Underwater endoscopic colorectal polyp resection: Feasibility in everyday clinical practice
Bibliographic record
Abstract
Background Endoscopic mucosal resection is well-established for resecting flat or sessile benign colon polyps. The novel underwater endoscopic mucosal resection eschews submucosal injection prior to endoscopic mucosal resection. Reports about underwater endoscopic mucosal resection were limited to small series of single and/or tertiary-care referral centers, with single or supervised operators. Objective The purpose of this study was to determine feasibility and efficacy of underwater resection of polyps of any morphology (underwater polypectomy, here includes underwater endoscopic mucosal resection) in routine clinical practice. Methods This study involved a comparison of colonoscopy records of two community hospitals (January 2015–December 2016) for underwater polypectomy ( n = 195) and gas insufflation polypectomy ( n = 186). Results Comparable demographics, procedural data, overall distribution, morphology and size of resected lesions, number of en bloc and R0 resections (any polyp morphology and size); exception: overall, underwater polypectomy pedunculated polyps were significantly larger than those in the gas insufflation polypectomy group, p = 0.030. Underwater polypectomy (median, min) resection time was significantly shorter than gas insufflation polypectomy: sessile and flat polyps 6–9 mm, 0.8 vs 2.7 ( p = 0.040); 10–19 mm, 2.0 vs 3.3 ( p = 0.025), respectively; pedunculated polyps 6–19 mm, 0.8 vs 3.3 ( p < 0.001). Underwater polypectomy resection of pedunculated polyps 6–19 mm showed significantly less immediate bleeding: 11.1% vs 1.5%, respectively ( p = 0.031). Conclusions Underwater polypectomy can be efficaciously used in routine clinical practice for the complete resection of colon polyps, with several advantages over gas insufflation polypectomy.
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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 | 0.004 | 0.022 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".