Acetylsalicylic Acid (Aspirin) for Primary Prevention of CardiovascularEvents in Patients with Diabetes: A Systematic Review and Meta-Analysisof Randomized Controlled Trials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.074 | 0.038 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it