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Efficacy of an AI System in Training Endoscopists to Assess Gastric Intestinal Metaplasia Via the EGGIM Score

Efficacy of an AI System in Training Endoscopists to Assess Gastric Intestinal Metaplasia Via the EGGIM Score: A Randomized Controlled Trial

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07208864
Enrollment
8
Registered
2025-10-06
Start date
2025-11-30
Completion date
2026-12-31
Last updated
2026-09-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gastric Intestinal Metaplasia

Brief summary

This prospective randomized controlled trial with a crossover design incorporated image-enhanced endoscopy (IEE) videos demonstrating complete standardized examinations of five standard gastric areas (antrum greater curvature, antrum lesser curvature, incisura, corpus lesser curvature, and corpus greater curvature). Endoscopists were stratified by experience level and randomly assigned to either the AI-assisted scoring first group, which performed EGGIM scoring with AI assistance in the initial phase followed by conventional scoring after a washout period, or the conventional scoring first group, which completed the assessments in reverse order. The study primarily evaluated the training efficacy of the EGGIM-AI system for improving endoscopists' EGGIM scoring performance by comparing diagnostic accuracy metrics, including the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity between groups at different study phases.

Interventions

DIAGNOSTIC_TESTAI-assisted EGGIM scoring

Endoscopists will evaluate the videos with the assistance of the AI system via EGGIM score.

DIAGNOSTIC_TESTConventional EGGIM scoring

Endoscopists will evaluate the videos without the assistance of the AI system via EGGIM score.

Sponsors

Qilu Hospital of Shandong University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Outcomes Assessor)

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

Endoscopists who have performed ≥50 image-enhanced endoscopy (IEE) procedures per year and demonstrated competency in performing standardized IEE.

Exclusion criteria

Endoscopists who participated in data acquisition or were unblinded to patients' identifiable information and clinical data.

Design outcomes

Primary

MeasureTime frameDescription
Efficacy of the EGGIM-AI system for improving endoscopists' EGGIM scoring performanceThrough study completion, an average of 3 monthsDiagnostic accuracy metrics, including the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity between groups at different study phases.

Secondary

MeasureTime frameDescription
Performance of EGGIM scoring by endoscopists with varying experience levelsThrough study completion, an average of 3 monthsDifferences in AUC, sensitivity, and specificity of EGGIM scores between experienced and inexperienced endoscopists within each group at different phases.

Countries

China

Contacts

CONTACTZhen Li
qilulizhen@sdu.edu.cn86+18560086106

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Sep 9, 2026