MétaCan
Menu
← Back to cohort
Record W3008170492 · doi:10.1093/jcag/gwz047.081

A82 SUCCESSFUL RESECTION OF GRADE 1 DUODENAL NEUROENDOCRINE TUMOURS USING ENDOSCOPIC TECHNIQUES IN TWO CANADIAN HOSPITALS

2020· article· en· W3008170492 on OpenAlexaffabout
Natasha Klemm, Destiny Lu-Cleary, Daljeet Chahal, Roberto Trasolini, Eric Lam, Fergal Donnellan

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsVancouver General HospitalSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineDuodenal bulbEndoscopic mucosal resectionSurgeryPerforationLymphovascular invasionEndoscopyPolypectomyDuodenoscopyDuodenumInternal medicineCancerMetastasisColonoscopyColorectal cancer

Abstract

fetched live from OpenAlex

Abstract Background Given the rarity of duodenal neuroendocrine tumours (dNETs), limited guidelines exist for resection of well-differentiated, ≤10 mm dNETS. As incidence rises, alternatives to surgery are valuable. We present 9 cases of endoscopic dNET resections and a literature review. Aims To demonstrate efficacy and safety of endoscopic resection for dNETs ≤10 mm at 2 Canadian hospitals. Methods We retrospectively analyzed data on 7 patients that had endoscopic dNET resection from 2013–2018. Endoscopic resection occurred if dNETs were ≤10 mm in diameter, did not extend to the muscularis propria and lymphovascular invasion was absent. WHO 2017 classification was used. Results All patients had biopsies and 5 (71%) had EUS prior to resection; 4 females and 3 males underwent resection of 9 dNETs; 2 via cap-assisted snare polypectomy; 4 with cap-assisted band mucosectomy; and 2 over-the-scope clip-assisted resection. The median size was 10 mm (4–11); 6 (67%) dNETS were found in the duodenal bulb, 2 at the D1/D2 junction and 1 in D2 alone. The median age was 68.5 (50–79) years. All dNETs were submucosal and well-differentiated. The dNETs were resected en bloc, but 3 did not have clear margins. Two procedures were complicated by duodenal perforation; 1 requiring surgery and 18 days in hospital. One case was complicated by bleeding with successful endoscopic hemostasis. The majority (75%) of resections were day procedures. Patients were followed for 6–12 months with an EGD or chromogrannin A. None of the patients had endoscopic residual disease, but 1 patient required a second procedure to remove a dNET left in situ following the initial resection of 2 dNETs 12 months earlier. In our literature review of 178 patients, the majority of dNETs were resected by EMR 81% (150/185) versus ESD, similar to our experience. Patients were slightly younger with a mean age of 63.28, and most dNETs (46%) were found in the duodenal bulb. Complications included intraoperative bleeding, perforation and death in 17 (9.55%), 9 (5.06%) and 1 (0.06%) patient(s) respectively. The rate of recurrence was 4/178 (2.25%) and patients had a mean follow up of 26.1 months. Conclusions Well-differentiated dNETs ≤10 mm in diameter can be successfully resected endoscopically. Complications can be managed intraoperatively and hospital stay remains minimal. 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)0.002
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 score0.294
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.307
Teacher spread0.289 · 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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of Gastroenterology→Same topicNeuroendocrine Tumor Research Advances→French-language works237,207→