Impact of ticagrelor with or without aspirin on total and recurrent bleeding and ischaemic events after percutaneous coronary intervention: a sub-study of the TWILIGHT trial
Bibliographic record
Abstract
AIMS: In standard time-to-first event analysis, early aspirin discontinuation followed by ticagrelor monotherapy has been shown to reduce bleeding without increasing ischaemic complications compared with ticagrelor plus aspirin after percutaneous coronary intervention (PCI). We evaluated whether these treatment effects are preserved when recurrent events are considered. METHODS AND RESULTS: In this TWILIGHT trial post-hoc analysis, we assessed the effects of ticagrelor monotherapy on the total number of events that occurred over the 12-month follow-up among 7119 high-risk patients randomized to aspirin or placebo in addition to ticagrelor at 3 months post-PCI if event-free and adherent to treatment. There were 391 patients with at least one Bleeding Academic Research Consortium (BARC) type 2, 3, or 5 bleeding (primary endpoint). Of those, 28 (7.2%) had a recurrent event. The total number of BARC 2, 3, or 5 bleeding events was 148 in the ticagrelor monotherapy arm compared with 278 with ticagrelor plus aspirin arm (P < 0.001). Among 272 patients with at least one key secondary ischaemic endpoint (all-cause death, myocardial infarction, or stroke), 37 (13.6%) sustained a recurrent event. Total ischaemic events were similar (155 vs. 159) in the two groups. CONCLUSION: Among selected high-risk patients who underwent PCI and completed 3 months of dual antiplatelet therapy followed by ticagrelor with or without aspirin, recurrent bleeding was less common than recurrent ischaemic events over 12 months. Analysis of total events indicates that ticagrelor monotherapy continues to be more effective than ticagrelor plus aspirin in reducing bleeding without a signal of ischaemic harm.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.004 | 0.001 |
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".