Exploring Variations in FEV1 and FVC z-Scores: A Methodological Framework to ‘the Elephant in the Room’.

<bold>Background:</bold> FEV1 and FVC and their z-scores (−z), serve as essential parameters to interpret lung function testing results from spirometry, facilitating the stratification of individuals based on airflow obstruction, PRISm, and normal or supra-normal lung function (see Fig. A). The aim of this study is to investigate the variation in FEV1 and FVC by their associations with other lung parameters. <bold>Methods:</bold> Data from the prospective population-based Austrian LEAD study were analyzed from n=14322 participants (age: 38.5±20.8 years, 54% females). FEV1 and FVC data were aligned to represent the variation in both parameters in a perpendicular coordinate system (short/long axis, see Fig. A). Univariate linear models were used to investigate the relationship of FEV1-z, FVC-z, short and long axis with parameters from spirometry, body plethysmography and forced oscillometry technique (FOT, Resmon). <bold>Results:</bold> Data aligned in the long axis elucidated (R²) 91.0% and 90.0% of the variance in FEV1-z and FVC-z, whereas FEV1 reflected only 65.0% of FVC. Data aligned in the short axis explained 95.7% of the variation in FEV1/FVC-z and >60% in MEF25-z and MEF25-75-z (see Fig. B). R² values with lung volumes and FOT reactance (X5) and resistance (R5) were <50%. <bold>Conclusion:</bold> This work highlights the advantage of transforming FEV1-z and FVC-z in line with their variations and evaluates the connections with further lung function parameters. <fig><object-id>erj;64/suppl_68/PA3052/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig>

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Published
2024-09-14
DOI
https://doi.org/10.1183/13993003.congress-2024.pa3052
Primary Topic
Advanced Causal Inference Techniques
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article

Exploring Variations in FEV1 and FVC z-Scores: A Methodological Framework to ‘the Elephant in the Room’.

Robab Breyer‐Kohansal, Tobias Mraz, Emiel F.�M. Wouters, Christoph Gross et al.
Advanced Causal Inference Techniques
article

Exploring Variations in FEV1 and FVC z-Scores: A Methodological Framework to ‘the Elephant in the Room’.

Robab Breyer‐Kohansal, Tobias Mraz, Emiel F.�M. Wouters, Christoph Gross, Marie-Kathrin Breyer, Sylvia Hartl, Charmaine Helk-Lim
article en

Abstract

<bold>Background:</bold> FEV1 and FVC and their z-scores (−z), serve as essential parameters to interpret lung function testing results from spirometry, facilitating the stratification of individuals based on airflow obstruction, PRISm, and normal or supra-normal lung function (see Fig. A). The aim of this study is to investigate the variation in FEV1 and FVC by their associations with other lung parameters. <bold>Methods:</bold> Data from the prospective population-based Austrian LEAD study were analyzed from n=14322 participants (age: 38.5±20.8 years, 54% females). FEV1 and FVC data were aligned to represent the variation in both parameters in a perpendicular coordinate system (short/long axis, see Fig. A). Univariate linear models were used to investigate the relationship of FEV1-z, FVC-z, short and long axis with parameters from spirometry, body plethysmography and forced oscillometry technique (FOT, Resmon). <bold>Results:</bold> Data aligned in the long axis elucidated (R²) 91.0% and 90.0% of the variance in FEV1-z and FVC-z, whereas FEV1 reflected only 65.0% of FVC. Data aligned in the short axis explained 95.7% of the variation in FEV1/FVC-z and >60% in MEF25-z and MEF25-75-z (see Fig. B). R² values with lung volumes and FOT reactance (X5) and resistance (R5) were <50%. <bold>Conclusion:</bold> This work highlights the advantage of transforming FEV1-z and FVC-z in line with their variations and evaluates the connections with further lung function parameters. <fig><object-id>erj;64/suppl_68/PA3052/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig>

Sigmund Freud Privatuniversität Wien (AT), Maastricht University (NL), Klinik Hietzing (AT)
Openalex Percentile: Top 80%
Advanced Causal Inference Techniques
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