Prospective Evalulation of Artificial Intelligence-assisted Monitoring of Effective Withdrawal Time Versus Standard Withdrawal Time on Adenoma Detected Per Colonoscopy
NCT ID: NCT06345105
Last Updated: 2025-06-11
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
198 participants
OBSERVATIONAL
2023-11-01
2025-01-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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AI group
AI monitoring of effective withdrawal time
Endoscreener QC
Artificial intelligence monitoring of effective withdrawal time
Interventions
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Endoscreener QC
Artificial intelligence monitoring of effective withdrawal time
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* history of colorectal cancer
* previous bowel resection (apart from appendectomy)
* Peutz-Jeghers syndrome, familial adenomatous polyposis or other polyposis syndromes
* bleeding tendency or severe comorbid illnesses for which polypectomy is considered unsafe.
* Cecum could not be intubated for various reasons
* Poor bowel preparation with Boston Bowel Preparation Scale (BBPS) \< 6
40 Years
ALL
Yes
Sponsors
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The University of Hong Kong
OTHER
Responsible Party
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Principal Investigators
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Thomas Ka-Luen Lui
Role: PRINCIPAL_INVESTIGATOR
The University of Hong Kong
Locations
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Queen Mary Hospital, the University of Hong Kong
Hong Kong, , Hong Kong
Countries
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Other Identifiers
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AIeffectiveV4
Identifier Type: -
Identifier Source: org_study_id
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