Evaluation of the Clinical Effectiveness of Upper Gastrointestinal Endoscopy Reporting System
Study Details
Study Description
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.
Condition or Disease | Intervention/Treatment | Phase |
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N/A |
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Experimental: Experimental group Physicians draft EGD reports with the assistance of the AI-based reporting system. |
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.
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No Intervention: 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. |
Outcome Measures
Primary Outcome Measures
- Completeness of reporting lesions [one month]
Calculation method = number of report lesions / total number of lesions x 100%
Secondary Outcome Measures
- 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%
- 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%
- Reporting time [one month]
The time that endoscopists draft reports
- Completeness of reporting lesions of AI system [one month]
Calculation method = number of report lesions / total number of lesions x 100%
- 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%
- 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.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Aged 18 years
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Aim to undergo screening, surveillance, and diagnosis
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Undergo sedated EGD
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Able to read, understand, and sign informed consent
Exclusion Criteria:
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EGD contraindications
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Not suitable for sedated endoscopy after anaesthesia evaluation
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Biopsy contraindications
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Active upper gastrointestinal bleeding or emergency oesophagogastroduodenoscopy (EGD)
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Pregnancy
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Upper gastrointestinal surgery or residual stomach
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Not suitable for recruitment after investigator evaluation because of other high-risk conditions
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Renmin Hospital of Wuhan University
Investigators
- Principal Investigator: Honggang Yu, MD, Wuhan University Renmin Hospital
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- EA-23-007