Respiratory Impedance Prediction in Children and Adolescents: A Meta-Modelling Approach
Abstract Respiratory oscillometry provides a simple, noninvasive method for assessing pulmonary function in children and is particularly sensitive to small airway obstruction. But its clinical application remains limited due to the lack of widely accepted reference values. In this study, we developed generalized meta-model equations for respiratory resistance and reactance at 5 Hz in children and adolescents using synthetic data generated from published paediatric oscillometric reference equations. A total of 25 reference equations reported since 2000 were analysed to identify the demographic and methodological factors contributing to variability among existing prediction models. Subsequently, a synthetic dataset comprising 70 healthy children and adolescents aged 2–19 years was generated using physiologically realistic anthropometric combinations derived from established paediatric growth references. Pearson correlation analysis revealed that height, age, and weight were significantly associated with both resistance and reactance, and variance inflation factor analysis indicated strong multicollinearity among these variables. Despite differences among published equations, strong agreement was observed across studies, with correlation coefficients exceeding 0.95 for resistance equations and 0.92 for reactance equations, and most predictions remaining within a ± 30% tolerance range. Stepwise multivariable regression was then used to develop generalized meta-model equations, yielding coefficients of determination of approximately 0.84 for both resistance and reactance at 5Hz. The proposed meta-models were further evaluated across different airway impairment states and bronchodilator responses, demonstrating their ability to preserve physiologically meaningful variations in respiratory resistance and reactance. Collectively, these findings support the proposed meta-models as a standardized framework for paediatric respiratory impedance at 5Hz.
Authors
- Mathias Baumert (ORCID: https://orcid.org/0000-0003-2984-2167)
- Md. Mokammel Haque (ORCID: https://orcid.org/0000-0003-3396-6568)
- Anuva Chowdhury (ORCID: https://orcid.org/0000-0002-2246-2228)
Publication Details
- Journal
- Annals of Biomedical Engineering
- Published
- 2026-10-18
- DOI
- https://doi.org/10.1007/s10439-026-04323-2
- Primary Topic
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00