Ischaemic cardiac outcomes in patients with atrial fibrillation treated with vitamin K antagonism or factor Xa inhibition: results from the ROCKET AF trial
Bibliographic record
Abstract
AIMS: We investigated the prevalence of prior myocardial infarction (MI) and incidence of ischaemic cardiovascular (CV) events among atrial fibrillation (AF) patients. METHODS AND RESULTS: In ROCKET AF, 14 264 patients with nonvalvular AF were randomized to rivaroxaban or warfarin. The key efficacy outcome for these analyses was CV death, MI, and unstable angina (UA). This pre-specified analysis was performed on patients while on treatment. Rates are per 100 patient-years. Overall, 2468 (17%) patients had prior MI at enrollment. Compared with patients without prior MI, these patients were more likely to be male (75 vs. 57%), on aspirin at baseline (47 vs. 34%), have prior congestive heart failure (78 vs. 59%), diabetes (47 vs. 39%), hypertension (94 vs. 90%), higher mean CHADS2 score (3.64 vs. 3.43), and fewer prior strokes or transient ischaemic attacks (46 vs. 54%). CV death, MI, or UA rates tended to be lower in patients assigned rivaroxaban compared with warfarin [2.70 vs. 3.15; hazard ratio (HR) 0.86, 95% confidence interval (CI) 0.73-1.00; P = 0.0509]. CV death, MI, or UA rates were higher in those with prior MI compared with no prior MI (6.68 vs. 2.19; HR 3.04, 95% CI 2.59-3.56) with consistent results for CV death, MI, or UA for rivaroxaban compared with warfarin in prior MI compared with no prior MI (P interaction = 0.10). CONCLUSION: Prior MI was common and associated with substantial risk for subsequent cardiac events. Patients with prior MI assigned rivaroxaban compared with warfarin had a non-significant 14% reduction of ischaemic cardiac 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".