Vitamin K Antagonists and Risk of Subdural Hematoma
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Subdural hematomas are an important bleeding complication of anticoagulation. We quantify the risk of subdural hematoma associated with anticoagulation with vitamin K antagonists (VKAs) compared with other oral antithrombotic therapies. METHODS: Randomized trials were identified from the Cochrane Central Register of Controlled Trials and were included if published since 1980 and compared oral VKAs with antiplatelet therapy or with direct-acting oral anticoagulants. Two reviewers independently extracted data with differences resolved by joint review. RESULTS: Nineteen randomized trials were included that involved 92 156 patients and 275 subdural hematomas. By meta-analysis, VKAs were associated with a significantly increased risk of subdural hematoma (odds ratios, 3.0; 95% confidence interval, 1.5-6.1) compared with antiplatelet therapy (9 trials, 11 603 participants). The risk of subdural hematoma was also significantly higher with VKAs versus factor Xa inhibitors (meta-analysis odds ratios, 2.9; 95% confidence interval, 2.1-4.1; 5 trials, 49 687 patients) and direct thrombin inhibitors (meta-analysis odds ratios, 1.8; 95% confidence interval, 1.2-2.7; 5 trials, 30 866 patients) versus VKAs. The absolute rate of subdural hematoma among 24 485 patients with atrial fibrillation treated with VKAs pooled from 6 trials testing direct-acting oral anticoagulants was 2.9 (95% confidence interval, 2.5-3.5) per 1000 patient-years. CONCLUSIONS: VKA use significantly increases the risk of subdural hematoma by ≈3-fold relative to antiplatelet therapy. Direct-acting oral anticoagulants are associated with a significantly reduced risk of subdural hematomas versus VKAs. Based on indirect comparisons to VKAs, the risks of subdural hematoma are similar with antiplatelet monotherapies and factor Xa inhibitors.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".