Restricted spirometry and cardiometabolic comorbidities: results from the international population based BOLD study
Bibliographic record
Abstract
BACKGROUND: Whether restricted spirometry, i.e. low Forced Vital Capacity (FVC), predicts chronic cardiometabolic disease is not definitely known. In this international population-based study, we assessed the relationship between restricted spirometry and cardiometabolic comorbidities. METHODS: A total of 23,623 subjects (47.5% males, 19.0% current smokers, age: 55.1 ± 10.8 years) from five continents (33 sites in 29 countries) participating in the Burden of Obstructive Lung Disease (BOLD) study were included. Restricted spirometry was defined as post-bronchodilator FVC < 5th percentile of reference values. Self-reports of physician-diagnosed cardiovascular disease (CVD; heart disease or stroke), hypertension, and diabetes were obtained through questionnaires. RESULTS: Overall 31.7% of participants had restricted spirometry. However, prevalence of restricted spirometry varied approximately ten-fold, and was lowest (8.5%) in Vancouver (Canada) and highest in Sri Lanka (81.3%). Crude odds ratios for the association with restricted spirometry were 1.60 (95% CI 1.37-1.86) for CVD, 1.53 (95% CI 1.40-1.66) for hypertension, and 1.98 (95% CI 1.71-2.29) for diabetes. After adjustment for age, sex, education, Body Mass Index (BMI) and smoking, the odds ratios were 1.54 (95% CI 1.33-1.79) for CVD, 1.50 (95% CI 1.39-1.63) for hypertension, and 1.86 (95% CI 1.59-2.17) for diabetes. CONCLUSION: In this population-based, international, multi-site study, restricted spirometry associates with cardiometabolic diseases. The magnitude of these associations appears unattenuated when cardiometabolic risk factors are taken into account.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".