Trial reportThe lancet. Gastroenterology & hepatology2020
Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a randomised controlled study.
Trial report in The lancet. Gastroenterology & hepatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to 3 registered trials, which are not on this map. Cited by 172 papers, 16 of them syntheses 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.
Real-World Validation of an Artificial Intelligence Characterization Support (CADx) System for Prediction of Polyp Histology in Colonoscopy: A Prospective Multicentre Study
Real-time Computer-aided Polyp/Adenoma Detection During Screening Colonoscopy: a Single-center Crossover Trial
Efficacy of Computer Aided Detection (CADe) System in Detecting Gastric Neoplasia - a Prospective Tandem Study
Who cites it
172 citing papers in PubMed, 16 syntheses or guidelines pooled it.
- Comparative Efficacy of Different AI Systems for Polyp Detection by Size During Colonoscopy: Systematic Review and Network Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Effectiveness of artificial intelligence-assisted colonoscopy for colorectal lesion detection: a systematic review and meta-analysis of randomized controlled trials.BMC medical imaging · 2026Pooled it
- The role of artificial intelligence in adenoma detection during colonoscopy: a systematic review and meta-analysis of randomized controlled trials-Artificial intelligence and adenoma detection.Techniques in coloproctology · 2026Pooled it
- Comparative Performance of Artificial Intelligence-Based Computer-Aided Detection Systems for Colorectal Polyps: A Systematic Review and Network Meta-Analysis.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Pooled it
- Artificial intelligence-based computer-aided detection systems for adenomas during colonoscopy: a systematic review and Bayesian network meta-analysis.Frontiers in artificial intelligence · 2026Pooled it
- Effectiveness of artificial intelligence-assisted colonoscopy in detecting and diagnosing colorectal tumors: a systematic review and network meta-analysis.International journal of colorectal disease · 2025Pooled it
- Effect of AI-assisted diagnosis on adenomas of different sizes: a meta-analysis with evidence from RCTs and trial sequential analysis.BMC gastroenterology · 2025Pooled it
- The Impact of Artificial Intelligence in Improving Polyp and Adenoma Detection Rate During Colonoscopy: Systematic-Review and Meta-Analysis.Asian Pacific journal of cancer prevention : APJCP · 2023Pooled it
- Randomized Clinical Trials of Machine Learning Interventions in Health Care: A Systematic Review.JAMA network open · 2022Pooled it
- Randomized Controlled Trials of Artificial Intelligence in Clinical Practice: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Effect of artificial intelligence-aided colonoscopy for adenoma and polyp detection: a meta-analysis of randomized clinical trials.International journal of colorectal disease · 2022Pooled it
- Artificial intelligence (AI) real-time detection vs. routine colonoscopy for colorectal neoplasia: a meta-analysis and trial sequential analysis.International journal of colorectal disease · 2021Pooled it
- Diagnostic Accuracy of Artificial Intelligence and Computer-Aided Diagnosis for the Detection and Characterization of Colorectal Polyps: Systematic Review and Meta-analysis.Journal of medical Internet research · 2021Pooled it
- Artificial Intelligence-Aid Colonoscopy Vs. Conventional Colonoscopy for Polyp and Adenoma Detection: A Systematic Review of 7 Discordant Meta-Analyses.Frontiers in medicine · 2021Pooled it
- Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.Nature medicine · 2020Guideline
- Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.Nature medicine · 2020Guideline
- Technical and clinical feasibility of single-use gastroscopy with real-time AI-based quality monitoring and single-use colonoscopy: a prospective two-center study.Biomedical engineering online · 2026Trial
- A prospective study evaluating an artificial intelligence-based system for withdrawal time measurement.Endoscopy · 2026Trial
- Colorectal mucosal exposure area assessment using artificial intelligence: a multicenter prospective observational study.Endoscopy · 2026Trial
- Automatic Quality Control System and Adenoma Detection Rates During Routine Colonoscopy: A Randomized Clinical Trial.JAMA network open · 2025Trial
112 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Commented on by
- Erratum issued
Authors and funding
26 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColonoscopy performance varies among endoscopists, impairing the discovery of colorectal cancers and precursor lesions. We aimed to construct a real-time quality improvement system (ENDOANGEL) to monitor real-time withdrawal speed and colonoscopy withdrawal time and to remind endoscopists of blind spots caused by endoscope slipping. We also aimed to evaluate the effectiveness of this system for improving adenoma yield of everyday colonoscopy.
methodsThe ENDOANGEL system was developed using deep neural networks and perceptual hash algorithms. We recruited consecutive patients aged 18-75 years from Renmin Hospital of Wuhan University in China who provided written informed consent. We randomly assigned patients (1:1) using computer-generated random numbers and block randomisation (block size of four) to either colonoscopy with the ENDOANGEL system or unassisted colonoscopy (control). Endoscopists were not masked to the random assignment but analysts and patients were unaware of random assignments. The primary endpoint was the adenoma detection rate (ADR), which is the proportion of patients having one or more adenomas detected at colonoscopy. The primary analysis was done per protocol (ie, in all patients having colonoscopy done in accordance with the assigned intervention) and by intention to treat (ie, in all randomised patients). This trial is registered with http://www.chictr.org.cn, ChiCTR1900021984.
findingsBetween June 18, 2019, and Sept 6, 2019, 704 patients were randomly allocated colonoscopy with the ENDOANGEL system (n=355) or unassisted (control) colonoscopy (n=349). In the intention-to-treat population, ADR was significantly greater in the ENDOANGEL group than in the control group, with 58 (16%) of 355 patients allocated ENDOANGEL-assisted colonoscopy having one or more adenomas detected, compared with 27 (8%) of 349 allocated control colonoscopy (odds ratio [OR] 2·30, 95% CI 1·40-3·77; p=0·0010). In the per-protocol analysis, findings were similar, with 54 (17%) of 324 patients assigned ENDOANGEL-assisted colonoscopy and 26 (8%) of 318 patients assigned control colonoscopy having one or more adenomas detected (OR 2·18, 95% CI 1·31-3·62; p=0·0026). No adverse events were reported.
interpretationThe ENDOANGEL system significantly improved the adenoma yield during colonoscopy and seems to be effective and safe for use during routine colonoscopy.
fundingHubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Hubei Province Major Science and Technology Innovation Project, and the National Natural Science Foundation of China.
Indexed as
Identifiers
31981518What 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.