Global lung function initiative reference values for cardiopulmonary exercise testing
Bibliographic record
Abstract
Background: Cardiopulmonary exercise testing (CPET) is used to assess individuals' physiological responses to exercise and to identify potential causes of exercise limitation. Aims and objectives: This study aimed to derive Global Lung Function Initiative (GLI) reference equations for peak oxygen uptake (V'O2peak) and peak work rate (Wpeak) in healthy individuals. Methods: CPET data were retrospectively collected from sites and underwent checks for consistency and quality. Generalised additive models of location, shape and scale (GAMLSS) were used to develop reference ranges, including age, sex, height, and weight as explanatory variables. The influence of geographic region, equipment, testing protocols and averaging methods for peak exercise data on the derived reference ranges was also examined. Results: Data from 6047 healthy individuals between 6 and 83 years across 17 sites in Europe, North and South America, and Asia were analysed. The final models explained 68.9% and 67.5% of the variability in V'O2peak and Wpeak, respectively. Variations persisted by site despite adjusting for key demographic factors. Geographic region, metabolic cart type, and averaging methods of peak exercise values improved model fit but were impractical as predictors for developing reference ranges. Conclusion: Significant heterogeneity in CPET testing methodology and outcomes between sites precluded the development of generalised reference ranges for V'O2peak and Wpeak. Further prospective studies with standardised CPET protocols and analytical methods are needed to reduce variability and establish robust, clinically meaningful interpretation strategies.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".