All-cause mortality after major gastrointestinal bleeding among patients receiving direct oral anticoagulants: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Although gastrointestinal (GI) bleeding represents the single most frequent site of anticoagulant-related major bleeding, outcomes after major GI bleeding including mortality are not well characterized and severity may be underappreciated. We aimed to determine 30-day all-cause mortality in adults with major GI bleeding on a direct oral anticoagulant (DOAC). Methods We searched MEDLINE, EMBASE, and Cochrane CENTRAL from inception to May 9, 2024 for randomized controlled trials and cohort studies that reported 30-day all-cause mortality after major GI bleeding in adults treated with a DOAC for venous thromboembolism or atrial fibrillation. Risk of bias was assessed using a modified QUIPS tool for prognostic studies. 30-day all-cause mortality was calculated using the random-effects inverse-variance method. Results We included 20 studies comprising 3987 DOAC-treated patients with major GI bleeds. The pooled estimate of 30-day all-cause mortality was 8.4 % (95 % confidence interval [CI], 4.9–12.5; I 2 = 83 %). In subgroup analyses, 30-day all-cause mortality was 10.3 % (95 % CI, 6.5–14.7; I 2 = 24 %) in prospective studies (9 studies, 675 major GI bleeds), 7.3 % (95 % CI, 2.2–14.4; I 2 = 90 %) in retrospective studies (11 studies, 3312 major GI bleeds), 12.9 % (95 % CI, 6.3–21.1; I 2 = 44 %) in considered at high risk of bias (9 studies, 387 major GI bleeds), and 6.1 % (95 % CI, 2.9–10.1; I 2 = 89 %) in those at low risk of bias (10 studies, 3562 major GI bleeds). Conclusion DOAC-related major GI bleeding appears to be associated with significant 30-day all-cause mortality. Further research is needed regarding the causes and contributors to mortality in this population to identify patients at high risk and develop mitigation strategies.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.039 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".