Evaluation of the Clinical Effectiveness of Upper Gastrointestinal Endoscopy Reporting System

NCT ID: NCT05851885

Last Updated: 2023-05-10

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

125 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-05-20

Study Completion Date

2024-05-20

Brief Summary

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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

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Conditions

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Endoscopy, Gastrointestinal Artificial Intelligence

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

SINGLE

Participants

Study Groups

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Experimental group

Physicians draft EGD reports with the assistance of the AI-based reporting system.

Group Type EXPERIMENTAL

AI-based reporting system

Intervention Type DIAGNOSTIC_TEST

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

Control group

Physicians 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.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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AI-based reporting system

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

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Renmin Hospital of Wuhan University

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Honggang Yu, MD

Role: PRINCIPAL_INVESTIGATOR

Wuhan University Renmin Hospital

Central Contacts

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Honggang Yu, MD

Role: CONTACT

+8613871281899

Other Identifiers

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EA-23-007

Identifier Type: -

Identifier Source: org_study_id

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