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Record W4414321826 · doi:10.1097/mcg.0000000000002242

Standardizing Success and Troubleshooting in EUS-Guided Gastroenterostomy

2025· article· en· W4414321826 on OpenAlexaff
Giuseppe Vanella, Francesco Frigo, Michiel Bronswijk, Roy van Wanroij, Yen‐I Chen, Kenneth F. Binmoeller, Manuel Pérez‐Miranda, Roberto Leone, Prabhleen Chahal, Shannon M. Chan, Manol Jovani, Amy Tyberg, Enrique Pérez‐Cuadrado‐Robles, Reem Z. Sharaiha, Marc Barthet, Pierre H. Deprez, Todd H. Baron, Michel Kahaleh, Douglas G. Adler, Mouen A. Khashab, Anthony Yuen Bun Teoh, Takao Itoi, Rastislav Kunda, Van der Merwe, Paolo Giorgio Arcidiacono

Bibliographic record

VenueJournal of Clinical Gastroenterology · 2025
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsMcGill University Health Centre
FundersBoston Scientific Corporation
KeywordsTroubleshootingGastroenterostomyGastric outlet obstructionLearning curveJejunostomyClinical Practice

Abstract

fetched live from OpenAlex

EUS-guided gastroenterostomy (EUS-GE) is rapidly emerging as a pivotal procedure in the management of gastric outlet obstruction due to its advantages over historical comparators such as surgical gastroenterostomy and endoscopic placement of gastroduodenal stents. The ability to create a stable surgical-range connection between 2 lumens, distant from the tumor, with the minimally invasive nature of an endoscopic procedure, offers high clinical efficacy, acceptable safety, and low recurrence rates. However, widespread adoption is impeded by the steep learning curve and lack of standardized methodologies. Like other interventional EUS procedures, EUS-GE utilizes lumen apposing metal stents. Unlike drainage procedures, the target in EUS-GE is a mobile structure with a virtual resting caliber that needs to be distended to create the connection, making misdeployment a significant drawback. This comprehensive illustrated technical review dissects the general and specific technical principles of EUS-GE covering the equipment, scene, settings, and endoscopic signs of correct and incorrect placement. It provides a deeper insight into the wireless simplified EUS-GE technique, the EUS-guided double-balloon-occluded gastrojejunostomy bypass, and the direct technique. Through pragmatic tips, expert advice, and elucidative step-by-step videos, a systematic roadmap for mastering this intricate procedure is presented. By addressing common challenges and providing troubleshooting strategies, this review aims to demystify EUS-GE, equipping practitioners with the tools to achieve reproducible and optimal outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.431
Teacher spread0.388 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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