A82 A SURVEY OF TRAINING PATHWAYS AND PRACTICE TRENDS OF ENDOSCOPIC SUBMUCOSAL DISSECTION IN CANADA
Bibliographic record
Abstract
Abstract Background Endoscopic submucosal dissection (ESD) has become the established standard for endoscopic removal of large gastrointestinal (GI) lesions and early GI malignancies, with improved outcomes compared to traditional endoscopic techniques and offers an alternative to surgery. However, ESD is technically challenging and requires significant healthcare infrastructure. As such, its adoption in Canada was slow relative to Asia and Europe. Thus far, the practice of ESD has been limited to a small number of tertiary centers. Currently, the availability and practice of ESD across Canada remains unclear. Aims To provide a descriptive overview of the training pathways and practice trends of endoscopists performing ESD in Canada. Methods ESD practitioners across Canada were identified from internal networks and by contacting respective endoscopy units. All endoscopists currently accepting ESD referrals were invited to participate in a cross-sectional survey that was distributed via SurveyMonkey. Results 27 ESD practitioners were identified; current survey response rate was 44% although is expected to increase. Median years of independent ESD practice was 5 (IQR 2.75). All practitioners underwent international ESD training of some type. 92% attended short-term training courses. 50% pursued international ESD fellowship training. 92% received training on animal models. 58% and 33% performed hands-on human upper and lower GI ESD respectively prior to independent practice. In practice, 67% of practitioners noted an increase in number of ESD procedures performed per year from 2015 to 2019. 67% rated the awareness of appropriate ESD indications by referring physicians to be “not so aware” or lower. 75% of practitioners report a patient wait time for ESD of 1–3 months. 67% and 75% rated the difficulty of securing endoscopy time and anesthesia support for ESD respectively to be “difficult” or “very difficult”. 75% were “dissatisfied” or “very dissatisfied” with their institution’s healthcare infrastructure to support ESD. 25% perceived their institution as supportive in expanding the practice of ESD. Conclusions A number of challenges exist for the adoption of ESD in Canada. Training pathways are highly variable, with no set standards and most practitioners pursue international training. In practice, the majority of practitioners express dissatisfaction with their access to necessary infrastructure for performing ESD and feel poorly supported by their centers in expanding its practice. As ESD is becoming the accepted standard in allowing for the minimally invasive treatment of indicated GI lesions; greater collaboration between practitioners, institutions, and healthcare systems is crucial to standardize ESD training and to ensure improved patient access. Funding Agencies None
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".