Incomplete resection of colorectal polyps of 4–20 mm in size when using a cold snare, and its associated factors
Bibliographic record
Abstract
BACKGROUND : Cold snare polypectomy (CSP) is increasingly used for polypectomy and is recommended as the first-line modality for small (< 10 mm) polyps. This study aimed to evaluate incomplete resection rates (IRRs) when using CSP for colorectal polyps of 4-20 mm. METHODS : Adults (45-80 years) undergoing screening, surveillance, or diagnostic colonoscopy and CSP by one of nine endoscopists were included. The primary outcome was the IRR for colorectal polyps of 4-20 mm, defined as the presence of polyp tissue in marginal biopsies after resection of serrated polyps or adenomas. Secondary outcomes included the IRR for serrated polyps, ease of resection, and complications. RESULTS: 413 patients were included (mean age 63; 48 % women) and 182 polyps sized 4-20 mm were detected and removed by CSP. CSP required conversion to hot snare resection in < 1 % of polyps of < 10 mm and 44 % of polyps sized 10-20 mm. The IRRs for polyps < 10 mm and ≥ 10 mm were 18 % and 21 %. The IRR was higher for serrated polyps (26 %) compared with adenomas (16 %). The IRR was higher for flat (IIa) polyps (odds ratio [OR] 2.9, 95 %CI 1.1-7.4); and when resection was judged as difficult (OR 4.2, 95 %CI 1.5-12.1), piecemeal resection was performed (OR 6.6, 95 %CI 2.0-22.0), or visible residual polyp was present after the initial resection (OR 5.4, 95 %CI 2.0-14.9). Polyp location, use of a dedicated cold snare, and submucosal injection were not associated with incomplete resection. Intraprocedural bleeding requiring endoscopic intervention occurred in 4.7 %. CONCLUSIONS : CSP for polyps of 4-9 mm is safe and feasible; however, for lesions ≥ 10 mm, CSP failure occurs frequently, and the IRR remains high even after technical success. Incomplete resection was associated with flat polyps, visual residual polyp, piecemeal resection, and difficult polypectomies.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".