Reference equations using segmented regressions for impulse oscillometry in healthy subjects aged 2.7-90 years

Area of Science:

• Pulmonary Function Testing
• Respiratory Physiology
• Biostatistics

Background:

• Existing impulse oscillometry (IOS) reference equations often cover limited age ranges, leading to inconsistencies in predicted lung function values.
• This age-specific limitation can cause discrepancies when assessing individuals across different age groups or as they transition between equations.
• A unified approach is needed for accurate IOS interpretation throughout the lifespan.

Purpose of the Study:

• To develop a single, comprehensive reference equation for impulse oscillometry (IOS) variables.
• To create equations applicable from infancy through old age, addressing limitations of current age-specific references.
• To provide a standardized tool for lung function assessment across the entire lifespan.

Main Methods:

• An ambispective cross-sectional study was conducted on 830 healthy, non-smoking adults and children.
• Impulse oscillometry (IOS) was performed following international standards.
• Multivariate piecewise linear regression (segmented regression) was employed to derive new reference equations.

Main Results:

• Segmented regression identified age-related breakpoints for most IOS variables, with one breakpoint for R5-R20.
• Multivariate regressions incorporated sex, age, height, and body mass index (BMI) as predictors.
• Coefficients were generated for calculating predicted values, limits of normal, percentage of predicted, and z-scores.

Conclusions:

• The study successfully generated IOS reference equations applicable from childhood to old age.
• These equations integrate key determinants of lung function: sex, age, height, and BMI.
• The developed equations offer a practical and consistent method for interpreting IOS results across diverse age groups.