Ticagrelor monotherapy after PCI in patients with concomitant diabetes mellitus and chronic kidney disease: TWILIGHT DM-CKD
Bibliographic record
Abstract
AIMS: We aimed to evaluate the treatment effects of ticagrelor monotherapy in the very high risk cohort of patients with concomitant diabetes mellitus (DM) and chronic kidney disease (CKD) 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-month dual antiplatelet therapy with ticagrelor and aspirin post-PCI, event-free patients were randomized to either aspirin or placebo in addition to ticagrelor for 12 months. Those with available information on DM and CKD status were included in this subanalysis and were stratified by the presence or absence of either condition: 3391 (54.1%) had neither DM nor CKD (DM-/CKD-), 1822 (29.0%) had DM only (DM+/CKD-), 561 (8.9%) had CKD only (DM-/CKD+), and 8.0% had both DM and CKD (DM+/CKD+). The incidence of the primary endpoint of Bleeding Academic Research Consortium (BARC) type 2, 3, or 5 bleeding did not differ according to DM/CKD status (P-trend = 0.13), but there was a significant increase in BARC 3 or 5 bleeding (P-trend < 0.001) as well as the key secondary endpoint of death, myocardial infarction, or stroke (P-trend < 0.001). Ticagrelor plus placebo reduced bleeding events compared with ticagrelor plus aspirin across all four groups, including DM+/CKD+ patients with respect to BARC 2-5 [4.5% vs. 8.7%; hazard ratio (HR) 0.49, 95% confidence interval (CI) 0.24-1.01] as well as BARC 3-5 (0.8% vs. 5.3%; HR 0.15, 95% CI 0.03-0.53) bleeding, with no evidence of heterogeneity. The risk of death, myocardial infarction, or stroke was similar between treatment arms across all groups. CONCLUSION: Irrespective of the presence of DM, CKD, and their combination, ticagrelor monotherapy reduced the risk of bleeding without a significant increase in ischaemic events compared with ticagrelor plus aspirin.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".