A93 VOLUME OF EMR EXPOSURE IN TRAINING IS CORRELATED WITH POLYPECTOMY COGNITIVE COMPETENCE AMONGST RECENT GASTROENTEROLOGY GRADUATES
Bibliographic record
Abstract
Abstract Background Competence in performing polypectomy is increasingly appreciated as a colonoscopy quality metric, as incomplete resection can lead to post-colonoscopy colorectal cancer, particularly for polyps removed using piecemeal endoscopic mucosal resection (EMR). The relationship between training experiences and cognitive competence in polypectomy has not been previously described. Aims We aimed to examine associations between training and assessment experiences, self-reported comfort, and cognitive competence in polypectomy amongst recent graduates of Canadian gastroenterology training programs. Methods An online survey was distributed to recent GI graduates (≤5 years in independent practice). The survey comprised 4 sections: (1) demographics; (2) training and assessment experiences in colonoscopy, polypectomy, and EMR; (3) self-reported comfort in performing aspects of polypectomy outlined in the Direct Observation of Polypectomy Skills Assessment Tool; and (4) performance on a 22-item multiple choice quiz intended to assess cognitive competence in polypectomy (items and correct responses to which were determined a priori based on agreement of two experts). Data was analyzed using descriptive statistics and associations between predictors (demographics, training/assessment experiences, self-reported comfort) and outcomes (quiz score) were assessed using multiple linear regression. Results There were 28 survey respondents, comprising 13 (46%) who trained in advanced endoscopy, 5 (18%) in hepatology, 2 (7%) in motility, 1 (4%) in IBD, 1 (4%) in nutrition, and 6 (21%) with no advanced training. This cohort had a mean (SD) duration in independent practice of 29.0 (18.4) months. Their mean (SD) annual volume of colonoscopy, polypectomy, and EMR in independent practice was 530 (221), 182 (76), 28 (16), respectively and they had completed 525 (203) colonoscopies, 146 (92) polypectomies, and 23 (20) EMRs in their prior training. Their mean (SD) quiz score was 71.9% (13.2%). ANOVA revealed significant score differences based on fellowship history, with those trained in advanced endoscopy achieving the highest scores (81.1%, P=0.01). Multiple linear regression revealed that the number of EMRs completed during training was significantly correlated with quiz performance (B=0.60, P=0.03). Conclusions EMR experience during training appears to be associated with cognitive competence in polypectomy in independent practice. These results suggest increasing exposure to EMR in training may improve polypectomy quality amongst practicing endoscopists. Funding Agencies CAG
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".