Acetylsalicylic Acid (Aspirin) for Primary Prevention of CardiovascularEvents in Patients with Diabetes: A Systematic Review and Meta-Analysisof Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Evidence regarding using acetylsalicylic acid (aspirin) for the prevention of cardiovascular (CV) events in patients with diabetes mellitus (DM) is inconsistent. Therefore, we performed a meta-analysis. METHODS: A literature search was performed (January 1990 to February 2022) and publications meeting the inclusion criteria were reviewed, and a meta-analysis was performed using RevMan software. The primary outcome was a composite of CV death, non-fatal myocardial infarction (MI) and stroke. Secondary outcomes included all-cause mortality, individual components of the primary outcome and major bleeding. RESULTS: The study cohort comprised 33525 diabetic patients from 9 randomized controlled trials. The primary outcome was significantly lower for aspirin vs. placebo (7.9 vs. 8.6, RR (risk ratio) 0.92, 95% CI (confidence interval) 0.86-0.99). All-cause mortality (10 vs. 10.3%, RR 0.97, 95% CI 0.90-1.03), CV death (4.4 vs. 4.7%, RR 0.93, 95% CI 0.83-1.04), non-fatal MI (4.6 vs. 4.8% RR 0.97, 95% CI 0.83- 1.15) and stroke (3.2 vs. 3.5%, RR 0.89, 95% CI 0.75-1.06) were similar between the two treatment groups. Major bleeding was significantly higher for aspirin compared with placebo (3.4 vs. 2.8%, RR 1.18, 95% CI 1.01-1.39). CONCLUSION: Aspirin use in patients with DM reduces the composite endpoint of CV death, non-fatal MI and stroke compared with a placebo. However, routine use of aspirin for primary prevention among diabetic patients cannot be advised due to the increased risk of major bleeding. These findings suggest careful risk assessment of individual patients.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".