S785 Efficacy and Safety of Enhanced Endoscopic Sleeve Gastroplasty With Argon Plasma Coagulation vs Endoscopic Sleeve Gastroplasty Alone: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Endoscopic sleeve gastroplasty (ESG), is a novel technique that reduces the gastric size reservoir using a full-thickness endoscopic suturing device. Its impact on weight loss has been significantly higher than lifestyle changes alone. There is a direct correlation between the integrity of the ESG and the achieved percentage of total body weight loss (%TBWL). Although, argon plasma coagulation (APC) is primarily used for the management of hemostasis by applying non-contact mucosal thermal ablation; its application before ESG could enhance wound healing and subsequent fibrosis, reducing suture dehiscence. Methods: Following the PRISMA guidelines, a systematic review and meta-analysis were performed to determine the impact of APC prior to ESG for weight loss. Primary outcomes were %TBWL at 6 and 12 months. Gray literature was included due to technique novelty. Data was analyzed using R version 4.2.2. The risk of bias was assessed by the Rob-2 and Robins-I tool. The quality of evidence was graded using the GRADE and Newcastle-Ottawa guidelines. Results: Two observational and one randomized clinical trial described the total weight loss at 6 and 12 months of ESG + APC vs ESG, totaling 231 patients. Meta-analysis test for overall effect showed no statistically significant difference between groups (SMD = 0.70; 95% CI = [-0.90; 2.30]; P = 0.20; and SMD = 0.77; 95% CI = [-0.57; 2.11]; P = 0.13, respectively). Similarly, there was no statistically significant difference in terms of rate of adverse events between groups (RR = 0.39; 95% CI = [0.13; 1.16]; P = 0.07). The risk of bias was moderate with moderate quality of evidence amongst the included studies. Conclusion: Our updated systematic review and meta-analysis demonstrated an absence of statistically significant difference in %TBWL loss at 6 to 12 months between ESG + APC compared to ESG alone. Further randomized studies are needed to confirm these findings.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".