Recurrence rates after endoscopic resection of large colorectal polyps: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: traditional hot snare polypectomy and standard EMR remains unclear. AIM: To analyze LRR of large colonic polyps in a systematic review and meta-analysis. METHODS: MEDLINE, EMBASE, EBM Reviews, and CINAHL were searched for prospective studies reporting LRR or incomplete resection rate (IRR) after colonic polypectomy of polyps ≥ 10 mm, published between January 2011 and July 2021. Primary outcome was LRR for polyps ≥ 10 mm. RESULTS: standard EMR without (15.2%; 95%CI, 12.5%-18.0%; 4 studies, 650 polyps) or with unsystematic margin ablation (16.5%; 95%CI, 15.2%-17.8%; 6 studies, 3031 polyps). CONCLUSION: LRR is significantly lower after ESD or EMR with routine margin ablation; thus, these techniques should be considered standard for endoscopic removal of large colorectal polyps. Other techniques, such as CSP, cold EMR, and underwater EMR require further evaluation in prospective studies before their routine implementation in clinical practice can be recommended.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.025 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".