Apixaban or Warfarin in Patients with an On-X Mechanical Aortic Valve
Bibliographic record
Abstract
BACKGROUND: Vitamin K antagonists are the only oral anticoagulants approved to prevent valve thrombosis and valve-related thromboembolism in patients with mechanical heart valves. Whether patients with an On-X mechanical aortic valve can be safely anticoagulated with apixaban is unknown. METHODS: Patients with an On-X aortic valve implanted at least 3 months before enrollment were randomly assigned to receive apixaban 5 mg twice daily or warfarin (target international normalized ratio 2.0 to 3.0). The primary efficacy end point was the composite of valve thrombosis or valve-related thromboembolism with coprimary analyses comparing apixaban with warfarin for noninferiority and comparing the apixaban event rate with an objective performance criterion (OPC). RESULTS: The trial was stopped after 863 participants were enrolled owing to an excess of thromboembolic events in the apixaban group. Most (94%) participants took aspirin. A total of 26 primary end-point events occurred, 20 (in 16 participants) in the apixaban group (4.2%/patient-year; 95% confidence interval [CI], 2.3 to 6.0) and 6 (in 6 participants) in the warfarin group (1.3%/patient-year; 95% CI, 0.3 to 2.3). The difference in primary end-point rates between the apixaban and warfarin groups was 2.9 (95% CI, 0.8 to 5.0); noninferiority and OPC success criteria were not met. Major bleeding rates were 3.6%/patient-year with apixaban and 4.5%/patient-year with warfarin. CONCLUSIONS: Apixaban did not demonstrate noninferiority to warfarin and is less effective than warfarin for the prevention of valve thrombosis or thromboembolism in patients with an On-X mechanical aortic valve. (Funded by Artivion; ClinicalTrials.gov number, NCT04142658.)
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".