A86 SUBMUCOSAL INJECTION FOR POLYPECTOMY AND INTERVENTIONAL ENDOSCOPY: AN INTERNATIONAL SURVEY
Bibliographic record
Abstract
Abstract Background Submucosal injection (SI) is used for standard polypectomies or during complex endoscopic interventions. SI helps to facilitate endoscopic resection and to prevent complications such as bleeding or perforation. Aims We were interested to evaluate endoscopists practice patterns of using SI during routine standard polypectomy and complex endotherapeutic procedures. Methods An online survey using the Google Form application was distributed through medical societies. Survey domains included training and practice characteristics of participating endoscopists as well as questions regarding the use of SI products for endoscopy procedures. Results A total of 236 endoscopists (mainly from the US, Canada, and Europe) participated in the survey. About half (48%) of endoscopists start using SI for routine polypectomies when polyps are larger than 10 mm, while 37% of endoscopist report having a size threshold larger than 15mm for using SI (22% report using SI starting at >15 mm, and 15% report using SI starting at >20 mm). Only a minority (11%) of endoscopists report using SI for polyps <10 mm and starting SI at 6 mm. However, 30,3% of endoscopists reported that their size threshold for using SI during polypectomies has decreased in recent years. 83% reported that using SI is beneficial for en-bloc resection, avoiding perforation (91,5%), avoiding thermic lesions (80%) and identifying dysplastic tissue (54,5%). Normal saline is the submucosal agent most commonly available for endoscopists (86,4%), followed by Eleview (66,8%), and ORISE Gel (20%). “Short lasting lift” and “cost” are reported concerns when opting for a specific SI solution. Methylene blue is the coloring agent that is most commonly used (68,9%). Excellent submucosal elevation, availability, and length of action are the most important features an SI should have according to endoscopists’ responses. Conclusions The use of SI is common during endoscopy procedures. For standard colorectal polypectomy procedures, most endoscopists start using SI only for polyps larger than 10mm. SI is used by endoscopists to prevent complications, improve endoscopic resection and to identify dysplastic tissue. 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".