Association of metformin with the mortality and incidence of cardiovascular events in patients with pre-existing cardiovascular diseases
Bibliographic record
Abstract
Background and Purpose Whereas whether metformin reduce all-cause, cardiovascular mortality, and incidence of cardiovascular events in patients with cardiac diseases remains inconclusive. Experimental Approach PubMed and Embase were searched up to May 2020 with a registration in PROSPERO (CRD42020189905) were collected. This article includes randomized controlled trials (RCT) and cohort studies. Hazard ratio (HR) with 95% CI was pooled across various trials by a random-effects model. Risk of bias was accounted as per Cochrane and Newcastle-Ottawa Scale (NOS) guidelines. Key Results This article enrolled 48 articles (1999-2020) for qualitative synthesis and identified 26 articles (33 studies in total, 61,704 patients) for final quantitative synthesis. Compared with non-metformin control, metformin is associated with reduced all-cause mortality (HR: 0.90; 95% CI: 0.83, 0.98; P = 0.01), cardiovascular mortality (HR: 0.89; 95% CI: 0.85, 0.94; P < 0.0001), incidence of coronary revascularization (HR: 0.79; 95% CI: 0.64, 0.98; P = 0.03), and heart failure (HR: 0.90; 95% CI: 0.87, 0.94; P < 0.0001) in patients with cardiac diseases, whereas metformin is not associated with reduced incidence of myocardial infarction (HR: 0.97; 95% CI: 0.80, 1.17; P = 0.73), angina (HR: 0.29; 95% CI: 0.04, 2.35; P = 0.25), and stroke (HR: 0.95; 95% CI: 0.78, 1.16; P = 0.59). Conclusion and Implications Metformin reduces all-cause mortality, cardiovascular mortality, incidence of coronary revascularization, and heart failure of patients with cardiac diseases, whereas metformin is not associated with reduced incidence of myocardial infarction, angina, and stroke.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".