Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlap
Abstract 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. Obj...
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| Format: | Article |
| Language: | English |
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Wiley
2025-04-01
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| Series: | Clinical and Translational Allergy |
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| Online Access: | https://doi.org/10.1002/clt2.70057 |
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| author | Yuning Huang Xue Zhang Jinwen Wang Wuping Bao Chengjian Lv Yingying Zhang Xue Tian Yan Zhou Min Zhang |
| author_facet | Yuning Huang Xue Zhang Jinwen Wang Wuping Bao Chengjian Lv Yingying Zhang Xue Tian Yan Zhou Min Zhang |
| author_sort | Yuning Huang |
| collection | DOAJ |
| description | Abstract 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. Clinical Trial Registration No. ChiCTR2400089625, www.chictr.org.cn. |
| format | Article |
| id | doaj-art-e685ca93252d42dc9495dc2cb4ae507c |
| institution | OA Journals |
| issn | 2045-7022 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Clinical and Translational Allergy |
| spelling | doaj-art-e685ca93252d42dc9495dc2cb4ae507c2025-08-20T02:24:50ZengWileyClinical and Translational Allergy2045-70222025-04-01154n/an/a10.1002/clt2.70057Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlapYuning Huang0Xue Zhang1Jinwen Wang2Wuping Bao3Chengjian Lv4Yingying Zhang5Xue Tian6Yan Zhou7Min Zhang8Department of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaDepartment of Respiratory and Critical Care Medicine Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai ChinaAbstract 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. Clinical Trial Registration No. ChiCTR2400089625, www.chictr.org.cn.https://doi.org/10.1002/clt2.70057acute exacerbationasthma‐COPD overlap impulse oscillometrysmall airway dysfunctionspirometry |
| spellingShingle | Yuning Huang Xue Zhang Jinwen Wang Wuping Bao Chengjian Lv Yingying Zhang Xue Tian Yan Zhou Min Zhang Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlap Clinical and Translational Allergy acute exacerbation asthma‐COPD overlap impulse oscillometry small airway dysfunction spirometry |
| title | Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlap |
| title_full | Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlap |
| title_fullStr | Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlap |
| title_full_unstemmed | Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlap |
| title_short | Role of impulse oscillometry in chronic obstructive pulmonary disease and asthma‐chronic obstructive pulmonary disease overlap |
| title_sort | role of impulse oscillometry in chronic obstructive pulmonary disease and asthma chronic obstructive pulmonary disease overlap |
| topic | acute exacerbation asthma‐COPD overlap impulse oscillometry small airway dysfunction spirometry |
| url | https://doi.org/10.1002/clt2.70057 |
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