Perspectives on endoscopic surveillance of dysplasia in inflammatory bowel disease: a survey of academic gastroenterologists
Bibliographic record
Abstract
BACKGROUND AND STUDY AIMS: Dye-based chromoendoscopy (DBC) is the preferred method for endoscopic dysplasia surveillance in patients with inflammatory bowel disease (IBD). We sought to examine the uptake of, and perception toward DBC among academic gastroenterologists. METHODS: We conducted an online survey of academic members of the Canadian Association of Gastroenterology to assess their current dysplasia surveillance practice, uptake of DBC, and perceived barriers to adoption of DBC. RESULTS: Of the 150 physicians contacted, 49 (32.7 %) responded to the survey. The majority of respondents reported subspecialty training in IBD (71.4 %), and the median number of years in practice was 12. White-light endoscopy with random colonic biopsies was the preferred dysplasia screening method (73.5 %). Only 26.5 % of respondents routinely used DBC, despite institutional availability of over 60 %. The major barriers to adoption of DBC were concerns about procedure duration (46.9 %), concerns about cost (44.9 %), and inadequate training (40.8 %). CONCLUSION: There is low uptake of DBC for dysplasia surveillance in IBD patients among academic gastroenterologists practicing in Canada. Additional studies should be completed to determine how to improve the uptake of DBC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".