Safety and efficacy of direct oral anticoagulants in patients with liver cirrhosis: a meta-analysis
Bibliographic record
Abstract
Background: Direct oral anticoagulants (DOACs) are the standard of care for treatment of venous thromboembolism and stroke prophylaxis in atrial fibrillation. Since patients with Child-Pugh (CP) B or C liver cirrhosis are underrepresented in trials, the safety of DOACs in this population is unclear. Objectives: This study synthesized primary evidence on the safety profile of DOACs in patients with advanced liver cirrhosis. Methods: A literature search of MEDLINE and Embase from inception to October 2025 identified randomized and nonrandomized cohort studies comparing DOAC with vitamin K antagonists or low-molecular-weight heparin in patients with liver cirrhosis. Screening and data collection were conducted in duplicate. The primary outcome was major bleeding defined by International Society on Thrombosis and Haemostasis criteria, stratified by CP class. Data were meta-analyzed using a random-effects model, presented as odds ratios (OR) with corresponding 95% CIs. Results: = 70) study were included. DOACs reduced major bleeding in both CP class B and C exclusive subgroup and a subgroup with unspecified CP stages of liver cirrhosis (CP B and C: OR, 0.53; 95% CI, 0.36-0.80; CP unspecified: OR, 0.66; 95% CI, 0.46-0.98). Conclusion: Based on the findings of this meta-analysis, DOACs may be associated with a reduced risk of major bleeding compared with vitamin K antagonists or low-molecular-weight heparin in patients with liver cirrhosis, including those with CP class B and C cirrhosis. The results of this meta-analysis should be interpreted in the context of methodological limitations. Future analysis should evaluate the impact of specific DOACs and dosage on safety outcomes in this patient population.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.061 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".