, while the negative predict...