Association between lung function and dyspnoea and its variation in the multinational Burden of Obstructive Lung Disease (BOLD) study
Bibliographic record
Abstract
Dyspnoea is a common symptom of respiratory disease. However, data on its prevalence in general populations and its association with lung function are limited and are mainly from high-income countries. The aims of this study were to estimate the prevalence of dyspnoea across several world regions, and to investigate the association of dyspnoea with lung function. Dyspnoea was assessed, and lung function measured in 25,806 adult participants of the multinational Burden of Obstructive Lung Disease study. Dyspnoea was defined as ≥2 on the modified Medical Research Council (mMRC) dyspnoea scale. The prevalence of dyspnoea was estimated for each of the study sites and compared across countries and world regions. Multivariable logistic regression was used to assess the association of dyspnoea with lung function in each site. Results were then pooled using random-effects meta-analysis. The prevalence of dyspnoea varied widely across sites without a clear geographical pattern. The mean prevalence of dyspnoea was 13.7 % (SD=8.2 %), ranging from 0 % in Mysore (India) to 28.8 % in Nampicuan-Talugtug (Philippines). Dyspnoea was strongly associated with both spirometry restriction (FVC<LLN: OR 2.07, 95 %CI 1.75–2.45) and spirometry airflow obstruction (FEV1/FVC
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".