Diabetes Mellitus and Prevention of Late Myocardial Infarction After Coronary Stenting in the Randomized Dual Antiplatelet Therapy Study
Bibliographic record
Abstract
BACKGROUND: Patients with diabetes mellitus (DM) are at high risk for recurrent ischemic events after coronary stenting. We assessed the effects of continued thienopyridine among patients with DM participating in the Dual Antiplatelet Therapy (DAPT) Study as a prespecified analysis. METHODS AND RESULTS: After coronary stent placement and 12 months treatment with open-label thienopyridine plus aspirin, 11 648 patients free of ischemic or bleeding events and who were medication compliant were randomly assigned to continued thienopyridine or placebo, in addition to aspirin, for 18 more months. After randomization, patients with DM (n=3391), in comparison with patients without DM (n=8257), had increased composite outcome of death, myocardial infarction (MI), or stroke (6.8% versus 4.3%, P<0.001), increased death (2.5% versus 1.4%, P<0.001), and MI (4.2% versus 2.6%, P<0.001). Among patients with DM, in a comparison of continued thienopyridine versus placebo, rates of stent thrombosis were 0.5% versus 1.1%, P=0.06, and rates of MI were 3.5% versus 4.8%, P=0.058; and among patients without DM the rates were 0.4% versus 1.4%, P<0.001 (stent thrombosis, P interaction=0.21) and 1.6% versus 3.6%, P<0.001 (MI, P interaction=0.02). Bleeding risk with continued thienopyridine was similar among patients with or without DM (interaction P=0.61). CONCLUSIONS: In patients with DM, continued thienopyridine beyond 1 year after coronary stenting is associated with reduced risk of MI, although this benefit is attenuated in comparison with patients without DM. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00977938.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".