Abstract 15664: Prior Oral Anticoagulant Status and Outcomes in Patients With Atrial Fibrillation With an Acute Coronary Syndrome and/or Undergoing Percutaneous Coronary Intervention: Insights From the Augustus Trial
Bibliographic record
Abstract
Background: Managing antithrombotic therapy transitions at hospital admission and discharge in patients with atrial fibrillation (AF) and an acute coronary syndrome (ACS) or percutaneous coronary intervention (PCI) is challenging and is affected by prior treatment. We examined oral anticoagulant (OAC) use prior to enrollment and the relationship with outcomes in the AUGUSTUS trial. Methods: Patients in AUGUSTUS (N=4,614) were analyzed according to whether they were [n=2262] or were not [n=2352] on a prior OAC. Bleeding and clinical outcomes were compared by Kaplan-Meier (KM) estimates at 180 days. For each outcome, KM estimates and treatment interactions were determined by randomized arm and prior OAC status. Results: Those with prior OAC use had higher CHA 2 DS 2 -VASC and HAS-BLED scores and more comorbid medical conditions (hypertension, heart failure, diabetes, prior stroke), and were more likely to have been enrolled following elective PCI. Prior OAC use included vitamin K antagonists (VKAs) 47%, rivaroxaban 22%, apixaban 22%, dabigatran 12%, and edoxaban 1%. There was no difference in combined ISTH major/clinically relevant non-major (CRNM) bleeding with or without prior OAC use (13.5% vs. 13.5%; HR 1.00, 95% CI 0.85-1.18). Patients with prior OAC use had lower risk of death or ischemic events (5.4% vs. 7.6%; HR 0.72, 95% CI 0.57-0.91). No interactions were observed between randomized treatment (apixaban vs. VKA and aspirin vs. placebo) and prior OAC status for outcomes other than MI where apixaban (vs. VKA) was associated with a lower risk of MI in those with prior OAC use (Figure). Conclusion: In AUGUSTUS, OAC prior to enrollment was more common in patients with comorbidities and those enrolled following elective PCI. Prior OAC was associated with fewer ischemic events but not more bleeding. Our results support the use of apixaban plus a P2Y12 inhibitor without aspirin for patients with AF and ACS/PCI, irrespective of prior OAC use.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".