A Randomized Trial Comparing High Definition Colonoscopy Alone With High Definition Dye Spraying and Electronic Virtual Chromoendoscopy for Detection of Colonic Neoplastic Lesions During IBD Surveillance Colonoscopy
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Dye spraying chromoendoscopy (DCE) is recommended for the detection of colonic neoplastic lesions in inflammatory bowel disease (IBD). The majority of neoplastic lesions are visible endoscopically and therefore targeted biopsies are appropriate for surveillance colonoscopy. To compare three different techniques for surveillance colonoscopy to detect colonic neoplastic lesions in IBD patients: high definition (HD), (DCE), or virtual chromoendoscopy (VCE) using iSCAN image enhanced colonoscopy. METHODS: A randomized non-inferiority trial was conducted to determine the detection rates of neoplastic lesions in IBD patients with longstanding colitis. Patients with inactive disease were enrolled into three arms of the study. Endoscopic neoplastic lesions were classified by the Paris classification and Kudo pit pattern, then histologically classified by the Vienna classification. RESULTS: A total of 270 patients (55% men; age range 20-77 years, median age 49 years) were assessed by HD (n=90), VCE (n=90), or DCE (n=90). Neoplastic lesion detection rates in the VCE arm was non-inferior to the DCE arm. HD was non-inferior to either DCE or VCE for detection of all neoplastic lesions. In the lesions detected, location at right colon and the Kudo pit pattern were predictive of neoplastic lesions (OR 6.52 (1.98-22.5 and OR 21.50 (8.65-60.10), respectively). CONCLUSIONS: In this randomized trial, VCE or HD-WLE is not inferior to dye spraying colonoscopy for detection of colonic neoplastic lesions during surveillance colonoscopy. In fact, in this study HD-WLE alone was sufficient for detection of dysplasia, adenocarcinoma or all neoplastic lesions.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it