Cargando…

The Value of Impulse Oscillometric Parameters and Quantitative HRCT Parameters in Differentiating Asthma–COPD Overlap from COPD

PURPOSE: To evaluate the value of impulse oscillometry (IOS) and quantitative HRCT parameters for differentiating asthma–COPD overlap (ACO) in COPD patients. PATIENTS AND METHODS: We enrolled 44 controls and 66 COPD patients, divided into the pure COPD group (n=40) and the ACO group (n=26). Spearman...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Dongzhu, Chen, Lichang, Fan, Chaofan, Zeng, Wenyi, Fan, Huizhen, Wu, Xiping, Yu, Huapeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541739/
https://www.ncbi.nlm.nih.gov/pubmed/34703222
http://dx.doi.org/10.2147/COPD.S331853
Descripción
Sumario:PURPOSE: To evaluate the value of impulse oscillometry (IOS) and quantitative HRCT parameters for differentiating asthma–COPD overlap (ACO) in COPD patients. PATIENTS AND METHODS: We enrolled 44 controls and 66 COPD patients, divided into the pure COPD group (n=40) and the ACO group (n=26). Spearman correlation analysis was utilized to assess the relationship between the quantitative HRCT and IOS parameters. A binary logistic regression analysis was performed to analyze the associations between the different variables and the risk of ACO. Receiver operating characteristic (ROC) curves were employed to identify the optimal cutoff and assess the diagnostic value of relative volume change −856 HU to −950 HU (RVC(−856 to −950)), decrease in the resistance from 5 Hz to 20 Hz (R5-R20) and their combination in predicting ACO. Bootstrapping validation was used to evaluate the internal validation. The concordance index (C-index) and calibration plot were calculated to assess the discrimination and calibration of the prediction model. RESULTS: Binary logistic regression analysis indicated that RVC(−856 to −950) and the IOS parameters (R5-R20, R5, X5) were independently correlated with a higher risk of developing ACO after adjusting for age, sex, body mass index (BMI), history of smoking, exacerbation and atopy or allergic rhinitis. A correlation analysis showed a good correlation between the pulmonary function parameters and RVC(−856 to −950), with a weaker correlation with the % area of low attenuation (LAA%) in ACO patients. Combining RVC(−856 to −950) and R5-R20 to predict ACO, the AUC was 0.909, and the optimal cutoff value was >-0.62 for RVC(−856 to −950) and >0.09 for R5-R20. Good calibration and favorable discrimination were displayed with a higher C-index. CONCLUSION: More serious small airway impairment exists in ACO patients. The combination of RVC(−856 to −950) and R5-R20 could be applied to differentiate ACO from COPD patients.