Comparative Benefits of Clopidogrel and Aspirin in High-Risk Patient Populations
Bibliographic record
Abstract
Clopidogrel has been evaluated in clinical trials that included cardiovascular patients with different risk levels for a cardiovascular event. We reviewed the results of the Clopidogrel vs Aspirin in Patients at Risk of Ischemic Events (CAPRIE) and Clopidogrel in Unstable Angina to Prevent Recurrent Events (CURE) trials, with special emphasis on comparing the outcomes in high-risk patients with those of the total populations in the trials. The results in the high-risk subgroups and total populations were compared by recording total event rates, absolute risk reduction, relative risk reduction, and number needed to treat. In the CAPRIE trial, the efficacy of clopidogrel was compared with acetylsalicylic acid (ASA) in the following subgroups: total population, previous coronary bypass surgery, history of more than 1 ischemic event, multiple vascular beds involvement, diabetes, and hypercholesterolemia. In the CURE trial, the combination of clopidogrel and ASA was compared with ASA alone. The results in the CURE study were compared in patients who did and did not have a coronary intervention procedure, in patients with different levels of risk based on the Thrombolysis in Myocardial Infarction score and in patients with and without a history of a revascularization procedure. High-risk subgroups of patients participating in the CAPRIE and CURE studies were more responsive to the beneficial effects of clopidogrel compared with the study population as a whole. High-risk groups in the CAPRIE and CURE studies would be expected to derive enhanced benefit from treatment with clopidogrel over that achieved by ASA.
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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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".