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Record W4213153342 · doi:10.1093/jcag/gwab049.126

A127 ENDOSCOPIC MUCOSAL RESECTION FOR DYSPLASTIC AND NEOPLASTIC BARRETT’S ESOPHAGUS: FINDINGS FROM A FOREGUT NEOPLASIA MULTIDISCIPLINARY DATABASE

2022· article· en· W4213153342 on OpenAlexaffabout
Hillary Wilson, Pam Blakely, Jerry T. Dang, Warren Sun, R. David McLean, Shahzeer Karmali, Chee Siong Wong

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsMedicineEndoscopic mucosal resectionEsophagectomyBarrett's esophagusDysplasiaEsophagusIntestinal metaplasiaInternal medicineAdenocarcinomaGeneral surgeryGastroenterologyDatabaseSurgeryEndoscopyEsophageal cancerCancer

Abstract

fetched live from OpenAlex

Abstract Background Previously, Barrett’s esophagus with high grade dysplasia (HGD) or neoplasia was treated with esophagectomy, which is associated with a high postoperative morbidity and mortality rate. Recent guidelines support the use of endoscopic mucosal resection (EMR) for T1a esophageal adenocarcinoma (EAC) and potentially T1b EAC; however, data on long term outcomes of endoscopic treatment is lacking. We created a combined prospective and retrospective multidisciplinary database to monitor outcomes of patients with Barrett’s esophagus undergoing endoscopic treatment. Aims Our primary aim was to compare outcomes of EMR and esophagectomy in patients presenting with BE and HGD, and/or early EAC. Methods A collaboration of gastroenterologists, general surgeons and thoracic surgeons from the University of Alberta, Edmonton, Alberta, provided input on the development of the database. All patients referred to the Northern Alberta Endoscopic Ablation Program from 2009–2021 who received at least one endoscopic treatment were included. A sub-analysis of all patients with pathologic confirmation of HGD, and/or early EAC was conducted to compare outcomes of EMR and esophagectomy. Results A total of 212 patients have been entered into the database. The most common findings were HGD, low grade dysplasia (LGD), and adenocarcinoma, respectively. All patients (n=48) who had at least LGD reached complete eradication of dysplasia (CE-D) and 95.8% reached complete eradication of intestinal metaplasia (CE-IM). Of those patients that reached CE-D, 8.3% developed recurrence of dysplasia (n=4). In the sub-analysis, 74 patients (76.3%) received endoscopic therapy while 23 patients (23.7%) received endoscopic therapy then ultimately an esophagectomy. There were significantly more T1b lesions in the esophagectomy group compared to the EMR group ( p<0.0001). Of all the patients in the EMR group, only 5.4% (n=4) had treatment related complications. Of patients receiving an esophagectomy, 60.9% (n=14) experienced treatment related complications. The mean length of stay for patients in the EMR group was 1.03 +/- 0.2 days, compared to 16.5 +/- 11.8 days for esophagectomy ( p<0.0001). Conclusions EMR provides definitive and durable treatment for BE lesions classified as T1b or less severe, with fewer complications and a shorter length of hospital stay than esophagectomy. Funding Agencies Alberta Innovates Health Solutions

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)0.002
metaresearch head score (Gemma)0.005
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 score0.067
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.267
Teacher spread0.254 · 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
Published2022
Admission routes2
Has abstractyes

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