Mortality and cardiovascular and respiratory morbidity in individuals with impaired FEV1 (PURE): an international, community-based cohort study
Bibliographic record
Abstract
Background The associations between the extent of forced expiratory volume in 1 s (FEV 1 ) impairment and mortality, incident cardiovascular disease, and respiratory hospitalisations are unclear, and how these associations might vary across populations is unknown. Methods In this international, community-based cohort study, we prospectively enrolled adults aged 35–70 years who had no intention of moving residences for 4 years from rural and urban communities across 17 countries. A portable spirometer was used to assess FEV 1 . FEV 1 values were standardised within countries for height, age, and sex, and expressed as a percentage of the country-specific predicted FEV 1 value (FEV 1 %). FEV 1 % was categorised as no impairment (FEV 1 % ≥0 SD from country-specific mean), mild impairment (FEV 1 % <0 SD to −1 SD), moderate impairment (FEV 1 % <–1 SD to −2 SDs), and severe impairment (FEV 1 % <–2 SDs [ie, clinically abnormal range]). Follow-up was done every 3 years to collect information on mortality, cardiovascular disease outcomes (including myocardial infarction, stroke, sudden death, or congestive heart failure), and respiratory hospitalisations (from chronic obstructive pulmonary disease, asthma, pneumonia, tuberculosis, or other pulmonary conditions). Fully adjusted hazard ratios (HRs) were calculated by multilevel Cox regression. Findings Among 126 359 adults with acceptable spirometry data available, during a median 7·8 years (IQR 5·6–9·5) of follow-up, 5488 (4·3%) deaths, 5734 (4·5%) cardiovascular disease events, and 1948 (1·5%) respiratory hospitalisation events occurred. Relative to the no impairment group, mild to severe FEV 1 % impairments were associated with graded increases in mortality (HR 1·27 [95% CI 1·18–1·36] for mild, 1·74 [1·60–1·90] for moderate, and 2·54 [2·26–2·86] for severe impairment), cardiovascular disease (1·18 [1·10–1·26], 1·39 [1·28–1·51], 2·02 [1·75–2·32]), and respiratory hospitalisation (1·39 [1·24–1·56], 2·02 [1·75–2·32], 2·97 [2·45–3·60]), and this pattern persisted in subgroup analyses considering country income level and various baseline risk factors. Population-attributable risk for mortality (adjusted for age, sex, and country income) from mildly to moderately reduced FEV 1 % (24·7% [22·2–27·2]) was larger than that from severely reduced FEV 1 % (3·7% [2·1–5·2]) and from tobacco use (19·7% [17·2–22·3]), previous cardiovascular disease (5·5% [4·5–6·5]), and hypertension (17·1% [14·6–19·6]). Population-attributable risk for cardiovascular disease from mildly to moderately reduced FEV 1 was 17·3% (14·8–19·7), second only to the contribution of hypertension (30·1% [27·6–32·5]). Interpretation FEV 1 is an independent and generalisable predictor of mortality, cardiovascular disease, and respiratory hospitalisation, even across the clinically normal range (mild to moderate impairment). Funding Population Health Research Institute, the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, Ontario Ministry of Health and Long-Term Care, AstraZeneca, Sanofi-Aventis, Boehringer Ingelheim, Servier, and GlaxoSmithKline, Novartis, and King Pharma. Additional funders are listed in the appendix.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".