Modified endoscopic ultrasound-guided double-balloon-occluded gastroenterostomy bypass (M-EPASS): a pilot study
Bibliographic record
Abstract
INTRODUCTION: We recently developed a double-balloon device, using widely available existing technology, to facilitate endoscopic ultrasound-guided gastroenterostomy (EUS-GE). Our aim is to assess the feasibility of this modified approach to EUS-guided double-balloon-occluded gastroenterostomy bypass (M-EPASS). METHODS: This was a single-center retrospective study of consecutive patients undergoing M-EPASS from January 2019 to August 2020. The double-balloon device consists of two vascular balloons that optimize the distension of a targeted small-bowel segment for EUS-guided stent insertion. The primary end point was the rate of technical success. RESULTS: 11 patients (45 % women; mean [standard deviation (SD)] age 64.9 [8.6]) with malignant gastric outlet obstruction were included. Technical and clinical success (ability to tolerate an oral diet) were achieved in 91 % (10/11) and 80 % (8/10) of patients, respectively. There was one adverse event (9 %) due to stent migration. Two patients (18 %) required re-intervention for stent obstruction secondary to food impaction. The mean (SD) time to a low residue diet was 3.5 (2.4) days. CONCLUSION: M-EPASS appears to facilitate the technique of EUS-GE, potentially enhancing its safety and clinical adoption. Larger studies are needed to validate this innovative approach to gastric outlet obstruction.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".