CDSS-assisted UGI Endoscopy vs. Routine Screening Endoscopy

NCT ID: NCT05452473

Last Updated: 2022-07-13

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

1200 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-07-06

Study Completion Date

2022-12-06

Brief Summary

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This study aimed to find the CDSS-assisted upper GI endoscopy has clinical benefit compared to conventional routine screening upper GI endoscopy. Investigators will conduct a pilot randomized controlled study. Consecutive patients will be allocated either to CDSS-assisted upper GI endoscopy or conventional routine screening upper GI endoscopy. The lesion detection rate will be compared between both groups.

Detailed Description

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Artificial intelligence has been adopted in the field of gastrointestinal endoscopy. Investigators previously established deep-learning models to predict the histology and invasion depth of gastric lesions using endoscopic stillcut images. However, clinical benefit of this model has not been evaluated. This study aimed to find the CDSS-assisted upper GI endoscopy has clinical benefit compared to conventional routine screening upper GI endoscopy. Investigators will conduct a pilot randomized controlled study. Consecutive patients who visited Chuncheon Sacred Heart hospital will be allocated either to CDSS-assisted upper GI endoscopy or conventional routine screening upper GI endoscopy. The lesion detection rate will be compared between both groups. Expert endoscopists will conduct this randomized study.

Conditions

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Healthy Individual

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

OTHER

Blinding Strategy

NONE

Study Groups

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CDSS-assisted screening endoscopy

Participants will be tested for CDSS-assisted screening upper gastrointestinal endoscopy

Group Type EXPERIMENTAL

CDSS-assisted upper GI endoscopy

Intervention Type OTHER

Expert endoscopists perform screening upper gastrointestinal endoscopy while looking at the monitor (CDSS system: automatic detection or lesion classification function) and listening to the sound of the monitor next to the original endoscopy monitor system.

Conventional routine screening endoscopy

Participants will be tested for Conventional routine screening upper gastrointestinal endoscopy

Group Type PLACEBO_COMPARATOR

no intervention

Intervention Type OTHER

Expert endoscopists perform routine screening upper gastrointestinal endoscopy without CDSS's help.

Interventions

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CDSS-assisted upper GI endoscopy

Expert endoscopists perform screening upper gastrointestinal endoscopy while looking at the monitor (CDSS system: automatic detection or lesion classification function) and listening to the sound of the monitor next to the original endoscopy monitor system.

Intervention Type OTHER

no intervention

Expert endoscopists perform routine screening upper gastrointestinal endoscopy without CDSS's help.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Participants who visited for routine screening upper gastrointestinal endoscopy

Exclusion Criteria

* Participants who refuse to participate in this study
* Participants who showed paradoxical reaction prohibiting routine examination
Minimum Eligible Age

20 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Chuncheon Sacred Heart Hospital

OTHER

Sponsor Role lead

Responsible Party

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Chang Seok Bang

PI

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Chang Seok Bang, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Hallym University

Locations

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Chuncheon Sacred Heart hospital

Chuncheon, Gangwon-do, South Korea

Site Status RECRUITING

Countries

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South Korea

Central Contacts

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Chang Seok Bang, MD., PhD.

Role: CONTACT

+82332405000

Facility Contacts

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Chang Seok Bang, MD, PHD

Role: primary

+82332405000

Cho Won Kim, MS

Role: backup

+82332405000

References

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Gong EJ, Bang CS, Lee JJ, Baik GH, Lim H, Jeong JH, Choi SW, Cho J, Kim DY, Lee KB, Shin SI, Sigmund D, Moon BI, Park SC, Lee SH, Bang KB, Son DS. Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy: development and validation study. Endoscopy. 2023 Aug;55(8):701-708. doi: 10.1055/a-2031-0691. Epub 2023 Feb 8.

Reference Type DERIVED
PMID: 36754065 (View on PubMed)

Other Identifiers

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AI RCT1

Identifier Type: -

Identifier Source: org_study_id

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