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Record W4408636424 · doi:10.1002/jgh3.70113

Dysplasia and Malignancy in Colonic Polyps: Preparing for a Resect and Discard Strategy in Canada

2025· article· en· W4408636424 on OpenAlexaffabout
V. Patel, Robert Bechara, Mandip Rai

Bibliographic record

VenueJGH Open · 2025
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsMalignancyDysplasiaGeneral surgeryMedicineInternal medicine

Abstract

fetched live from OpenAlex

Background/Aims: Colonoscopies are commonly performed to evaluate and remove polyps. Currently, at most centers in Canada, all resected polyps are submitted for histologic examination. A resect and discard strategy has not been widely adopted in the Canadian population. The objective of this study was to characterize polyps and their rates of dysplasia. Methods/Results: Colonoscopies and pathology reports were analyzed at a tertiary care hospital. We recorded polyp size, histology, and the presence of high-grade dysplasia (HGD)/cancer. Out of a total of 2218 colonoscopies, 2945 polyps were removed. In descending order, tubular adenomas, hyperplastic, sessile serrated, tubulovillous, and inflammatory polyps represented 67.4%, 16.2%, 9.9%, 5.6%, and 0.8% of all polyps, respectively. Regarding size, 1703 polyps were between 1 and 5 mm, with only 2 (0.12%) showing HGD. Similarly, in the 6-9 mm group, there were 699 polyps, with only 3 (0.43%) showing HGD. Neither of these groups had evidence of cancer. In contrast, the > 10 mm group had 543 polyps, of which 87 (16.02%) showed HGD, and 15 (2.76%) exhibited cancer. In our patient population, only 0.04% of patients would have a change in their screening interval due to HGD in polyps that were < 5 mm in size. Conclusions: Based on these findings, a resect and discard strategy should be further evaluated for diminutive polyps in this population. While current recommendations for post-polypectomy screening include pathological assessment, further research on screening intervals based on size, location, and optical diagnosis may reduce resource utilization without compromising outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.315
Teacher spread0.296 · 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.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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