A124 INITIAL EXPERIENCES AND OUTCOMES IN LAUNCHING AN ESD PROGRAM IN CANADA
Bibliographic record
Abstract
Abstract Background Endoscopic submucosal dissection (ESD) is emerging as the preferred modality for curative resection of certain gastrointestinal lesions, yet it has a steep learning curve. Formal ESD training in Canada is limited, thus several endoscopists have sought training abroad. There are no data on the initial outcomes of ESD in Canada. Aims To describe the experience of a single advanced endoscopist (P.B.) who completed a mentor-apprentice model of ESD training in Europe and recently launched an ESD service in Canada. Methods Formal training in submucosal endoscopy was completed over a 12-month period (Sep 2018-Aug 2019) in Milan, Italy involving a stepwise progression through case observation (n=40), use of animal models (n=10), partial completion of human cases under direct supervision (n=25), and independent completion of human cases (n=19). Upon return to Calgary, AB, the program was promoted via grand rounds, an evening launch event and word-of-mouth. Patient and lesion characteristics, as well as procedure details and ESD outcomes were recorded prospectively in a database and used to complete a practice audit. Cases were divided into two timeframes (first 18 vs second 18 cases) and then compared with respect to specimen size, resection speed, R0 resection rate, and adverse event (AE) rate using the Mann-Whitney U and two-proportion Z-tests. Results From Nov 2019 to Sep 2021, 36 lesions were treated by ESD in 34 patients (mean (SD) age=66.5 (13.5) years). Most lesions were located in the rectum (44.4%) or stomach (41.7%); 21 (58.3%) were neoplastic, of which 5 (23.8%) were submucosal carcinomas, 11 (52.3%) were mucosal carcinomas (7 m1/Tis, 4 m2-3/T1a), and 5 (23.8%) were neuroendocrine tumors. The overall en bloc resection rate was 97.2% (35/36 lesions). In comparing the first 18 cases to the second 18 cases (Table 1), there were non-significant trends toward increases in mean specimen size (5.4 to 8.6 cm2, P=0.07) and R0 resection rate (62.5% to 84.6%, P=0.24). Resection speed increased significantly (2.97 to 6.25 cm2/hr, P=0.04), while AE rates remained the same (11.1%); namely 2 episodes of bleeding requiring repeat endoscopy in each set of cases. There were no perforations or intra-abdominal infections. Conclusions With appropriate training and support, ESD can be performed safely and effectively in a Canadian context. Proficiency can be expected to improve significantly within the first 2 years of independent ESD practice without compromising safety. 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 | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".