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Effect of AI Monitoring Blind Spots of EGD on the Inspection Time and Lesion Dection Rate

Primary Purpose

Upper Gastrointestinal Symptoms

Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Endoangle
Sponsored by
Renmin Hospital of Wuhan University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional other trial for Upper Gastrointestinal Symptoms focused on measuring Esophagogastroduodenoscopy, Artificial intelligence, Blind spot

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesAccepts Healthy Volunteers

Inclusion Criteria: patients aged 18 years or older patients able to give informed consent American Society of Anesthesiology risk class 1,2 or 3 Exclusion Criteria: patients with absolute contraindications to EGD examination patients with a history of previous gastrectomy patients with a serious underlying disease pregnant patients researchers believe that the patient is not suitable to participate in the trial

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm Type

    Experimental

    No Intervention

    Arm Label

    AI group

    Routine group

    Arm Description

    In the AI group, except for the original videos, there is additional information presented to endoscopists:(1)the virtual stomach model monitoring;(2)time;(3)scoring. Endoscopists will complete EGD examination without blind spots.

    In the Routine group, only the original videos and there is no additional information, and inspection time will be no less than 7 minutes.

    Outcomes

    Primary Outcome Measures

    Dection rate of neoplastic lesions
    Proportion of patients with neoplastic lesions among all patients undergoing esophagogastroduodenoscopy.

    Secondary Outcome Measures

    Inspection time
    It is the time from intubation to extubation of the patient without biopsy.

    Full Information

    First Posted
    April 3, 2023
    Last Updated
    June 16, 2023
    Sponsor
    Renmin Hospital of Wuhan University
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    1. Study Identification

    Unique Protocol Identification Number
    NCT05832411
    Brief Title
    Effect of AI Monitoring Blind Spots of EGD on the Inspection Time and Lesion Dection Rate
    Official Title
    Effect of Artificial Intelligence Monitoring Blind Spots of EGD on the Inspection Time and Dection Rate of Neoplastic Lesions
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    March 2023
    Overall Recruitment Status
    Not yet recruiting
    Study Start Date
    July 1, 2023 (Anticipated)
    Primary Completion Date
    May 31, 2024 (Anticipated)
    Study Completion Date
    August 31, 2024 (Anticipated)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Sponsor
    Name of the Sponsor
    Renmin Hospital of Wuhan University

    4. Oversight

    Studies a U.S. FDA-regulated Drug Product
    No
    Studies a U.S. FDA-regulated Device Product
    No

    5. Study Description

    Brief Summary
    The goal of this clinic trial is to learn about the effect of AI monitoring blind spots on the inspection time to EGD. Patients are randomly assigned to undergo an EGD with or without the assistance of AI. In the AI group, except for the original videos, there is additional information presented to endoscopists:(1)the virtual stomach model monitoring;(2)time;(3)scoring. Researchers will compare intervention group to see if it have a shorter inspection time compared with the control group.
    Detailed Description
    The goal of this clinic trial is to evaluate the effect of real-time artificial intelligence for monitoring blind spots on the inspection time of EGD. Patients are randomly assigned to undergo an EGD with or without the assistance of AI. In the AI group, except for the original videos, there is additional information presented to endoscopists:(1)the virtual stomach model monitoring;(2)time;(3)scoring. Researchers will compare intervention group to see if it have a shorter inspection time in the case of non-inferior detection rate of gastric neoplastic lesions.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Upper Gastrointestinal Symptoms
    Keywords
    Esophagogastroduodenoscopy, Artificial intelligence, Blind spot

    7. Study Design

    Primary Purpose
    Other
    Study Phase
    Not Applicable
    Interventional Study Model
    Parallel Assignment
    Masking
    Participant
    Allocation
    Randomized
    Enrollment
    1672 (Anticipated)

    8. Arms, Groups, and Interventions

    Arm Title
    AI group
    Arm Type
    Experimental
    Arm Description
    In the AI group, except for the original videos, there is additional information presented to endoscopists:(1)the virtual stomach model monitoring;(2)time;(3)scoring. Endoscopists will complete EGD examination without blind spots.
    Arm Title
    Routine group
    Arm Type
    No Intervention
    Arm Description
    In the Routine group, only the original videos and there is no additional information, and inspection time will be no less than 7 minutes.
    Intervention Type
    Device
    Intervention Name(s)
    Endoangle
    Intervention Description
    there is additional information presented to endoscopists:(1)the virtual stomach model monitoring;(2)time;(3)scoring.
    Primary Outcome Measure Information:
    Title
    Dection rate of neoplastic lesions
    Description
    Proportion of patients with neoplastic lesions among all patients undergoing esophagogastroduodenoscopy.
    Time Frame
    Through study completion, an average of 1 year
    Secondary Outcome Measure Information:
    Title
    Inspection time
    Description
    It is the time from intubation to extubation of the patient without biopsy.
    Time Frame
    20min

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Accepts Healthy Volunteers
    Accepts Healthy Volunteers
    Eligibility Criteria
    Inclusion Criteria: patients aged 18 years or older patients able to give informed consent American Society of Anesthesiology risk class 1,2 or 3 Exclusion Criteria: patients with absolute contraindications to EGD examination patients with a history of previous gastrectomy patients with a serious underlying disease pregnant patients researchers believe that the patient is not suitable to participate in the trial

    12. IPD Sharing Statement

    Plan to Share IPD
    No
    IPD Sharing Plan Description
    Sponsor approval for data sharing should be sought; Data access requests should be made via an application form detailing the specific requirements and the proposed research and publication plan
    Citations:
    PubMed Identifier
    30858305
    Citation
    Wu L, Zhang J, Zhou W, An P, Shen L, Liu J, Jiang X, Huang X, Mu G, Wan X, Lv X, Gao J, Cui N, Hu S, Chen Y, Hu X, Li J, Chen D, Gong D, He X, Ding Q, Zhu X, Li S, Wei X, Li X, Wang X, Zhou J, Zhang M, Yu HG. Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy. Gut. 2019 Dec;68(12):2161-2169. doi: 10.1136/gutjnl-2018-317366. Epub 2019 Mar 11.
    Results Reference
    background
    PubMed Identifier
    34547254
    Citation
    Wu L, Xu M, Jiang X, He X, Zhang H, Ai Y, Tong Q, Lv P, Lu B, Guo M, Huang M, Ye L, Shen L, Yu H. Real-time artificial intelligence for detecting focal lesions and diagnosing neoplasms of the stomach by white-light endoscopy (with videos). Gastrointest Endosc. 2022 Feb;95(2):269-280.e6. doi: 10.1016/j.gie.2021.09.017. Epub 2021 Sep 20.
    Results Reference
    background
    PubMed Identifier
    27548885
    Citation
    Bisschops R, Areia M, Coron E, Dobru D, Kaskas B, Kuvaev R, Pech O, Ragunath K, Weusten B, Familiari P, Domagk D, Valori R, Kaminski MF, Spada C, Bretthauer M, Bennett C, Senore C, Dinis-Ribeiro M, Rutter MD. Performance measures for upper gastrointestinal endoscopy: a European Society of Gastrointestinal Endoscopy (ESGE) Quality Improvement Initiative. Endoscopy. 2016 Sep;48(9):843-64. doi: 10.1055/s-0042-113128. Epub 2016 Aug 22. No abstract available.
    Results Reference
    background

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    Effect of AI Monitoring Blind Spots of EGD on the Inspection Time and Lesion Dection Rate

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