Safety and Efficacy of Aspirin and Indobufen in the Treatment of Atherosclerotic Diseases: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The pathogenesis of atherosclerotic thrombosis primarily involves platelet activation and aggregation, making antiplatelet therapy the cornerstone of treatment for such diseases. Objective: This meta-analysis aimed to compare the safety and efficacy of aspirin and indobufen in antiplatelet therapy for patients with atherosclerotic diseases. Methods: We searched the Cochrane Library, PubMed, Embase, Web of Science, and the Chinese Wanfang databases. The literature was screened according to predefined inclusion and exclusion criteria. Risk ratio (RR) was used to assess the magnitude of risk associated with exposure and our inclusion criteria are as follows: (1) the study population comprised adults (aged 18 years and older) with coronary heart disease caused by coronary artery atherosclerosis or stroke caused by intracranial atherosclerosis; (2) the intervention was represented by indobufen in the study groups versus aspirin in the control groups; (3) the primary outcome was the incidence of major adverse cardiovascular and cerebrovascular events or any bleeding or Bleeding Academic Research Consortium 2/3/5 bleeding; (4) the secondary outcomes were cardiovascular death, myocardial infarction, and ischemic stroke; adverse cardiovascular events such as coronary thrombus reformation, heart failure, myocardial infarction, stroke, angina pectoris, and cardiovascular death; stroke; myocardial infarction; and cardiovascular death; and (5) the studies were randomized clinical trials with either crossover or parallel designs or prospective observational trials. Results: Eighteen trials with a total of 12,981 patients were included in this study. Compared to aspirin, indobufen reduced the risk of (1) bleeding events (RR 0.54, 95% CI 0.41-0.71; P<.0001), (2) Bleeding Academic Research Consortium 2/3/5 bleeding (RR 0.50, 95% CI 0.26-0.94; P=.03), (3) adverse cardiovascular events (RR 0.43, 95% CI 0.30-0.61; P<.00001), and (4) myocardial infarction (RR 0.60, 95% CI 0.41-0.89; P=.01). However, there were no significant differences between the 2 groups in terms of major adverse cardiovascular and cerebrovascular events, stroke, or cardiovascular mortality. Conclusions: Compared with aspirin, indobufen demonstrated better safety and was not inferior to aspirin in terms of efficacy, with superior results in some aspects (eg, fewer risks of adverse cardiovascular events and myocardial infarction). Further studies with larger sample sizes or longer follow-up periods may provide additional evidence.
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How this classification was reachedexpand
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".