Drug drug interactions between antithrombotic medications and the risk of gastrointestinal bleeding
Bibliographic record
Abstract
BACKGROUND: Anticoagulants and antiplatelet drugs (e.g., warfarin, clopidogrel and acetylsalicylic acid) are key therapeutic agents in the treatment of cardiovascular diseases. However, drug-drug interactions may lead to a greatly increased risk of gastrointestinal bleeding when these drugs are combined. We assessed whether antithrombotic drug combinations increased the risk of such bleeding in a general practice population. METHODS: We conducted a population-based, retrospective case-control study using records in the United Kingdom General Practice Research Database from 2000 through 2005. Cases were identified as patients over 18 years of age with a first-ever diagnosis of gastrointestinal bleeding. They were matched with controls by physician practice, patient age and index date (date of diagnosis of bleeding). All eligible patients had to have at least 3 years of follow-up data in the database. Drug exposure was considered to be any prescription issued in the 90 days before the index date. RESULTS: There were 4028 cases with a diagnosis of gastrointestinal bleeding and 40 171 matched controls. The prescribing of acetylsalicylic acid with either clopidogrel (adjusted rate ratio [RR] 3.90, 95% confidence interval [CI] 2.78-5.47) or warfarin (adjusted RR 6.48, 95% CI 4.25-9.87) was associated with a greater risk of gastrointestinal bleeding than that observed with each drug alone. The same was true when a nonsteroidal anti-inflammatory drug was combined with either clopidogrel (adjusted RR 2.93, 95% CI 1.74-4.93) or warfarin (RR 4.60, 95% CI 2.77-7.64). INTERPRETATION: Drug combinations involving antiplatelets and anticoagulants are associated with a high risk of gastrointestinal bleeding beyond that associated with each drug used alone. Physicians should be aware of these risks to better assess their patients' therapeutic risk-benefit profiles.
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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 | 0.005 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".