The Global Lung Function Initiative: dispelling some myths of lung function test interpretation
Bibliographic record
Abstract
Educational Aims To summarise limitations and implications associated with using outdated spirometry reference equations to interpret lung function. To describe the Quanjeret al., 2012 “Global Lung Function Initiative” (GLI) spirometry equations and the advantages of using these in both clinical practice and research studies. To discuss the necessary steps and challenges when switching to the GLI, including adjustment for ethnicity, re-calculation of previous results for accurate trend reports and education of both patients and professionals. Summary Lung function results can help with establishing a diagnosis, with assessment of treatment effects and with making a prognosis. However, arbitrary differences in the way lung function is expressed and interpreted may result in mismanagement of patients as well as hindering our understanding of the global burden of lung disease. In this article, we summarise the Global Lung Function Initiative spirometry reference equations and dispel some common myths related to the use and interpretation of spirometry results.
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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 | 0.200 | 0.295 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.037 |
| Scholarly communication | 0.010 | 0.023 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.010 | 0.050 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".