S1436 From Bleeding to Healing: Unveiling the Efficacy and Safety of UI-EWD Hemostatic Powder in Gastrointestinal Bleeding—A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: A novel endoscopic hemostatic adhesive powder (UI-EWD) was developed to cope with the high rebleeding rates associated with the current endoscopic hemostatic options for gastrointestinal bleeding. This meta-analysis aimed to assess the safety and effectiveness of UI-EWD hemostatic adhesive powder as a salvage treatment modality for upper and lower gastrointestinal bleeding. Methods: Electronic databases like PubMed, Cochrane Central and ScienceDirect were searched from inception to January 2025. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The proportions were pooled with 95% Confidence Intervals (CI) using R version 4.2.3 and employing the “metaprop” package for the dichotomous outcomes. The primary and secondary outcomes of interest were clinical success, overall rebleeding, early rebleeding, delayed rebleeding, time to rebleeding, mortality and adverse events. The quality assessment was done through the Cochrane Risk of Bias (RoB) 2.0 tool and the Newcastle Ottawa Scale. The risk of publication bias was assessed visually through funnel plots and statistically through Egger’s regression test. Results: Three studies (including 2 trials and one cohort) with a total of 211 patients were included in this meta-analysis. The pooled clinical success rate was 98% (95% confidence interval [CI]: [85-100%]; I2 = 0%). The overall rebleeding rate was 11% (95% confidence interval: [0-93%]; I2 = 11.5%). The pooled rates of early and delayed rebleeding were 10% (95% CI: [1-51%]; I2 = 70.5%) and 9% (95% CI: [3-22%]; I2 = 0%) respectively. Conclusion: UI-EWD hemostatic adhesive powder demonstrates a high clinical success rate and relatively low overall rebleeding rates, making it an effective salvage treatment for gastrointestinal bleeding. The early and delayed rebleeding rates are manageable, with minimal heterogeneity observed in delayed rebleeding outcomes. These findings suggest UI-EWD is a promising and safe option for managing challenging bleeding cases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.036 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".