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Colonoscopy TRaining With or Without Artificial INtelligence Among Endoscopy Residents

NCT07420309 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 10

Last updated 2026-02-19

No results posted yet for this study

Summary

Type of study: Randomized controlled study

Investigated Procedure: Artificial Intelligence Software for Polyp Detection in Colonoscopy training

Trial participants: Endoscopy trainees during their training with at least one year of training ahead and no previous structured exposure to CADe

Objectives:

Primary: Adenoma Miss Rate (AMR) in the end of the first year of training for each group and after the crossover.

Secondary: Further endoscopists-related parameters will be recorded and compared between the two arms: PDR, ADR, aADR, PMR, withdrawal time, CIR, AEs

The investigators will be asked, when possible, to follow-up the patients until they have their next colonoscopy or a diagnosis of CRC to assess for interval cancer.

Conditions

  • Colonoscopy Training

Interventions

DIAGNOSTIC_TEST

Artificial Intelligence in colonoscopy

Training in colonoscopy with or without CADe

DIAGNOSTIC_TEST

Conventional colonoscopy training

The trainees will be trained with the conventional colonoscopy for the study period

Sponsors & Collaborators

  • University of Thessaly

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Model
CROSSOVER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-02-01
Primary Completion
2027-03-01
Completion
2027-07-01

Countries

  • Greece

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07420309 on ClinicalTrials.gov