Ticagrelor and aspirin for the prevention of cardiovascular events after coronary artery bypass graft surgery
Bibliographic record
Abstract
BACKGROUND: Ticagrelor was shown to reduce mortality in patients who underwent coronary artery bypass grafting (CABG), but its effect on graft patency is unknown. METHODS: We performed a prospective, randomised, double-blind, placebo-controlled trial, comparing ticagrelor 90 mg twice daily versus placebo for 3 months added to aspirin 81 mg/day, following isolated CABG. Aspirin was started within 12 h, and study medication within 72 h after CABG. Primary outcome was graft occlusion on CT angiography (CTA) performed 3 months post CABG. Patients were followed to 12 months for death, myocardial infarction, stroke, repeat revascularisation and bleeding. RESULTS: The study was terminated prematurely after randomising 70 patients between September 2011 and August 2014 because of slow recruitment. CTA was performed in 56 patients who completed >1 month of study drug. Graft occlusion occurred in 7/25 (28.0%) patients on ticagrelor and 17/31 (48.3%) on placebo, p=0.044. Of 207 analysable grafts, graft occlusion occurred in 9/87 (10.3%) with ticagrelor and 22/120 (18.3%) with placebo, p=0.112. Graft occlusion or stenosis ≥50% occurred in 10/87 (11.5%) ticagrelor vs 32/120 (26.7%) placebo, p=0.007. There was no major bleeding, but minor bleeding was higher with ticagrelor (31.4% vs 2.9%, p=0.003). In univariate analysis, ticagrelor use reduced graft occlusion (OR 0.32, 95% CI 0.10 to 0.97, p=0.047), which remained significant on multivariable analysis (OR 0.25, 95% CI 0.073 to 0.873, p=0.03). CONCLUSIONS: Ticagrelor added to aspirin after CABG reduced the proportion of patients with graft occlusion, and was a significant univariate and multivariable predictor of graft occlusion. These results are hypothesis-generating and should be confirmed in larger studies. TRIAL REGISTRATION NUMBER: NCT01373411: Results.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".