Aspirin for the Prevention of Recurrent Venous Thromboembolism
Bibliographic record
Abstract
BACKGROUND: In patients with a first unprovoked venous thromboembolism (VTE) the risk of recurrent VTE remains high after anticoagulant treatment is discontinued. The Aspirin for the Prevention of Recurrent Venous Thromboembolism (the Warfarin and Aspirin [WARFASA]) and the Aspirin to Prevent Recurrent Venous Thromboembolism (ASPIRE) trials showed that aspirin reduces this risk, but they were not individually powered to detect treatment effects for particular outcomes or subgroups. METHODS AND RESULTS: An individual patient data analysis of these trials was planned, before their results were known, to assess the effect of aspirin versus placebo on recurrent VTE, major vascular events (recurrent VTE, myocardial infarction, stroke, and cardiovascular disease death) and bleeding, overall and within predefined subgroups. The primary analysis, for VTE, was by intention to treat using time-to-event data. Of 1224 patients, 193 had recurrent VTE over 30.4 months' median follow-up. Aspirin reduced recurrent VTE (7.5%/yr versus 5.1%/yr; hazard ratio [HR], 0.68; 95% confidence interval [CI], 0.51-0.90; P=0.008), including both deep-vein thrombosis (HR, 0.66; 95% CI, 0.47-0.92; P=0.01) and pulmonary embolism (HR, 0.66; 95% CI, 0.41-1.06; P=0.08). Aspirin reduced major vascular events (8.7%/yr versus 5.7%/yr; HR, 0.66; 95% CI, 0.50-0.86; P=0.002). The major bleeding rate was low (0.4%/yr for placebo and 0.5%/yr for aspirin). After adjustment for treatment adherence, recurrent VTE was reduced by 42% (HR, 0.58; 95% CI, 0.40-0.85; P=0.005). Prespecified subgroup analyses indicate similar relative, but larger absolute, risk reductions in men and older patients. CONCLUSIONS: Aspirin after anticoagulant treatment reduces the overall risk of recurrence by more than a third in a broad cross-section of patients with a first unprovoked VTE, without significantly increasing the risk of bleeding. CLINICAL TRIAL REGISTRATION URL: www.anzctr.org.au. Unique identifier: ACTRN12611000684921.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".