OPTIMAL EPINEPHRINE INJECTION VOLUME FOR ENDOSCOPIC TREATMENT OF ACUTE PEPTIC ULCER BLEEDING. A SYSTEMATIC REVIEW AND META-ANALYSIS.
Bibliographic record
Abstract
INTRODUCTION: Endoscopic treatment improves the outcomes of patients with acute peptic ulcer bleeding (APUB). Epinephrine injection is a frequently used treatment. There is no consensus, however, on the optimal volume of epinephrine injection. Primary aim was to compare the efficacy and safety of endoscopic injection using different volumes of epinephrine for APUB treatment in a systematic review and meta-analysis. METHODS: Systematic searches were performed for full papers published from 1986 until January 2025 in multiple databases. We included randomized controlled trials (RCT) comparing different epinephrine volumes injection. Primary outcome was permanent haemostasis defined as achieved initial haemostasis and not rebleeding during admission. Secondary outcomes were adverse events, need for rescue treatment and mortality. We estimated the OR and 95%CI using random-effects models. RESULTS: Four RCT including 556 patients were analyzed. No studies comparing different doses of epinephrine in combination therapy were found. In studies comparing different doses of epinephrine alone, permanent haemostasis was more frequently achieved in the large-volume injection groups (91% vs 77%, OR:2.90; 95%CI:1.72-4.86, p<0.0001). Adverse events (AE) were also more frequent in the large-volume groups (33% vs 3%, OR: 21.02; 95%CI:6.51-67.87, p<00001). Abdominal pain was the most frequent AE. Bowel perforation appeared only when injection volumes exceeded 35 cc. CONCLUSION: Endoscopic injection of large volumes of epinephrine up to 30cc appear safe and improve rates of permanent haemostasis when compared to lower injection volume in patients with APUB. Trials assessing the use of larger epinephrine volume in combination endoscopic hemostatic therapy are needed.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".