Ticagrelor versus aspirin 2 years after coronary bypass: Observational analysis from the TARGET trial
Bibliographic record
Abstract
BACKGROUND: Compared to conventional aspirin therapy, ticagrelor did not improve vein graft patency 1 year after coronary bypass surgery (CABG) in the ticagrelor antiplatelet therapy to reduce graft events and thrombosis (TARGET) trial. However, it is unknown whether ticagrelor may impact graft patency long-term following surgery. METHODS: In the TARGET multicenter trial, 250 CABG patients were randomized to aspirin 81 mg or ticagrelor 90 mg twice daily. In this observational analysis, 2 years after surgery, vein graft occlusion and clinical events were compared among subjects who agreed to a second year of double-blind study drug administration (N = 156). RESULTS: Two-year graft assessment was performed for 142 patients (80 aspirin patients, 62 ticagrelor patients, 425 total grafts), with an overall 2-year graft occlusion rate of 10.6%. Vein graft occlusion at 2 years, the primary outcome of this study, did not significantly differ between the two groups (15.7% vs. 13.2%, aspirin vs. ticagrelor, p = .71). The incidence of vein grafts with any disease (stenosis or occlusion) did not significantly differ between the groups (19.4% vs. 19.8%, aspirin vs. ticagrelor, p = 1.00), and the number of patients with vein graft disease did not significantly differ between the groups (30.0% vs. 29.0%, aspirin vs. ticagrelor, p = 1.00). Vein grafts developing new disease did not significantly differ between the two groups (1.5% vs. 3.8%, aspirin vs. ticagrelor, p = .41). Freedom from major adverse cardiovascular events at 2 years was similar between the groups (p = .75). CONCLUSION: Compared to conventional aspirin therapy, ticagrelor did not significantly reduce vein graft disease 2 years after CABG.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".