Upper Gastrointestinal Endoscopy Reporting System in Improving Report Quality

A Prospective, Single-arm, Single-center Observational Study to Evaluate the Clinical Effectiveness of an Intelligent Reporting System for the Upper Gastrointestinal Endoscopy

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05851716

Enrollment

100

Registered

2023-05-10

Start date

2023-08-21

Completion date

2024-05-20

Last updated

2023-09-05

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

Conditions

Artificial Intelligence, Endoscopy, Gastrointestinal

Brief summary

The goal of this observational study is to evaluate the effectiveness of an AI-based reporting system for upper gastrointestinal endoscopy. The main question it aims to answer is: Whether the AI-based reporting system can improve the completeness of the reports, which are drafted by endoscopists with the AI assistance. Participants will undergo upper gastrointestinal endoscopy examination as routine. The junior endoscopists will draft the report with the assiatance of the AI system. And the senior and expert endoscopists will draft the report using the traditional reporting system without AI assistance.

Interventions

None listed

Study design

Observational model

OTHER

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

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

Design outcomes

Primary

Measure	Time frame	Description
Completeness of reporting lesions	one month	Calculation method = number of report lesions / total number of lesions x 100%

Secondary

Measure	Time frame	Description
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%

Countries

China

Contacts

Primary ContactHonggang Yu, MD

yuhonggang1968@163.com+8613871281899

Outcome results