A Randomized Controlled Trial of Cold Snare Polypectomy Technique: Technique Matters More Than Snare Wire Diameter
Bibliographic record
Abstract
INTRODUCTION: Cold snare polypectomy (CSP) is safe and effective for the removal of small adenomas (≤10 mm); however, reported incomplete resection rates (IRRs) vary. The optimal CSP technique, where a wide margin of normal tissue is resected around the target lesion, and snare design have both been hypothesized to reduce the IRR after CSP. We sought to investigate the efficacy of a thin-wire versus thick-wire diameter snare on IRR, using the standardized CSP technique. METHODS: This was an international multicenter parallel design randomized trial with 17 endoscopists of varying experience (NCT02581254). Patients were randomized in a 1:1 ratio to the use of a thin-wire (0.30 mm) or thick-wire (0.47 mm) snare for CSP of small (≤10 mm) colorectal polyps. The primary end point was the IRR as determined by the histologic assessment of the defect margin after polypectomy. RESULTS: Over 52 months to January 2020, 1,393 patients were eligible. A total of 660 patients with polyps (57.4% male) were randomized to a thin-wire (n = 339) or thick-wire (n = 321) snare. The overall IRR of the cohort was 1.5%. There was no significant difference in the IRR between the thin- and thick-wire arms; relative risk-0.41, 95% CI (0.11-1.56), P = 0.21. No significant differences were observed in the rate of adverse events. DISCUSSION: In this multicenter randomized trial, CSP is safe and effective with very low rates of incomplete resection independent of the diameter of the snare wire used. This suggests that the optimal operator technique is more important than the snare design alone in minimizing residual adenoma after CSP.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".