Adenoma Miss rate in Artificial Intelligence-Based versus Conventional Colonoscopy, A Prospective Randomized Trial
Phase 4
Completed
- Conditions
- Accuracy of Artificial intelligence colonoscopy in Colorectal Cancer ScreeningCRC screening, AI colonoscopy, polyp miss rate
- Registration Number
- TCTR20230504002
- Lead Sponsor
- Faculty of Medicine Vajira Hospital, Navamindradhiraj University
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Completed
- Sex
- All
- Target Recruitment
- 98
Inclusion Criteria
Age 50-75
Exclusion Criteria
1.Known case Inflammatory bowel disease or Colorectal cancer
2.Contraindication for biopsy or polypectomy
3.Poor bowel preparation (Boston bowel preparation scale < 6 scores)
4.Incomplete colonoscopy
5.suspected polyposis syndromes, inflammatory bowel disease, and colorectal cancer
6.In-period colorectal screening by any modalities
Study & Design
- Study Type
- Interventional
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Adenoma Miss Rate the day colonoscopy the number adenoma detected at second colonoscopy divided by the total number of lesions detected at first and second colonoscopy
- Secondary Outcome Measures
Name Time Method Polyp Miss Rate the day colonoscopy the number polyp detected at second colonoscopy divided by the total number of lesions detected at first and second colonoscopy,Adenoma Detection Rate the day colonoscopy number of examinations with adenomas/total number of examinations,Polyp Detection Rate The day colonoscopy number of examinations with polyps/total number of examinations,Adenoma per colonoscopy the day colonoscopy All number of detected adenoma divided by number of participants,Polyp per colonoscopy the day colonoscopy All number of detected polyps divided by number of participants