Are proton pump inhibitors the first choice for acute treatment of gastric ulcers? A meta analysis of randomized clinical trials
Bibliographic record
Abstract
BACKGROUND: Gastric ulcers are a frequent problem in the United States. Proton pump inhibitors have been shown to increase healing rates and improve clinical symptoms. The objective of this study is to compare gastric ulcer healing rates for patients treated with a proton pump inhibitor (PPI) (omeprazole, rabeprazole, pantoprazole, or lansoprazole), an histamine 2- receptor antagonist (ranitidine) or placebo. METHODS: A literature search was conducted to identify randomized, controlled clinical trials that included a PPI in at least one treatment arm and assessed the gastric ulcer healing rates endoscopically. The healing rates were estimated for each treatment at specific time points, and Rate Ratios (RR) and 95% confidence intervals (CI) were estimated for each trial. RESULTS: Sixteen trials met the inclusion criteria: four compared a PPI versus placebo, nine compared a PPI versus ranitidine (no trials of rabeprazole versus ranitidine met the inclusion criteria), and three compared a newer PPI (lansoprazole, pantoprazole or rabeprazole) versus omeprazole. In relation to ranitidine, the pooled RR of PPIs (lansoprazole, omeprazole and pantoprazole) was 1.33 (95% CI 1.24 to 1.42) at four weeks. In each trial, greater improvement in the studied clinical symptoms was found with the newer PPIs (rabeprazole, pantoprazole and lansoprazole) when compared to omeprazole. CONCLUSION: In this study treatment with PPIs resulted in higher healing rates than ranitidine or placebo. This evidence suggests that the first choice for gastric ulcer treatment for the greater relief of symptoms is one of the newer PPIs.
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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 | 0.040 | 0.069 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.046 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| 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".