S1370 Intermittent vs Continuous Proton Pump Inhibitor Therapy for Bleeding Peptic Ulcer: An Updated Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Gastrointestinal bleeding from peptic ulcers remains a significant clinical challenge, with high rebleeding rates even after endoscopic intervention. Proton pump inhibitors (PPIs) are commonly used to maintain hemostasis by maintaining gastric pH, but the optimal administration method—continuous infusion versus intermittent therapy—remains debated. This meta-analysis compares the efficacy of intermittent versus continuous PPI therapy in preventing rebleeding and other clinical outcomes in patients with bleeding peptic ulcers. Methods: We systematically searched databases including Embase, Scopus, Web of Science, Medline/PubMed, and Cochrane. Primary outcomes were rebleeding rates, mortality, hospital stay duration, and ICU admissions. Quality assessment was conducted using the Newcastle-Ottawa Scale for cohort studies and the Cochrane Risk of Bias Tool (ROB2) for RCTs. Meta-analyses were performed using a random-effects model, and heterogeneity was assessed with the I² statistic. Results: Eighteen studies (n = 3664) were included, spanning multiple countries. Meta-analysis showed no significant difference between intermittent and continuous PPI therapy in terms of rebleeding rates (OR = 1.02; 95% CI = 0.80–1.29; P = 0.88, I² = 20%), mortality (OR = 0.93; 95% CI = 0.56–1.55; P = 0.79, I² = 21%), or the need for surgery (OR = 1.09; 95% CI = 0.71–1.70; P = 0.69, I² = 0%). However, intermittent therapy was associated with significantly lower ICU admissions (OR = 0.29; 95% CI = 0.22–0.40; P < 0.00001, I² = 7%). Conclusion: Intermittent PPI therapy is as effective as continuous infusion in managing bleeding peptic ulcers, with comparable rebleeding, surgery, and mortality outcomes. Intermittent therapy also reduces ICU admission rates, suggesting a viable, cost-effective alternative to continuous infusion. Further research with larger, multi-center trials is needed to confirm these findings across diverse populations and healthcare settings.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".