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Record W4247857726 · doi:10.1093/jcag/gwz006.268

A269 ENHANCED CHARACTERIZATION OF BARRETT’S ESOPHAGUS ISLANDS THROUGH A REVISION OF THE PRAGUE CRITERIA

2019· article· en· W4247857726 on OpenAlexaff
A S Dhillon, S Li, Pam Blakely, Christopher Kevin Wong

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineBarrett's esophagusGERDDysplasiaEsophagusConcordanceRadiofrequency ablationCryotherapyBiopsyEndoscopic mucosal resectionEndoscopyRadiologyGeneral surgerySurgeryInternal medicineRefluxAdenocarcinomaCancerAblationDisease

Abstract

fetched live from OpenAlex

Gastroesophageal reflux disease (GERD) remains one of the most common referrals to gastroenterology and is associated with a 10–15% risk of Barrett’s esophagus (BE). Although progression to esophageal adenocarcinoma is low in BE, current recommendations are for eradication therapy in patients found to have dysplasia on histology. Endoscopic eradication strategies range from radiofrequency ablation (RFA), photodynamic therapy, cryotherapy and endoscopic resection. The current standards in reporting BE extent via the Prague Criteria and biopsy protocol via the Seattle protocol do not address the finding of Barrett’s islands (BI) or their significance. Based on recent studies, BI not uncommon and may represent potential areas of missed dysplastic lesions. Our group attempted to implement a revised Prague classification system of the circumferential segment (C), maximum BE extent (M) and presence of BI measured from GE junction (I). i) To review the proportion of individuals referred for BE with BI outside of classic Prague C&M criteria utilizing an enhanced Prague classification system ii) To assess the concordance and variability of histology between biopsy samples of Barrett’s islands and Prague C&M lesions We retrospectively reviewed a single tertiary care centre and single endoscopist’s experience in patients referred with BE. All patients referred to the tertiary center through the years of 2014 – 2016 were evaluated with a second endoscopy with high definition white light and narrow band imaging. Depending on initial referral, management included; Barrett’s mapping, RFA or EMR. All cases were classified using an enhanced Prague criterion incorporating BI’s using the “I” nomenclature. Only the most proximal island was recorded. BE reports were conveyed as; “CxMxIx”. A total of 71 patients referred for BE were included. 40.8% (29/71) of all patients referred for BE were noted to have BI. A minority of these patients had biopsies of the islands as the majority underwent direct treatment. Of the individuals whom underwent biopsies, 3 cases had discordant results compared to histology within Prague C&M classification. Overall there was only fair inter-rater agreement between island and Prague histology, k=0.37 (p=0.05). Our findings indicate a high prevalence of BI among patients referred for BE and a moderate rate of discordance with histology. This highlights the need for referring physicians to identify and perform separate biopsies BI to referral for treatment Our proposed enhanced Prague classification represents a novel method of reporting BI systematically among endoscopist’s. Further studies on the implementation of an enhanced Prague criteria in relation to clinical outcomes should be conducted. 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)0.003
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.273
Teacher spread0.263 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

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