Trial reportUnited European gastroenterology journal2020
Colon capsule endoscopy versus CT colonography after incomplete colonoscopy. Application of artificial intelligence algorithms to identify complete colonic investigations.
Trial report in United European gastroenterology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02826993 (Can Colon Capsule Endoscopy Substitute CT Colonography in the Large Bowel Examination of Persons Whose Colonoscopy Was Incomplete?), which is not on this map. Cited by 25 papers, 3 of them syntheses that pooled it.
What it found
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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.
Can Colon Capsule Endoscopy Substitute CT Colonography in the Large Bowel Examination of Persons Whose Colonoscopy Was Incomplete?
Who cites it
25 citing papers in PubMed, 3 syntheses or guidelines pooled it, 38 citations in OpenAlex.
- PillCam COLON 2 for investigation of the colon through direct visualisation: systematic review and economic evaluation.Health technology assessment (Winchester, England) · 2026Pooled it
- Follow-up endoscopy rates as an indicator of effectiveness in colon capsule endoscopy: a systematic review and meta-analysis.BMJ open gastroenterology · 2025Pooled it
- Artificial intelligence in endoscopy and colonoscopy: a comprehensive bibliometric analysis of global research trends.Frontiers in medicine · 2025Pooled it
- Artificial Intelligence in Gastrointestinal Wireless Capsule Endoscopy: A Systematic Literature Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Expected Values of Artificial Intelligence in Colon Capsule Endoscopy: Artificial Intelligence in Capsule Endoscopy Consortium Position Statement.Endoscopy international open · 2026Article
- The Role of Video Capsule Endoscopy in Hereditary Polyposis Syndromes: A Narrative Review.Diagnostics (Basel, Switzerland) · 2025Review
- Artificial intelligence in gastroenterology: Ethical and diagnostic challenges in clinical practice.World journal of gastroenterology · 2025Article
- Transparency and Representation in Clinical Research Utilizing Artificial Intelligence in Oncology: A Scoping Review.Cancer medicine · 2025Article
- Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.Scientific reports · 2025Article
- A Narrative Review on the Role of Artificial Intelligence (AI) in Colorectal Cancer Management.Cureus · 2025Review
- Non-neoplastic findings in colon capsule endoscopy: Additional yield.Endoscopy international open · 2024Article
- A systematic review of capsule aspiration in capsule endoscopy.Annals of translational medicine · 2024Review
- Third Eye? The Assistance of Artificial Intelligence (AI) in the Endoscopy of Gastrointestinal Neoplasms.Journal of clinical medicine · 2023Review
- Article
- Change in onset age of first primary colorectal cancer in the USA.International journal of colorectal disease · 2023Article
- Clinical utility of colon capsule endoscopy: a moving target?Therapeutic advances in gastroenterology · 2023Review
- Colon Capsule Endoscopy in the Diagnosis of Colon Polyps: Who Needs a Colonoscopy?Diagnostics (Basel, Switzerland) · 2022Review
- Modern Machine Learning Practices in Colorectal Surgery: A Scoping Review.Journal of clinical medicine · 2022Article
- The Effect of Prucalopride on the Completion Rate and Polyp Detection Rate of Colon Capsule Endoscopies.Clinical epidemiology · 2022Article
- The role of AI technology in prediction, diagnosis and treatment of colorectal cancer.Artificial intelligence review · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGuidelines suggest computed tomography colonography (CTC) following incomplete optical colonoscopy (OC). Colon capsule endoscopies (CCE) have been suggested as an alternative, although completion rates have been unsatisfactory. Introduction of artificial intelligence (AI)-based localization algorithms of the camera capsules may enable identification of incomplete CCE investigations overlapping with incomplete OCs.
objectiveThe study aims to investigate relative sensitivity of CCE compared with CTC following incomplete OC, investigate the completion rate when combining results from the incomplete OC and CCE, and develop a forward-tracking algorithm ensuring a safe completeness of combined investigations.
methodsIn this prospective paired study, patients with indication for CTC following incomplete OC were included for CCE and CTC. Location of CCE abortion and OC abortion were registered to identify complete combined investigations. AI-based algorithm for localization of capsules were developed reconstructing the passage of the colon.
resultsIn 237 individuals with CTC indication; 105 were included, of which 97 underwent both a CCE and CTC. CCE was complete in 66 (68%). Including CCEs which reached most oral point of incomplete OC, 73 (75%) had complete colonic investigations; 78 (80%) had conclusive investigations. Relative sensitivity of CCE compared with CTC was 2.67 (95% confidence interval (CI) 1.76;4.04) for polyps >5 mm and 1.91 (95% CI 1.18;3.09) for polyps >9 mm. An AI-based algorithm was developed.
conclusionSensitivity of CCE following incomplete OC was superior to CTC. Introducing and improving algorithm-based localization of capsule abortion may increase identification of overall complete investigation rates following incomplete OC.ClinicalTrials.gov identifier: NCT02826993.
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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.