Endoscopic Ultrasound‐Guided Coiling Plus Glue Injection Compared With Other Endoscopic Modalities in Managing Gastric Varices: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Gastric varices (GV) are a major complication of portal hypertension, with a high risk of severe bleeding. Conventional endoscopic glue injection or endoscopic ultrasound (EUS) directed therapies have been used for treatment. However, each has its limitations. EUS-guided combination of coil and glue injection has emerged as a potential strategy to improve outcomes. This meta-analysis compares the efficacy and safety of EUS-coil and glue to other endoscopic modalities in GV management. METHODS: statistic, and subgroup and sensitivity analyses were performed. The risk of bias in studies and the certainty of the evidence were evaluated. RESULTS: Nine studies with 579 patients met the inclusion criteria. Compared with other modalities, EUS-coil and glue had a lower risk of reintervention (RR = 0.32, 95% CIs = 0.21-0.50) and a higher rate of GV obliteration (RR = 1.18, 95% CIs = 1.03-1.37). There was no significant difference in mortality risk (RR = 0.87, 95% CIs = 0.54-1.40). The overall risk of adverse events (RR = 0.55, 95% CIs = 0.34-0.90) was lower, particularly rebleeding (RR = 0.36, 95% CIs = 0.22-0.59). The certainty of evidence ranged from very low to moderate due to bias and study heterogeneity. CONCLUSIONS: EUS-coil and glue injection offers superior efficacy and a favorable safety profile compared with other endoscopic treatments for GV. However, the quality of the evidence warrants further well-designed studies to assess long-term outcomes.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.005 | 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".