Comparative evaluation of expiratory airflow limitation between patients with COPD and BE using IOS

Impulse oscillometry (IOS) allows evaluation of the compartmentalized resistance and reactance of the respiratory system, distinguishing central and peripheral obstruction. The IOS measurements are getting attention in the diagnosis and differentiation of chronic respiratory diseases. However, no data are available in the literature to differentiate between COPD and BE using IOS parameters. We aimed to evaluate the feasibility of IOS in the diagnosis of bronchiectasis non-cystic fibrosis (BE) in comparison to COPD. Whole breath, inspiration, expiration, and inspiratory-expiratory difference (Delta) were evaluated based on the IOS parameters: total resistance (R5), central airway resistance (R20), peripheral airway resistance (R5-R20), reactance (X5), reactance area (AX), and resonance frequency (Fres). Fifty-nine subjects (21 Healthy, 19 BE, and 19 COPD) participated in this study. It was observed a significant difference in the comparison of healthy and pulmonary disease groups (BE and COPD) for total breathing (R5-R20, X5, AX, and Fres), inspiratory phase (R5 and R5-R5), and expiratory phase (R5-R20 and X5). The comparison between BE and COPD groups showed significant difference in the expiratory phase for resistance at 5 and 20 Hz and, Delta R5 and Delta R20. The IOS evidenced an increase of R5, R20 and R5-R20 in patients with BE and COPD when compared to healthy subjects. Expiratory measures of IOS revealed increased airway resistance in COPD compared to BE patients who had similar FEV1 measured by spirometry, however, further studies are needed to confirm these differences.

Automated summary

IOS is a promising tool for differentiating between healthy individuals and those with respiratory diseases such as bronchiectasis and COPD. Specific parameters of IOS, particularly in the expiratory phase, show significant differences between BE and COPD groups. Further studies are needed to confirm these findings and explore the full potential of IOS in diagnosing and monitoring respiratory diseases.