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Updated: Aug 24, 2025
Conducting Respiratory Oscillometry in an Outpatient Setting
Published on: April 8, 2022
Clinical application of oscillometry in respiratory diseases: an impulse oscillometry registry
Xiaolin Liang1, Jinping Zheng1, Yi Gao1
1National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Background:
Respiratory oscillometry is a promising complement to the traditional pulmonary function tests for its simplicity. The usefulness of oscillometry in adult clinical practice has not been clarified. This study aimed to analyse the characteristics and diagnostic performance of oscillometry in respiratory diseases, and explore the cut-offs of oscillometric parameters for severity grading.
Methods:
In this multicentre registry of impulse oscillometry (IOS), IOS and spirometric data of healthy individuals and patients with respiratory diseases were collected and analysed. Linear mixed model analysis was performed to explore the effects of disease and forced expiratory volume in 1 s (FEV1) on oscillometric parameters.
Results:
The study included 567 healthy subjects, 781 asthmatic patients, 688 patients with chronic obstructive pulmonary disease (COPD), 109 patients with bronchiectasis, 40 patients with upper airway obstruction (UAO) and 274 patients with interstitial lung disease (ILD) in the analysis. Compared at the same FEV1 level, asthma, COPD, bronchiectasis, UAO and ILD displayed different oscillometric characteristics. The z-score of resistance at 5 Hz (R 5) was the best variable to identify respiratory diseases with a sensitivity of 62.4-66.7% and a specificity of 81.5-90.3%. With reference to the severity grading cut-offs of FEV1, R 5 z-scores of 2.5 and 4 were defined as the cut-off values of moderately and severely increased R 5.
Conclusion:
Respiratory oscillometry is more appropriate to be a tool of evaluating, rather than of diagnosing, respiratory diseases. A severity grading system of oscillometric parameters was developed to help the interpretation of oscillometry in clinical practice.
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