A Nationwide Survey of Training Pathways and Practice Trends of Endoscopic Submucosal Dissection in Canada
Bibliographic record
Abstract
Background: Endoscopic submucosal dissection (ESD) has become an established standard for endoscopic removal of large gastrointestinal (GI) lesions and early GI malignancies. However, ESD is technically challenging and requires significant health care infrastructure. As such, its adoption in Canada has been relatively slow. The practice of ESD across Canada remains unclear. Our study aimed to provide a descriptive overview of training pathways and practice trends of ESD in Canada. Methods: Current ESD practitioners across Canada were identified and invited to participate in an anonymous cross-sectional survey. Results: Twenty-seven ESD practitioners were identified; survey response rate was 74%. Respondents were from 15 different institutions. All practitioners underwent international ESD training of some type. Fifty per cent pursued long-term ESD training programs. Ninety-five per cent attended short-term training courses. Sixty per cent and 40% performed hands-on live human upper and lower GI ESD, respectively, before independent practice. In practice, 70% saw an increase per year in number of procedures performed from 2015 to 2019. Sixty per cent were dissatisfied with their institution's health care infrastructure to support ESD. Thirty-five per cent perceived their institution as supportive of expanding the practice of ESD. Conclusions: Several challenges exist to the adoption of ESD in Canada. Training pathways are variable, with no set standards. In practice, practitioners express dissatisfaction with access to necessary infrastructure and feel poorly supported in expanding the practice of ESD. As ESD is increasingly the accepted standard for the treatment of many neoplastic GI lesions, greater collaboration between practitioners and institutions is crucial to standardize training and ensure patient access.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".