Bibliographic record
Abstract
Question: Is a history of pre-existing atherothrombotic disease associated with an increased risk of subsequent ischemic events, and is it associated with a reduction in efficacy of clopidogrel? Population: Patients with recent ischemic stroke (IS), myocardial infarction (MI), or established peripheral arterial disease, and a history of pre-existing symptomatic atherothrombotic disease (IS and=or MI) were enrolled in the Clopidogrel versus Aspirin in Patients at Risk of Ischemic Events (CAPRIE) trial. CAPRIE was a randomized, blinded, clinical trial comparing the efficacy of clopidogrel with aspirin in patients at risk of ischemic events. Design and methods: Retrospective, subgroup analysis of 4496 patients with a prior history of symptomatic atherothrombotic disease from the CAPRIE study. Results: Compared with the overall population of CAPRIE, patients with pre-existing symptomatic atherothrombotic disease have elevated rates of IS, MI, or vascular death. The 3-year rates of IS, MI, or vascular death were 20.4% with clopidogrel and 23.8% with aspirin (absolute risk reduction: 3.4%; 95% CI: -0.2 to 7.0; number needed to treat: 29; relative risk reduction: 14.9% (95% CI: 0.3 to 27.3; p = 0.045)). Conclusion: Patients with a history of previous symptomatic atherothrombotic disease suffer a high rate of subsequent ischemic events. Among these patients, the absolute risk reduction of clopidogrel over aspirin is greater compared with patients without pre-existing atherothrombotic disease.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.215 | 0.112 |
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".