Yuning Huang, Xue Zhang, Jinwen Wang, Wuping Bao, Chengjian Lv, Yingying Zhang, Xue Tian, Yan Zhou, Min Zhang
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Traditional spirometry may miss SAD due to its reliance on forced vital capacity.</p>\n </section>\n \n <section>\n \n <h3> Objective</h3>\n \n <p>This study investigates the role of impulse oscillometry system (IOS) for early detection, disease monitoring, and AE prediction.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Pathological specimens from 64 patients with normal lung function were divided into small airway pathological abnormalities (PAs, <i>n</i> = 38) and normal pathology (PN, <i>n</i> = 26). Logistic regression and receiver operating characteristic (ROC) curve analysis evaluated IOS's predictive value for SAD. Additionally, 37 healthy volunteers, 125 COPD patients, and 128 ACO patients underwent spirometry, IOS, FeNO, CT scans, and blood tests. Correlations between IOS and spirometry indices were evaluated. One-year follow-up of 140 patients assessed IOS's predictive capability for AE.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>ROC analysis indicated that R5 − R20 combined with FEF<sub>75</sub>%pred best predicted PAs (areas under the ROC curves [AUC] = 0.80). R5 − R20, with a cut-off of 0.09 kPa/[L/s], demonstrated 85.6% sensitivity and 72.9% specificity in distinguishing COPD from healthy individuals, and 89.1% sensitivity with 72.9% specificity for ACO. In COPD, R5 − R20 correlated strongly with spirometry indices (<i>r</i> = 0.60), while Fres correlated well in ACO (<i>r</i> = 0.48) for FEV<sub>1</sub>%pred ≥ 50%, with slightly weaker correlations for FEV<sub>1</sub>%pred < 50%. For predicting AE, a model combining R5 − R20, FEV<sub>1</sub>%Pred and body mass index had an AUC of 0.860 in COPD, while a model with Fres, FEV<sub>1</sub>%pred and fraction of exhaled nitric oxide achieved an AUC of 0.874 in ACO.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>IOS is valuable for early detection, monitoring, and AE prediction in COPD and ACO, enhancing diagnostic precision.</p>\n </section>\n \n <section>\n \n <h3> Clinical Trial Registration</h3>\n \n <p>No. ChiCTR2400089625, www.chictr.org.cn.</p>\n </section>\n </div>","PeriodicalId":10334,"journal":{"name":"Clinical and Translational Allergy","volume":"15 4","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clt2.70057","citationCount":"0","resultStr":"{\"title\":\"Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma-chronic obstructive pulmonary disease overlap\",\"authors\":\"Yuning Huang, Xue Zhang, Jinwen Wang, Wuping Bao, Chengjian Lv, Yingying Zhang, Xue Tian, Yan Zhou, Min Zhang\",\"doi\":\"10.1002/clt2.70057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Small airway dysfunction (SAD) is critical in chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap (ACO), impacting disease severity, acute exacerbation (AE) risk, and prognosis. Traditional spirometry may miss SAD due to its reliance on forced vital capacity.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>This study investigates the role of impulse oscillometry system (IOS) for early detection, disease monitoring, and AE prediction.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>Pathological specimens from 64 patients with normal lung function were divided into small airway pathological abnormalities (PAs, <i>n</i> = 38) and normal pathology (PN, <i>n</i> = 26). Logistic regression and receiver operating characteristic (ROC) curve analysis evaluated IOS's predictive value for SAD. Additionally, 37 healthy volunteers, 125 COPD patients, and 128 ACO patients underwent spirometry, IOS, FeNO, CT scans, and blood tests. Correlations between IOS and spirometry indices were evaluated. One-year follow-up of 140 patients assessed IOS's predictive capability for AE.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>ROC analysis indicated that R5 − R20 combined with FEF<sub>75</sub>%pred best predicted PAs (areas under the ROC curves [AUC] = 0.80). R5 − R20, with a cut-off of 0.09 kPa/[L/s], demonstrated 85.6% sensitivity and 72.9% specificity in distinguishing COPD from healthy individuals, and 89.1% sensitivity with 72.9% specificity for ACO. In COPD, R5 − R20 correlated strongly with spirometry indices (<i>r</i> = 0.60), while Fres correlated well in ACO (<i>r</i> = 0.48) for FEV<sub>1</sub>%pred ≥ 50%, with slightly weaker correlations for FEV<sub>1</sub>%pred < 50%. 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Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma-chronic obstructive pulmonary disease overlap
Background
Small airway dysfunction (SAD) is critical in chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap (ACO), impacting disease severity, acute exacerbation (AE) risk, and prognosis. Traditional spirometry may miss SAD due to its reliance on forced vital capacity.
Objective
This study investigates the role of impulse oscillometry system (IOS) for early detection, disease monitoring, and AE prediction.
Methods
Pathological specimens from 64 patients with normal lung function were divided into small airway pathological abnormalities (PAs, n = 38) and normal pathology (PN, n = 26). Logistic regression and receiver operating characteristic (ROC) curve analysis evaluated IOS's predictive value for SAD. Additionally, 37 healthy volunteers, 125 COPD patients, and 128 ACO patients underwent spirometry, IOS, FeNO, CT scans, and blood tests. Correlations between IOS and spirometry indices were evaluated. One-year follow-up of 140 patients assessed IOS's predictive capability for AE.
Results
ROC analysis indicated that R5 − R20 combined with FEF75%pred best predicted PAs (areas under the ROC curves [AUC] = 0.80). R5 − R20, with a cut-off of 0.09 kPa/[L/s], demonstrated 85.6% sensitivity and 72.9% specificity in distinguishing COPD from healthy individuals, and 89.1% sensitivity with 72.9% specificity for ACO. In COPD, R5 − R20 correlated strongly with spirometry indices (r = 0.60), while Fres correlated well in ACO (r = 0.48) for FEV1%pred ≥ 50%, with slightly weaker correlations for FEV1%pred < 50%. For predicting AE, a model combining R5 − R20, FEV1%Pred and body mass index had an AUC of 0.860 in COPD, while a model with Fres, FEV1%pred and fraction of exhaled nitric oxide achieved an AUC of 0.874 in ACO.
Conclusions
IOS is valuable for early detection, monitoring, and AE prediction in COPD and ACO, enhancing diagnostic precision.
期刊介绍：
Clinical and Translational Allergy, one of several journals in the portfolio of the European Academy of Allergy and Clinical Immunology, provides a platform for the dissemination of allergy research and reviews, as well as EAACI position papers, task force reports and guidelines, amongst an international scientific audience.
Clinical and Translational Allergy accepts clinical and translational research in the following areas and other related topics: asthma, rhinitis, rhinosinusitis, drug hypersensitivity, allergic conjunctivitis, allergic skin diseases, atopic eczema, urticaria, angioedema, venom hypersensitivity, anaphylaxis, food allergy, immunotherapy, immune modulators and biologics, animal models of allergic disease, immune mechanisms, or any other topic related to allergic disease.
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