The concurrent use of antithrombotic therapies and the risk of bleeding in patients with atrial fibrillation
Bibliographic record
Abstract
Patients with atrial fibrillation (AF) often receive, in addition to warfarin, antithrombotic drugs to manage other comorbid conditions. To date, few population-based studies have quantified the bleeding risk associated with the concurrent use of these therapies. The United Kingdom General Practice Research Database was used to identify a cohort of 70,760 patients newly-diagnosed with AF between 1993 and 2008. A nested case-control analysis was conducted within that cohort, and conditional logistic regression was used to estimate adjusted rate ratios (RRs) of bleeding associated with current use of warfarin, aspirin, and clopidogrel in single therapy, as well as in dual and triple therapy, as compared with non-use of any therapy. A total of 10,850 patients experienced a bleeding event during follow-up. In single therapy, warfarin was associated with the highest increased risk (RR: 2.08, 95% confidence interval [CI]: 1.95-2.23), followed by clopidogrel (RR: 1.57, 95% CI: 1.37-1.81) and aspirin (RR: 1.25, 95% CI: 1.17-1.34). In dual therapy, combinations containing warfarin were associated with a higher increased risk (warfarin-aspirin: RR: 2.87, 95% CI: 2.58-3.19, and warfarin-clopidogrel: RR: 2.74, 95% CI: 2.14-3.51), than those not containing warfarin (aspirin-clopidogrel: RR: 1.68, 95% CI: 1.44-1.97). Triple therapy of warfarin-aspirin-clopidogrel was associated with the highest increased risk (RR: 3.75, 95% CI: 2.71-5.19). This large population-based study suggests that while all antithrombotic therapies are associated with an elevated risk of bleeding, the risks increase in an additive fashion with dual and triple therapy, particularly in combinations containing warfarin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".