Abstract 13168: Benefits of Apixaban Over Warfarin are Preserved Independent of Warfarin Time in Therapeutic Range: Insights From the AUGUSTUS Trial
Bibliographic record
Abstract
Introduction: In the AUGUSTUS trial, patients randomized to apixaban had lower rates of major or clinically relevant non-major (CRNM) bleeding, lower rates of death or hospitalization, and similar rates of death or ischemic events compared with warfarin. Patients randomized to aspirin (ASA) had higher rates of bleeding with similar rates of death or hospitalization, and death or ischemic event. The impact of warfarin time-in-therapeutic-range (TTR) on these outcomes is not known; however, it is plausible that sites achieving better TTR might have better outcomes with warfarin use. Methods: Using average site TTR, we assessed the hazard of bleeding, ischemic events, and death/hospitalization across quartiles of site-based TTR. These analyses were performed for both randomized strategies: apixaban vs warfarin and ASA vs placebo. Results: This analysis included data from 4420 patients at 399 sites. Site TTR was separated into quartiles of TTR (Q1: 0-49%, Q2: 42-55%, Q3: 56-69%, Q4: 70-100%). Sites with higher TTR tended to have fewer female patients (32.4% Q1 vs 25.4% Q4), more White patients (88.5% Q1 vs 97.1% Q4), and more patients previously prescribed oral anticoagulants (44.5% Q1 vs 52.5% Q4). There was no significant interaction between site TTR quartile and the hazard ratio (HR) for bleeding, death or hospitalization, or death or ischemic event with apixaban vs warfarin, or on the HR for bleeding, or death or hospitalization with ASA vs placebo (Figure). There was a borderline significant interaction (p<0.047) between site TTR quartile and the HR for death or ischemic events with ASA vs placebo, such that patients at sites with higher TTR were more likely to derive a benefit from ASA compared with placebo. Conclusion: The benefits of apixaban over warfarin seen previously in AUGUSTUS are consistent across the spectrum of quartiles of site TTR. Patients at sites with higher average TTR may be more likely to derive a benefit from aspirin use to prevent death or ischemic events.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".