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S876 Utility of Pancolonic Dye Spray Chromoendoscopy for Dysplasia Detection and Management in Inflammatory Bowel Diseases

2021· article· en· W3210574170 on OpenAlexaffabout
Claudia Dziegielewski, Sarang Gupta, Jeffrey D. McCurdy, Richmond Sy, Nav Saloojee, Sanjay K. Murthy

Bibliographic record

VenueThe American Journal of Gastroenterology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsChromoendoscopyMedicineDysplasiaInflammatory bowel diseaseColonoscopyUlcerative colitisGastroenterologyEndoscopyInternal medicineColorectal cancerRadiologyDiseaseCancer

Abstract

fetched live from OpenAlex

Introduction: Patients with inflammatory bowel disease (IBD) involving the colorectum are at increased risk for the development of flat and poorly delineated dysplastic lesions. Pancolonic dye spray chromoendoscopy (DCE) is an adjunct to white light endoscopy (WLE) that enhances detection and delineation of such lesions. We evaluated the utility of DCE for lesion detection and/or management in patients with IBD who had visible (polypoid or flat lesions) or invisible (identified in non-targeted biopsies) dysplasia detected during high-definition (HD)-WLE. Methods: We retrospectively studied patients with colonic IBD from The Ottawa Hospital (Ottawa, Canada) who underwent DCE by a trained endoscopist, as follow-up for dysplasia detected during HD-WLE over a 7-year period (2013-2020). We assessed the ability of DCE to permit visualization of previously unidentified or poorly defined dysplasia, or to facilitate complete resection of poorly delineated dysplastic lesions. Results: Twenty-four patients were included (mean age 56.7±13.8 years, 50.0% male, 70.8% ulcerative colitis, mean disease duration 18.0±11.0 years, 70.8% moderate or severe disease activity historically, 41.7% remote history of dysplasia, and 4.2% PSC). More than 70% of patients were referred for DCE following detection of invisible dysplasia; the remainder were referred for surveillance of poorly defined flat dysplastic lesions. The dysplasia detection rate was 41.7% in HD-WLE, compared to 70.8% for DCE. For patients referred for DCE following detection of invisible dysplasia, DCE identified visible dysplasia at the same site in 8/17 (47.1%) patients, and visible dysplasia at a different site in 6/17 (35.3%) patients. For patients without prior invisible dysplasia, DCE identified new visible dysplasia in 3/7 (42.9%) of patients. DCE upgraded the highest grade of dysplasia and diagnosed CRC in 8.3% of patients, which was missed on index HD-WLE. DCE was unable to facilitate lesion resection in 12.5% of patients referred for poorly defined dysplastic lesions due to advanced lesion characteristics. Conclusion: In this study, DCE demonstrated utility in allowing detection of previously invisible dysplastic lesions in 33.3% patients, and in identifying a higher grade of dysplasia in 8.3% of patients. Further studies are needed to validate our findings. Given the low costs and risks associated with DCE, surveillance of patients with uncertain dysplastic findings on WLE using DCE is advisable.

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)0.001
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.238
Teacher spread0.233 · 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
Published2021
Admission routes2
Has abstractyes

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