ReviewDEN open2022
Detection of colorectal lesions during colonoscopy.
Review in DEN open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Optimizing surveillance in Lynch syndrome: lesion detection and comparative performance of different colonoscopy modalities-a systematic review and network meta-analysis.International journal of colorectal disease · 2025Pooled it
- Efficacy of image-enhanced endoscopy for colorectal polyp detection.Clinical endoscopy · 2026Review
- From microbiome profiling to precision medicine: diagnostic and therapeutic potential in gastrointestinal disorders: current evidence, challenges, and future directions.Annals of medicine and surgery (2012) · 2026Review
- The Molecular Landscape of Colorectal Laterally Spreading Tumors: From Endoscopic Subtypes to Molecular Targets.International journal of molecular sciences · 2025Review
- Negative effect of prolonged cecal intubation time on adenoma detection in female patients.JGH open : an open access journal of gastroenterology and hepatology · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Owing to its high mortality rate, the prevention of colorectal cancer is of particular importance. The resection of colorectal polyps is reported to drastically reduce colorectal cancer mortality, and examination by endoscopists who had a high adenoma detection rate was found to lower the risk of colorectal cancer, highlighting the importance of identifying lesions. Various devices, imaging techniques, and diagnostic tools aimed at reducing the rate of missed lesions have therefore been developed to improve detection. The distal attachments and devices for improving the endoscopic view angle are intended to help avoid missing blind spots such as folds and flexures in the colon, whereas the imaging techniques represented by image-enhanced endoscopy contribute to improving lesion visibility. Recent advances in artificial intelligence-supported detection systems are expected to supplement an endoscopist's eye through the instant diagnosis of the lesions displayed on the monitor. In this review, we provide an outline of each tool and assess its impact on the reduction in the incidence of missed colorectal polyps by summarizing previous clinical research and meta-analyses. Although useful, the many devices, image-enhanced endoscopy, and artificial intelligence tools exhibited various limitations. Integrating these tools can improve their shortcomings. Combining artificial intelligence-based diagnoses with wide-angle image-enhanced endoscopy may be particularly useful. Thus, we hope that such tools will be available in the near future.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.