Ticagrelor with or without aspirin in high-risk patients with anaemia undergoing percutaneous coronary intervention: a subgroup analysis of the TWILIGHT trial
Bibliographic record
Abstract
AIM: The aim of this study was to assess the effect of ticagrelor monotherapy among high-risk patients with anaemia undergoing percutaneous coronary intervention (PCI). METHODS AND RESULTS: In the TWILIGHT (Ticagrelor with Aspirin or Alone in High-Risk Patients after Coronary Intervention) trial, after 3 months of ticagrelor plus aspirin, high-risk patients were maintained on ticagrelor and randomized to aspirin or placebo for 1 year. Anaemia was defined as haemoglobin <13 g/dL for men and <12 g/dL for women. The primary endpoint was Bleeding Academic Research Consortium (BARC) 2, 3, or 5 bleeding. The key secondary endpoint was a composite of all-cause death, myocardial infarction, or stroke.Out of 6828 patients, 1329 (19.5%) had anaemia and were more likely to have comorbidities, multivessel disease, and to experience bleeding or ischaemic complications than non-anaemic patients. Among anaemic patients, BARC 2, 3, or 5 bleeding occurred less frequently with ticagrelor monotherapy than with ticagrelor plus aspirin [6.4% vs. 10.7%; hazard ratio (HR) 0.60; 95% confidence interval (CI) 0.41-0.88; P = 0.009]; the rate of the key secondary endpoint was similar in the two arms (5.2% vs. 4.8%; HR 1.07; 95% CI 0.66-1.74; P = 0.779). These effects were consistent in patients without anaemia (interaction P values 0.671 and 0.835, respectively). CONCLUSION: In high-risk patients undergoing PCI, ticagrelor monotherapy after 3 months of ticagrelor-based dual antiplatelet therapy was associated with a reduced risk of clinically relevant bleeding without any increase in ischaemic events irrespective of anaemia status (TWILIGHT: NCT02270242).
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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) | 0.005 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".