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Record W4213202304 · doi:10.1093/jcag/gwab049.032

A33 ENDOSCOPIC ULTRASOUND-GUIDED GASTROJEJUNOSTOMY VERSUS SURGICAL GASTROJEJUNOSTOMY AND ENTERAL STENTING FOR THE TREATMENT OF MALIGNANT GASTRIC OUTLET OBSTRUCTION: A SYSTEMATIC REVIEW AND META-ANALYSIS

2022· review· en· W4213202304 on OpenAlexaff
Joshua A. Benchaya, Y Chen, Myriam Martel, Alan Barkun, Jonathan Wyse, Lorenzo Ferri, Corey Miller

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typereview
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsJewish General HospitalMcGill University Health Centre
Fundersnot available
KeywordsMedicineEndoscopic ultrasoundGastric outlet obstructionMeta-analysisEnteral administrationOdds ratioEndoscopic stentingStentAdverse effectSurgeryParenteral nutritionRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Gastric outlet obstruction (GOO), often encountered in advanced malignancy, is associated with debilitating symptoms and decreased quality of life. Traditional management of this condition has been surgical gastrojejunostomy (SGJ) or enteral stenting (ES). While SGJ is highly effective, it is invasive and associated with high rates of morbidity. ES provides a less invasive approach with a lower risk of adverse events; however, it is associated with a significant risk of stent dysfunction with increased need for reintervention. Endoscopic ultrasound-guided gastrojejunostomy (EUS-GJ) is a novel modality in the management of GOO that aims to endoscopically bypass the obstruction with a lumen-apposing metal stent, with early studies suggesting good effectiveness and safety outcomes; but the data are limited. Aims To perform a systematic review and meta-analysis comparing the clinical outcomes of EUS-GJ to more traditional treatments of malignant GOO. Methods The study protocol was prospectively registered with the PROSPERO international database. The literature was systematically searched using MEDLINE, EMBASE and Web of Knowledge databases from inception through May 2021. Studies comparing EUS-GJ to ES or SGJ in patients with malignant GOO were included. Meta-analysis was performed with results reported as odds ratios (ORs) with 95% confidence intervals (CIs) using random effects models. The two primary outcomes of interest were clinical success without GOO recurrence and adverse events. Secondary outcome was technical success. Results Ten studies with a total of 1016 patients were included. EUS-GJ was associated with higher clinical success without GOO recurrence compared to SGJ or ES [OR: 2.19, 95% CI: 1.18–4.09, heterogeneity: P = 0.10; I2 = 59%]. Subgroup analysis showed higher clinical success without GOO recurrence compared to ES [OR: 5.31, 95% CI: 3.07–9.17], but no significant difference compared to SGJ [OR: 1.69, 95% CI: 0.76–3.72]. EUS-GJ was associated with fewer adverse events compared to SGJ and ES [OR: 0.28, 95% CI: 0.14–0.55] and compared to SGJ alone [OR: 0.20, 95% CI: 0.10–0.37], but no difference was noted when compared to ES alone [OR: 0.53, 95% CI: 0.15–1.87]. EUS-GJ was associated with decreased technical success compared to SGJ and ES [OR: 0.26, 95% CI: 0.09 – 0.75] and SGJ alone [OR: 0.14, 95% CI: 0.04–0.48]; however, there was no difference when compared to ES alone [OR: 0.43, 95% CI: 0.05–3.44]. Conclusions EUS-GJ provides a robust bypass with lower risk of recurrent obstruction compared to ES and fewer adverse events compared to SGJ. High quality prospective studies are needed to further characterize the role of EUS-GJ in the management of malignant GOO. Funding Agencies None

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0200.036
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.067
GPT teacher head0.323
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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