Gaps in knowledge and future needs in defining the clinical applications of oscillometry
| Area of need | What we think we know | Identified gaps/research questions |
| Harmonisation of oscillometry devices [3] | Different metrics between commercial devices as measured impedance is increased. | Established standard testing procedures to compare devices. Encourage manufacturers to revise hardware and firmware/software design. |
| Normative values | Multiple reference populations to determine “normal”, separate for children and adults. | Large, multicentre studies to determine multi-ethnic population normal values across all ages, equivalent to the Global Lung Function Initiative. |
| Minimal clinically important change | Short-term test variability over minutes and days; coefficient of repeatability values in children and adults. Longitudinal data in healthy people to understand variability and changes through life. | Correlations with clinical progression in disease populations. Minimally clinically important changes for each oscillometry index, which likely vary with disease and treatment. |
| Bronchodilator response | Cut-offs for significant bronchodilator responses, expressed for multiple indices in different ways, from individual studies in healthy people. Good discrimination between health and asthma. Higher sensitivity than spirometry in terms of response and identifying responders. Higher sensitivity than spirometry in identifying individuals with poor asthma control. | Determine the most useful way to express bronchodilator responses in the clinic. Consistency of such responses within subjects over time. Further studies on clinical correlates of bronchodilator responses, in both healthy and disease populations across all ages. |
| Standardisation of bronchial challenge testing protocol | Good feasibility in younger age groups. Variability across studies in terms of cut-offs. Higher sensitivity than spirometry in terms of response and identifying responders. | Determine value added to hyperresponsiveness measured by spirometry. Determine standardised cut-offs for the range of challenge agents. Potential feasibility of shorter protocols. |
| Phenotyping in obstructive diseases | Correlations of specific indices with symptoms, imaging and spirometry in terms of baseline measures, changes in response to treatment and prediction of treatment response. | Determine which indices provide the most clinically relevant information by reporting comprehensive, head-to-head comparison across the full range of indices, within disease populations, including patient-centred outcomes. Explore the role of new indices, such as those obtained from within-breath measurements. Sensitivity analyses within disease populations for oscillometry indices. Comprehensive studies correlating oscillometry measures with other phenotyping tools, such as lung imaging and histology. Determine correlations with known and emerging biomarkers of disease, particularly in response to treatment. |
| Grading severity of abnormalities | No data. | Assess degrees of deviation from normal in relation to statistical variation and clinical outcomes. |
| Home monitoring | Potential marker of airway instability in asthma. Sensitive detector of exacerbations in COPD, and utility as guide for intervention in subset of COPD patients (those with previous hospitalisation). | Role in exacerbation detection and guide for intervention in asthma. Role in prediction of disease progression and responses to treatment in asthma and COPD. Utility in other diseases. |
| Emerging clinical applications | Potential role in identifying lung function deficits in preterm children. Limited utility demonstrated thus far in cystic fibrosis in children, less data in adults. Potential role in detecting early changes in smokers. Potential utility in identifying pathological changes in obesity. Potential in monitoring progression after environmental exposures. Potential in diagnosis of vocal cord dysfunction. Potential role in titrating level of respiratory support in sleep and in COPD patients in the intensive care setting. Potential in identifying clinical progression in lung and bone marrow transplant patients, as well as interstitial lung disease and neuromuscular disease. | Larger clinical studies beyond proof of concept. Potential for aerosol generation to stratify risk of preventing spread of infection compared to spirometry. |