Asthma and the risk of cardiovascular diseases and mortality: a meta-analysis of cohort studies
Bibliographic record
Abstract
BACKGROUND: It has been shown that asthma is potentially linked to a higher risk of cardiovascular disease (CVD) and cardiovascular mortality (CVM). OBJECTIVES: This study aims to systematically review and summarize epidemiological evidence on the relationship between asthma and these cardiovascular outcomes. DESIGN: Systematic review and meta-analysis. DATA SOURCES AND METHODS: This meta-analysis, registered with PROSPERO (CRD 42024576126), utilized data from PubMed, Embase, the Cochrane Library, and references from included studies. The search covered literature from the inception of these databases until July 17, 2024. We included observational studies examining the link between asthma and CVD and CVM. Bias risk was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS). We calculated pooled relative risk (RR) with a 95% confidence interval (CI) using a random-effects model. RESULTS: A total of 29 studies encompassing 11,380,027 participants were included. The overall risk for CVD in asthma patients was 1.30 (95% CI: 1.20-1.42). Specific CVD risks were elevated for coronary heart disease (CHD, RR 1.35; 95% CI: 1.27-1.42), angina pectoris (AP, RR 1.48; 95% CI: 1.16-1.89), myocardial infarction (MI, RR 1.33; 95% CI: 1.25-1.41), and heart failure (HF, RR 1.53; 95% CI: 1.04-2.23). Asthma was also associated with a higher risk of CVM (RR 1.26; 95% CI: 1.05-1.51). CONCLUSION: Asthma is associated with a higher risk of developing CVD, including specific types such as CHD, AP, MI, and HF. In addition, asthma patients face an increased risk of cardiovascular mortality compared to non-asthmatics.
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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 | 0.029 | 0.045 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.066 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".