The impact of bleeding complications in patients receiving target-specific oral anticoagulants: a systematic review and meta-analysis
Bibliographic record
Abstract
Vitamin K antagonists (VKAs) have been the standard of care for treatment of thromboembolic diseases. Target-specific oral anticoagulants (TSOACs) have been developed and found to be at least noninferior to VKAs with regard to efficacy, but the risk of bleeding with TSOACs remains controversial. We performed a systematic review and meta-analysis of phase-3 randomized controlled trials (RCTs) to assess the bleeding side effects of TSOACs compared with VKAs in patients with venous thromboembolism or atrial fibrillation. We searched MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials; conference abstracts; and www.clinicaltrials.gov with no language restriction. Two reviewers independently performed study selection, data extraction, and study quality assessment. Twelve RCTs involving 102 607 patients were retrieved. TSOACs significantly reduced the risk of overall major bleeding (relative risk [RR] 0.72, P < .01), fatal bleeding (RR 0.53, P < .01), intracranial bleeding (RR 0.43, P < .01), clinically relevant nonmajor bleeding (RR 0.78, P < .01), and total bleeding (RR 0.76, P < .01). There was no significant difference in major gastrointestinal bleeding between TSOACs and VKAs (RR 0.94, P = .62). When compared with VKAs, TSOACs are associated with less major bleeding, fatal bleeding, intracranial bleeding, clinically relevant nonmajor bleeding, and total bleeding. Additionally, TSOACs do not increase the risk of gastrointestinal bleeding.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".