The Implementation of Computer-aided Detection in an Initial Endoscopy Training Improves the Quality Measures of Trainees' Future Colonoscopies
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Quality Indicators, Health Care
- Sponsor
- Jagiellonian University
- Enrollment
- 6000
- Locations
- 1
- Primary Endpoint
- Serrated polyp detection rate (SDR)
- Status
- Completed
- Last Updated
- last year
Overview
Brief Summary
Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. The study aimed to evaluate the quality indicators of endoscopists trained in an AI environment compared to those trained conventionally.
Detailed Description
Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. The study aimed to evaluate the quality indicators of endoscopists trained in an AI environment compared to those trained conventionally. A study included 6,000 adult patients who underwent a colonoscopy for various reasons. The study retrospectively evaluated the first 1,000 procedures performed by six endoscopists after completing training relying entirely on endoscopists' detection skills without AI enhancement. Three of those young endoscopists were trained with CADe, and three without additional assistance. Quality indicators were assessed in both groups. The morphology of detected polyps was evaluated to determine the influence of AI-enhanced training on laterally spreading tumors (LST) detection rate.
Investigators
Zofia Orzeszko
Principal Investigator
Jagiellonian University
Eligibility Criteria
Inclusion Criteria
- •adult participants who underwent a colonoscopy for various reasons performed by specific endoscopists that were assessed in terms of quality indicators
Exclusion Criteria
- •a history of bowel resection
- •confirmed inflammatory bowel disease
- •suspicion of polyps or cancer in other imaging tests
- •suspicion of familial adenomatous polyposis
Outcomes
Primary Outcomes
Serrated polyp detection rate (SDR)
Time Frame: During the colonoscopy examination
The percentage of colonoscopies when the serrated polyp was found
withdrawal time
Time Frame: During the colonoscopy examination
The time from the cecal intubation to the end of the examination
Cecal intubation rate (CIR)
Time Frame: During the colonoscopy examination
The percentage of colonoscopies with successful cecal intubations
Adenoma Detection Rate (ADR)
Time Frame: During the colonoscopy examination
The percentage of colonoscopies when the adenoma was found
Advanced adenoma detection rate (AADR)
Time Frame: During the colonoscopy examination
The percentage of colonoscopies when the advanced adenoma (\>10mm) was found
Adenoma per colonoscopy score (APC)
Time Frame: During the colonoscopy examination
The average number of adenomas detected in a single colonoscopy
Secondary Outcomes
- Laterally spreading tumor detection rate(During the colonoscopy examination)