Adding oscillometry to spirometry in guidelines better identifies uncontrolled asthma, future exacerbations, and potential targeted therapy

Predictive Value of Impulse Oscillometry Combined with Fractional Expiratory Nitric Oxide Test for Asthma in Preschool Children

Objective

Prediction of asthma in preschool children is challenging and lacks objective indicators. The aim is to observe and analyze the variances between impulse oscillometry (IOS) and fractional expiratory nitric oxide (FeNO) in preschool children with wheezing, establish a joint prediction model, and explore the diagnostic value of combining IOS with FeNO in diagnosing asthma among preschool children.

Patients and methods

This study enrolled children aged 3-6 years with wheezing between June 2021 and June 2022. They were categorized as asthmatic (n=104) or non-asthmatic (n=109) after a 1-year follow-up. Clinical data, along with IOS and FeNO measurements from both groups, underwent univariate regression and multiple regression analyses to identify predictive factors and develop the most accurate model. The prediction model was built using the stepwise (stepAIC) method. The receiver operating characteristic curve (ROC), calibration curve, Hosmer-Lemeshow test, and decision curve analysis (DCA) were employed to validate and assess the model.

Results

During univariate analysis, a history of allergic rhinitis, a history of eczema or atopic dermatitis, and measures including FeNO, R5, X5, R20, Fres, and R5-R20 were found to be associated with asthma diagnosis. Subsequent multivariate analysis revealed elevated FeNO, R5, and X5 as independent risk factors. The stepAIC method selected five factors (history of allergic rhinitis, history of eczema or atopic dermatitis, FeNO, R5, X5) and established a prediction model. The combined model achieved an AUROC of 0.94, with a sensitivity of 0.89 and specificity of 0.88, surpassing that of individual factors. Calibration plots and the HL test confirmed satisfactory accuracy.

Conclusion

This study has developed a prediction model based on five factors, potentially aiding clinicians in early identification of asthma risk among preschool children.

The role of oscillometry in asthma

PURPOSE OF REVIEW

Oscillometry is a noninvasive pulmonary function test that has gained significant interest in the evaluation of lung disease. Currently, oscillometry is primarily a research tool, but there is a growing body of evidence supporting its clinical use. This review describes the recent work evaluating the role of oscillometry in the diagnosis and treatment of asthma.

RECENT FINDINGS

A large body of observational data supports the ability of oscillometry to distinguish healthy individuals from those with respiratory symptoms or lung disease. Oscillometry may not be as useful as an isolated diagnostic test in asthma, but the combination with other pulmonary function tests may improve its diagnostic ability. Oscillometry can detect peripheral airways dysfunction in asthma, which is associated with symptoms and the risk for exacerbations. To help guide future research, minimal clinically important differences for specific oscillometry variables have been developed. Oscillometry may be useful in monitoring the response to biological therapy and has potential for personalizing treatment for individual patients. Oscillometry also has potential in uncovering unique aspects of the pathophysiology of asthma in obesity.

SUMMARY

Oscillometry is a promising tool in the diagnosis and management of asthma. More research is needed to support its routine clinical use.