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Record W4310181370 · doi:10.5946/ce.2022.114

Endoscopic ultrasound-directed transgastric endoscopic retrograde cholangiopancreatography for patients with Roux-en-Y gastric bypass anatomy: technical overview

2022· review· en· W4310181370 on OpenAlexaff
Hirokazu Honda, Jeffrey D. Mosko, Ryosuke Kobayashi, Andras B. Fecso, Bong Sik Kim, Scott Schoeman, Gary R. May

Bibliographic record

VenueClinical Endoscopy · 2022
Typereview
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineEndoscopic retrograde cholangiopancreatographyGastric bypassEndoscopic ultrasoundRoux-en-Y anastomosisLaparoscopyAmpullaBalloonRadiologyEndoscopySurgeryGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Endoscopic retrograde cholangiopancreatography (ERCP) in patients with Roux-en-Y gastric bypass anatomy is a well-documented challenge. Traditionally, this problem has been overcome with adjunctive techniques, such as device-assisted ERCP, including double-balloon or single-balloon enteroscopy and laparoscopy-assisted transgastric ERCP. Endoscopic ultrasound-directed transgastric ERCP (EDGE) is a novel technique that enables access to the ampulla using a duodenoscope without surgical intervention and has shown high clinical and technical success rates in recent studies. However, this approach is technically demanding, necessitating a thorough understanding of the gastrointestinal anatomy as well as high operator experience. In this review, we provide a technical overview of EDGE in parallel with our personal experience at our center and propose a simple algorithm to select patients for its appropriate application. In conjunction, the outcomes of EDGE compared with those of device-assisted and laparoscopy-assisted transgastric ERCP will be discussed.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.378
Teacher spread0.330 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2022
Admission routes1
Has abstractyes

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