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Record W2790792101 · doi:10.1136/flgastro-2017-100919

Curriculum review: colorectal cancer surveillance and management of dysplasia in IBD

2018· review· en· W2790792101 on OpenAlexaff
Hajir Ibraheim, Angad Dhillon, Ioannis Koumoutsos, Shraddha Gulati, Bu Hayee

Bibliographic record

VenueFrontline Gastroenterology · 2018
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsSt. Thomas Hospital
FundersNational Institute for Health and Care Research
KeywordsMedicineChromoendoscopyDysplasiaInflammatory bowel diseaseColorectal cancerGeneral surgeryEndomicroscopyEndoscopic mucosal resectionColonoscopyReferralInternal medicineDiseaseEndoscopyGastroenterologyCancerFamily medicine

Abstract

fetched live from OpenAlex

The significantly increased risk of colorectal cancer (CRC) in longstanding colonic inflammatory bowel disease (IBD) justifies the need for endoscopic surveillance. Unlike sporadic CRC, IBD-related CRC does not always follow the predictable sequence of low-grade to high-grade dysplasia and finally to invasive carcinoma, probably because the genetic events shared by both diseases occur in different sequences and frequencies. Surveillance is recommended for patients who have had colonic disease for at least 8-10 years either annually, every 3 years or every 5 years with the interval dependant on the presence of additional risk factors. Currently, the recommended endoscopic strategy is high-definition chromoendoscopy with targeted biopsies, although the associated lengthier procedure time and need for experienced endoscopists has limited its uniform uptake in daily practice. There is no clear consensus on the management of dysplasia, which continues to be a challenging area particularly when endoscopically invisible. Management options include complete resection (and/or referral to a tertiary centre), close surveillance or proctocolectomy. Technical advances in endoscopic imaging such as confocal laser endomicroscopy, show exciting potential in increasing dysplasia detection rates but are still far from being routinely used in clinical practice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.851
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.322
Teacher spread0.303 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2018
Admission routes1
Has abstractyes

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