S1055 Efficacy and Safety of Peroral Endoscopic Myotomy for the Treatment of Esophageal Diverticula: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: A new minimally invasive treatment, known as per-oral endoscopic myotomy (POEM), has emerged for managing esophageal diverticula, including Zenker’s diverticulum, epiphrenic diverticulum, Killian-Jamieson diverticulum, and thoracic esophageal diverticulum. This meta-analysis aimed to assess the efficacy and safety of POEM for esophageal diverticula. Methods: Electronic databases including PubMed, Cochrane Central, and ScienceDirect were searched from inception till January 2025. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The pooled analysis was conducted under the random effects model using R version 4.2.3 and employing the “metaprop” package. The primary and secondary outcomes of interest were treatment success, technical success, symptoms recurrence, and adverse effects. The quality assessment was done through the Newcastle Ottawa Scale. The publication bias was assessed through visual inspection of funnel plots. Results: Thirty-seven studies pooling a total of 1,032 patients were included in this meta-analysis. The pooled clinical success was 92% (95% confidence interval [CI] 89-94%; I2 = 0%). The technical success rate was 99% (95% CI 97-99%; I2 = 0%). The pooled rate of symptom recurrence was 6% (95% CI 4-9%; I2 = 0%) whereas the overall adverse effects were 9% (95% CI 7-12%; I2 = 0%). Conclusion: POEM demonstrates high clinical and technical success rates with low rates of symptom recurrence and adverse effects supporting its efficacy and safety for managing esophageal diverticula. These findings highlight POEM as a promising minimally invasive treatment option for diverse esophageal diverticula types.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.047 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".