Potential clinical benefits of proton pump inhibitors for secondary prevention of recurrent bleeding among patients with upper gastrointestinal bleeding receiving oral anticoagulants: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Proton pump inhibitors (PPIs) are commonly used among these patients to prevent upper gastrointestinal bleeding (UGIB) in anticoagulated patients. However, their clinical benefits among patients receiving OACs with a history of UGIB remain inconclusive. This study aimed to summarize the clinical benefits of PPIs for the secondary prevention of recurrent UGIB among patients using OACs. METHODS: A systematic search was performed in PubMed, EMBASE, Cochrane, and Scopus databases for clinical studies conducted among patients receiving OACs with PPIs and a history of UGIB. The primary outcome was the recurrent UGIB, analysed using a random-effect model. Heterogeneity was assessed by the I2-statistic. The quality of studies was assessed by the Newcastle-Ottawa Scale. KEY FINDINGS AND CONCLUSIONS: Four studies with a total of 67 148 participants were included. Of those, three were conducted among patients with atrial fibrillation and one among unspecified patients. Our meta-analysis indicated that PPIs were associated with a lower risk of recurrent UGIB with a hazard ratio (HR) of 0.67 (95%CI; 0.58-0.76, I2 = 8.9%) compared with no PPIs for patients receiving oral anticoagulants. Our subgroup analysis using comparators showed the robustness of the main findings. The HR of PPIs for recurrent UGIB in patients receiving vitamin K antagonists and direct oral anticoagulants compared with no PPI were 0.67 (95%CI; 0.54-0.80, I2 = 0.0%) and 0.63 (95%CI; 0.52-0.74, I2 = 0.0%), respectively. PPIs could potentially reduce the risk of recurrent UGIB. Clinicians might consider using PPIs for secondary prevention among patients receiving OAC.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.045 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".