Evidence map›Paper›PMID 40734813›Full record

ReviewGastroenterology and hepatology from bed to bench2025

Algorithmic approach for endoscopic management of colorectal polyps: an up-to-date review.

Amir Sadeghi, Ali Yousefian Astaneh, Erfan Arabpour, Mohammad Reza Zali

Abstract readReview
In one paragraph

Review in Gastroenterology and hepatology from bed to bench, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Amir SadeghiGastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Ali Yousefian AstanehStudent Research Committee, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Erfan ArabpourGastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammad Reza ZaliGastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the growing incidence of colorectal cancer worldwide, mainly due to increased early detection in screening programs, usage of endoscopic techniques for management of colorectal lesions have been gaining progressive attention. Each year, more advanced endoscopic techniques come to practice and old ones find technical enhancements. By reviewing guidelines, randomized controlled trials, meta-analyses, and original research, we aim to establish an evidence-based approach for selecting the optimal endoscopic method based on the polyp size, morphology, and classification. We critically analyze the advantages, limitations, and potential complications associated with each technique, providing a comprehensive overview for clinicians and suggest areas which may yet need further studies to be conducted. Our comprehensive review can provide a framework that will help clinicians choose an approach most suitable for their patients. This review attempts to contribute to the optimization of endoscopic management in colorectal polyps, with eventual improvement in patient outcomes.

Indexed as

Colorectal polypsEMREndoscopic therapyESDManagementPolypectomy

Identifiers

PMID40734813
PMCPMC12301536

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.