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Record W3134417071 · doi:10.1093/jcag/gwab002.135

A137 LAPAROSCOPIC ENDOSCOPIC COOPERATIVE SURGERY FOR GASTROINTESTINAL STROMAL TUMOURS: EARLY EXPERIENCE IN A CANADIAN ACADEMIC CENTRE

2021· article· en· W3134417071 on OpenAlexaffabout
Daniel J. Low, Andras B. Fecso, Tyler R. Chesney, Jeffrey D. Mosko

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGiSTMedicineLesionStromal cellSurgeryWedge resectionLaparoscopyResectionPathology

Abstract

fetched live from OpenAlex

Abstract Background Surgical resection with laparoscopic gastric wedge resection is commonly conducted for local management of gastrointestinal stromal tumours (GIST). However, resection margins are often difficult to appreciate for lesions with larger endophytic components. As a result, tumour margins may be compromised or excess tissue resected. Laparoscopic endoscopic cooperative surgery (LECS) was developed in Japan to overcome these technical challenges in the resection of subepithelial lesions, including GISTs. Here, we present a case report of an early Canadian experience utilizing LECS in the management of gastric GIST. Aims To describe a case report of an early Canadian experience of LECS for the resection of a gastric GIST. Methods We performed a review of the literature and describe a case of LECS. Results We present a 70-year-old female referred to our centre for endoscopic resection of a 2.5x2.5cm histologically confirmed gastric GIST (low mitotic index and no known metastases). Repeat endoscopic evaluation at our centre confirmed a 25-30mm subepithelial lesion with both exophytic (small) and endophytic (large) components. After tumour board review, we opted for a LECS approach. In the OR, the lesion was identified endoscopically and marked with a Dual J-Knife (Olympus). The margins were injected with a combination of Voluven, methylene blue, and dilute epinephrine. A circumferential incision was then completed using standard ESD technique. The lesion was subsequently identified laparoscopically, with endoscopic guidance, along the lesser curvature. The lesser omentum was mobilized for clear visualization of the serosa around the lesion. A full thickness incision was made endoscopically along the distal aspect of lesion. Full thickness resection was continued endoscopically for one third of the circumference of the lesion until gastric insufflation became compromised. Full thickness resection was completed laparoscopically under endoscopic guidance with grossly negative margins. The defect was closed with running laparoscopic sutures. Endoscopic leak test was performed which was negative. The specimen was retrieved and follow up pathology demonstrated a GIST with low mitotic index and negative margins without tumour rupture. Conclusions In a review of the literature, LECS appears to minimize tissue resection while maintaining R0 resection rates. This technique is especially useful for subepithelial lesions with larger endophytic and transmural components. It has an excellent safety profile with a less than 5% anastomotic leak rate. As such, the literature supports LECS as a suitable procedure for gastric subepithelial lesions <50 mm. However, further studies are needed to compare it systematically to conventional laparoscopic wedge resection in addition to other innovative endoscopic techniques such as STER and EFTR. 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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.431
Threshold uncertainty score0.856

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.294
Teacher spread0.268 · 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 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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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