The sustained increase of cardiovascular risk following COPD exacerbations: meta-analyses of the EXACOS-CV studies
Bibliographic record
Abstract
Background The EXAcerbations of COPD and their OutcomeS on CardioVascular disease (EXACOS-CV) multi-database studies have consistently shown an increased risk of serious cardiovascular event following COPD exacerbations, but with some risk temporality variations. EXACOS-CV results were meta-analysed to increase their generalisability and improve precision. Methods Studies conducted in Canada, the United States, Germany, the Netherlands, Spain, Italy, Japan and England were meta-analysed, amounting to 1 030 875 individuals. Generally, each study included individuals aged ≥40 years with a COPD diagnosis in 2014–2019; primary outcome was the composite of non-fatal acute coronary syndrome, decompensated heart failure, ischaemic stroke, arrhythmias and all-cause death. Pooled hazard ratios (HR p ) of risks in post-exacerbation periods ( versus periods outside exacerbations) were obtained through random effects meta-analysis. Results Time periods following an exacerbation (any severity) were associated with increased and sustained risks of the composite outcome: HR p 10.22 (95% CI 5.34–19.57) in days 1–7 and HR p 1.24 (95% CI 1.09–1.40) in days 181–365. Risks were elevated for 6 months (HR p 1.25, 95% CI 1.01–1.55 in days 31–180) and 1 year (HR p 1.48, 95% CI 1.11–1.96 in days 181–365) following a moderate or a severe exacerbation, respectively. In newly diagnosed individuals, risks were increased until days 31–180: HR p 1.66 (95% CI 1.14–2.42) and HR p 1.61 (95% CI 1.28–2.02) following the first and the second post-diagnosis exacerbation, respectively. Conclusion Risk of severe cardiovascular events is sustainably increased following an exacerbation of COPD, even early and moderate ones. Cardiopulmonary risk reduction should be a global core target of COPD management.
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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 | 0.022 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.052 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".