Image-enhanced endoscopy and endoscopic resection practices in the colon among endoscopists in India
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background and study aims Clinical practice patterns for image-enhanced endoscopy (IEE) and colonic endoscopic resection practices vary among endoscopists. We conducted a survey to understand the differences in IEE and colonoscopic resection practices among endoscopists from India. Methods An online cross-sectional survey comprising 40 questions regarding quality control of colonoscopy, IEE, and colonic endoscopic resection practices was circulated through the registry of the Indian Society of Gastroenterology and Association of Colon and Rectal Surgeons of India. Participation was voluntary and response to all questions was compulsory. Results There were 205 respondents to the survey (93.2 % gastroenterologists, 90.2 % male, 54.6 % aged 30 to 40 years, 36.1 % working in academic institution, 36.1 % working in corporate hospitals). Of the endoscopists, 50.7 % had no training in IEE and 10.7 % performed endoscopy on systems without any IEE modalities. Endoscopists with more experience were more likely to use IEE modalities in practice routinely (P = 0.007). Twenty percent never used IEE to classify polyps. Sixty percent of respondents did not use dye-chromoendoscopy. Less experienced endoscopists used viscous solutions as submucosal injectate (P = 0.036) more often. Of the respondents, 44 % never tattooed the site of endoscopic resection. Ablation of edges post-endoscopic mucosal resection was not done by 25.5 % respondents. Most respondents used electronic chromoendoscopy (36.1 %) or random four-quadrant sampling (35.6 %) for surveillance in inflammatory bowel disease. Surveillance post-endoscopic resection was done arbitrarily by 24 % respondents at 6 months to 1 year. Conclusions There are several lacunae in the practice of IEE and colonic endoscopic resection among endoscopists, with need for programs for privileging, credentialing and proctoring these endoscopic skills.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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