Endoscopic resection of upper gastrointestinal lesions using the colonic Ovesco full-thickness resection device: Retrospective observational case series of 22 cases
Bibliographic record
Abstract
Abstract Background and study aims The endoscopic full-thickness resection (EFRT) device (FTRD) has been shown to have acceptable outcomes in regard to efficacy and safety in the resection of colorectal lesions. Data on its use in the upper gastrointestinal tract are limited to small case series. Patients and methods All consecutive patients undergoing endoscopic full-thickness resection of gastric or duodenal lesions at our institutions were analyzed retrospectively for a primary endpoint of technical success. Results A total of 22 patients with duodenal and gastric lesions underwent EFTR between June 2018 and February 2022. Technical success was achieved in 20 of 22 (91 %) of the procedures. Indications for EFTR were: subepithelial tumor (n = 14), mucosal lesion (n = 5), scar resection (n = 2), and EFTR of endoscopic submucosal dissection (ESD) resection base (n = 1). The FTRD could be advanced to the lesion in all 22 cases (100 %). No dilation of the upper esophageal sphincter (UES) or pylorus was required to pass the device. There were 14 cases of gastric lesions and eight duodenal. One subepithelial lesion was too big for the cap and one scar could not be sucked into the cap. One lesion (gastrointestinal stromal tumor) was removed at second procedure with the ESD technique, including over-the-scope clip. The R0 resection rate for deployed clips was 90 % (18 of 20). There were two superficial esophageal tears from FTRD insertion that required no therapy. No bleeding occurred during the postoperative period. Conclusions Upper gastrointestinal EFTR using the colonic Ovesco FTRD is feasible without pre-dilation of the upper esophageal sphincter or pylorus. This study further confirms acceptable efficacy and safety in upper gastrointestinal use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".