Heightened long-term cardiovascular risks after exacerbation of chronic obstructive pulmonary disease
Bibliographic record
Abstract
OBJECTIVE: To examine the risk of adverse cardiovascular (CV) events following an exacerbation of chronic obstructive pulmonary disease (COPD). METHODS: This retrospective cohort study identified patients with COPD using administrative data from Alberta, Canada from 2014 to 2019. Exposure periods were 12 months following moderate or severe exacerbations; the reference period was time preceding a first exacerbation. The primary outcome was the composite of all-cause death or a first hospitalisation for acute coronary syndrome, heart failure (HF), arrhythmia or cerebral ischaemia. Time-dependent Cox regression models estimated covariate-adjusted risks associated with six exposure subperiods following exacerbation. RESULTS: Among 1 42 787 patients (mean age 68.1 years and 51.7% men) 61 981 (43.4%) experienced at least one exacerbation and 34 068 (23.9%) died during median follow-up of 64 months. The primary outcome occurred in 43 564 (30.5%) patients with an incidence rate prior to exacerbation of 5.43 (95% CI 5.36 to 5.50) per 100 person-years. This increased to 95.61 per 100 person-years in the 1-7 days postexacerbation (adjusted HR 15.86, 95% CI 15.17 to 16.58) and remained increased for up to 1 year. The risk of both the composite and individual CV events was increased following either a moderate or a severe exacerbation, though greater and more prolonged following severe exacerbation. The highest magnitude of increased risk was observed for HF decompensation (1-7 days, HR 72.34, 95% CI 64.43 to 81.22). CONCLUSION: Moderate and severe COPD exacerbations are independent risk factors for adverse CV events, especially HF decompensation. The impact of optimising COPD management on CV outcomes should be evaluated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".