Spirometric Reference Values for Advanced Age from a South German Population
Bibliographic record
Abstract
BACKGROUND: The diagnostic use of lung function using spirometry depends on the validity of reference equations. A multitude of spirometric prediction values have been published, but in most of these studies older age groups are underrepresented. OBJECTIVES: The aim of the present study was to establish new spirometric reference values for advanced age and to compare these to recent prediction equations from population-based studies. METHODS: In the present study spirometry was performed in a population-based sample from the KORA-F4 and KORA-Age cohorts (2006-2009, Augsburg, Germany) comprising 592 never-smoking subjects aged 42-89 years and with no history of respiratory disease. Using quantile regression analysis, equations for the median and lower limit of normal were derived for indices characterizing the expiratory flow-volume curve: forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, peak expiratory flow (PEF), and forced expiratory flow rates at 25, 50 and 75% of exhaled FVC (FEF25, FEF50 and FEF75). RESULTS: FEV1 and FVC were slightly higher, and PEF was lower compared to recently published equations. Importantly, forced expiratory flow rates at middle and low lung volume, as putative indicators of small airway disease, were in good agreement with recent data, especially for older age. CONCLUSION: Our study provides up-to-date reference equations for all major indices of flow-volume curves in middle and advanced age in a South German population. The small deviations from published equations indicate that there might be some regional differences of lung function within the Caucasian population of advanced age in Europe.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".