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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT05851885
Other study ID # EA-23-007
Secondary ID
Status Not yet recruiting
Phase N/A
First received
Last updated
Start date May 20, 2023
Est. completion date May 20, 2024

Study information

Verified date April 2023
Source Renmin Hospital of Wuhan University
Contact Honggang Yu, MD
Phone +8613871281899
Email yuhonggang1968@163.com
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial 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.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 125
Est. completion date May 20, 2024
Est. primary completion date April 20, 2024
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility 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


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
AI-based reporting system
AI-based reporting system is a software platform for real-time analysis and records of abnormalities and landmarks during endoscopy.

Locations

Country Name City State
n/a

Sponsors (1)

Lead Sponsor Collaborator
Renmin Hospital of Wuhan University

Outcome

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