Routine Prophylactic Endoscopic Clipping Is Not Efficacious in the Prevention of Delayed Post-Polypectomy Bleeding: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND AND AIMS: Colorectal cancer (CRC) can be prevented through colonoscopic polypectomy, but this exposes patients to risks, including delayed post-polypectomy bleeding (DPPB). Endoscopists increasingly use clips prophylactically with the aim of preventing DPPB. However, clips are costly, and data to support their efficacy in this context are inconsistent. We performed a systematic review and meta-analysis of randomized controlled trials to assess the efficacy of prophylactic clipping for preventing DPPB. METHODS: We searched electronic databases and other relevant sources for randomized controlled trials assessing the efficacy of prophylactic clipping versus no clipping for the prevention of DPPB. Pooled relative risks were determined using a fixed-effects model. Subgroup analyses were also performed. RESULTS: A total of 2305 citations were initially screened. Seven randomized controlled trials satisfied all criteria for inclusion. The quality of included studies was generally low to moderate. A total of 2851 patients underwent 5405 polypectomies. Delayed post-polypectomy bleeding occurred at an overall pooled rate of 2.5%. No overall benefit of clipping for preventing DPPB was observed, with a pooled relative risk of 0.86 (95% confidence interval [CI], 0.55 to 1.36). No significant patient or polyp factors predicting DPPB were found through subgroup analyses. No publication bias was identified. CONCLUSIONS: Randomized trials to date do not demonstrate a protective effect of prophylactic clipping for the prevention of DPPB, and therefore, the practice of routine prophylactic clipping appears unjustified. Additional high quality randomized trials are required to identify higher-risk groups that may benefit from prophylactic clipping.
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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 | 0.025 | 0.068 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".