Evaluation of the Clinical Effectiveness of Upper Gastrointestinal Endoscopy Reporting System

Not Applicable

Not yet recruiting

• Conditions: Artificial Intelligence; Endoscopy, Gastrointestinal
• Interventions: Diagnostic Test: AI-based reporting system

• Registration Number: NCT05851885
• Lead Sponsor: Renmin Hospital of Wuhan University

Brief Summary

The objective of this study is to assess the effectiveness of an AI-based reporting system for upper gastrointestinal endoscopy. The primary question that this study aims to address is whether the reporting system can enhance the completeness and accuracy of endoscopic reports when assisted by AI, as drafted by endoscopists. Patients will be randomly assigned to either the experimental group or the control group. In the experimental group, physicians will draft EGD reports with the assistance of the AI-based reporting system, while in the control group, physicians will use the conventional reporting system to draft EGD reports. At the same time, the AI-based reporting system will automatically generate a report of the EGD examination.

Detailed Description

Not available

Study Timeline

• Status Verified: 2023-04
• Study First Submitted: 2023-04-30
• Study First Submitted QC: 2023-04-30
• Last Update Submitted: 2023-04-30
• Study First Posted: 2023-05-10
• Last Update Posted: 2023-05-10
• Study Start: 2023-05-20
• Primary Completion: 2024-04-20
• Study Completion: 2024-05-20

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 125

Inclusion Criteria

1. Aged 18 years
2. Aim to undergo screening, surveillance, and diagnosis
3. Undergo sedated EGD
4. Able to read, understand, and sign informed consent

Exclusion Criteria

1. EGD contraindications
2. Not suitable for sedated endoscopy after anaesthesia evaluation
3. Biopsy contraindications
4. Active upper gastrointestinal bleeding or emergency oesophagogastroduodenoscopy (EGD)
5. Pregnancy
6. Upper gastrointestinal surgery or residual stomach
7. Not suitable for recruitment after investigator evaluation because of other high-risk conditions

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Experimental group	AI-based reporting system	Physicians draft EGD reports with the assistance of the AI-based reporting system.

Primary Outcome Measures

Name	Time	Method
Completeness of reporting lesions	one month	Calculation method = number of report lesions / total number of lesions x 100%

Secondary Outcome Measures

Name	Time	Method
Accuracy of report drafting on lesion features	one month	Calculation method = number of accurately drafted features of lesions / total number of drafted features x 100%
Completeness of reporting lesions of AI system	one month	Calculation method = number of report lesions / total number of lesions x 100%
Physician satisfaction survey	one month	Use 5-point Likert scale to assess physician satisfaction, acceptance, and trust in using the intelligent graphic report system to draft endoscopic reports.
Completeness of report drafting on lesion features	one month	Calculation method = number of drafted features of lesions / total number of features required to be drafted x 100%
Reporting time	one month	The time that endoscopists draft reports
Accuracy of report drafting on lesion features of AI system	one month	Calculation method = number of accurately drafted features of lesions / total number of drafted features x 100%