Meta‐analysis: proton‐pump inhibition in high‐risk patients with acute peptic ulcer bleeding
Bibliographic record
Abstract
BACKGROUND: Recent data suggest that profound acid suppression may improve outcomes of patients in peptic ulcer bleeding. AIM: To better characterize the role of different pharmacological therapies in this population. METHODS: MEDLINE was used to identify randomized trials (01/1990-04/2003) that assessed the efficacy of pharmacological treatments for patients with bleeding peptic ulcers exhibiting high-risk stigmata (Forrest Ia-IIb). Three groups of treatment were assessed: proton-pump inhibitors given as high-dose bolus followed by intravenous constant infusion (40-80 mg and at least 6 mg/h), high-dose oral proton-pump inhibitors (at least twice the standard dosage), non-high-dose proton-pump inhibitors (other proton-pump inhibitors dosing schedules). Mixed-effect models were used to determine rate differences between treatment and control groups. RESULTS: Eighteen studies (1855 patients) were included. High-dose intravenous proton-pump inhibitors significantly reduced rebleeding (-14.6%), surgery (-5.4%) and mortality (-2.7%) compared with placebo, and rebleeding (-20.6%) compared with H(2)RA. Compared with placebo, high-dose oral proton-pump inhibitors significantly reduced only rebleeding (-11.8%), while non-high-dose proton-pump inhibitor treatment significantly improved all three outcomes. CONCLUSIONS: High-dose intravenous proton-pump inhibitor significantly decreases ulcer rebleeding, surgery and mortality. Early data on high-dose oral proton-pump inhibitor suggest improved rebleeding. The non-high-dose proton-pump inhibitor regimens, including a broad range of dosing, also improved outcomes, suggesting that doses inferior to those in the high-dose intravenous proton-pump inhibitor may be effective.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.032 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| 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".