Abstract 4143980: Bleeding with the FXI Inhibitor Abelacimab compared with Rivaroxaban in Patients on Antiplatelet therapy: A Prespecified Analysis of the AZALEA-TIMI 71 Trial
Bibliographic record
Abstract
Background: Combining antiplatelet (APT) with anticoagulant therapy increases the risk of bleeding. In AZALEA-TIMI 71, the novel factor XI inhibitor abelacimab reduced the risk of bleeding compared with rivaroxaban in patients with atrial fibrillation (AF). In this analysis, we investigated whether the safety of abelacimab vs rivaroxaban was modified by antiplatelet therapy. Methods: AZALEA-TIMI 71 randomized 1,287 patients with AF to abelacimab (90 or 150 mg subcutaneously monthly) or rivaroxaban (20 mg orally daily), with stratification by planned use of concomitant APT. The primary outcome, major or clinically relevant non-major (CRNM) bleeding, was compared using Cox proportional hazards adjusted for age, sex, and BMI, with an interaction term for randomized treatment and APT use. Results: Of 1,287 patients, 318 (25%) were on APT at baseline (16% aspirin only, 8% P2Y 12 only, 2% DAPT) and were younger (median age 72 vs 75 years) and had a higher prevalence of CAD (74% vs 40%), prior MI (36% vs 16%) and PAD (15% vs 11%) than those not on APT (p<0.05 for each). The rate of major or CRNM bleeding tended to be higher in those on APT than those not taking APT in the rivaroxaban group (10.6% vs. 7.7%), but not in the abelacimab group (Fig). Both abelacimab doses significantly reduced major or CRNM bleeding compared with rivaroxaban regardless of APT use [60-66% in patients not on ATP and 70-74% in patients on ATP] (Fig). Given the higher rates of bleeding in patients on both rivaroxaban and APT, the corresponding absolute risk reductions with abelacimab tended to be greater in patients on APT (7.1-8.1%) compared to those not on APT (4.6-5.0%) (Fig). Conclusion: Inhibition of FXI with abelacimab results in substantial reductions in bleeding compared with rivaroxaban regardless of concomitant APT use. These data support the potential advantage of FXI inhibitors in patients who require concomitant APT.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".