Study Results
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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COMPLETED
NA
1162 participants
INTERVENTIONAL
2021-11-24
2022-11-21
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
CROSSOVER
DIAGNOSTIC
SINGLE
Study Groups
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CAC Group
Inspection with computer assisted colonoscopy.
EW10-EC02 (Endoscopy Support Program)
EW10-EC02 is intended to automatically detect the location of suspected polyps in colonoscopy exams. Identified polyps are highlighted to the clinician in real-time during the exam, as a video image superimposed on the endoscope monitor. EW10-EC02 is limited to the detection of suspected findings, and should not be used in lieu of full patient evaluation or relied upon to make or confirm a diagnosis.
CC Group
Inspection with conventional colonoscopy
No interventions assigned to this group
Interventions
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EW10-EC02 (Endoscopy Support Program)
EW10-EC02 is intended to automatically detect the location of suspected polyps in colonoscopy exams. Identified polyps are highlighted to the clinician in real-time during the exam, as a video image superimposed on the endoscope monitor. EW10-EC02 is limited to the detection of suspected findings, and should not be used in lieu of full patient evaluation or relied upon to make or confirm a diagnosis.
Eligibility Criteria
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Inclusion Criteria
* Patients aged 45 or older
* Patients who can provide an informed consent
Exclusion Criteria
* Patients who are pregnant or are planning pregnancy during study period
* Patients who are not able to or refuse to give informed consent
45 Years
ALL
Yes
Sponsors
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Fujifilm Medical Systems USA, Inc.
INDUSTRY
Responsible Party
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Principal Investigators
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Prateek Sharma, MD
Role: PRINCIPAL_INVESTIGATOR
Kansas City VA Medical Center
Locations
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Keck Medicine University of Southern California
Los Angeles, California, United States
Largo Medical Center (HCA)
Largo, Florida, United States
Brigham and Women's Hospital
Chestnut Hill, Massachusetts, United States
GI Associates
Flowood, Mississippi, United States
Saint Luke's Hospital of Kansas City
Kansas City, Missouri, United States
Kansas City VA Medical Center
Kansas City, Missouri, United States
New York University/Manhattan Endoscopy
New York, New York, United States
Columbia University Medical Center
New York, New York, United States
Virginia Mason Medical Center
Seattle, Washington, United States
Swedish Medical Center
Seattle, Washington, United States
Countries
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References
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Desai M, Ausk K, Brannan D, Chhabra R, Chan W, Chiorean M, Gross SA, Girotra M, Haber G, Hogan RB, Jacob B, Jonnalagadda S, Iles-Shih L, Kumar N, Law J, Lee L, Lin O, Mizrahi M, Pacheco P, Parasa S, Phan J, Reeves V, Sethi A, Snell D, Underwood J, Venu N, Visrodia K, Wong A, Winn J, Wright CH, Sharma P. Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial. Am J Gastroenterol. 2024 Jul 1;119(7):1383-1391. doi: 10.14309/ajg.0000000000002664. Epub 2024 Jan 18.
Other Identifiers
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P-21-006
Identifier Type: -
Identifier Source: org_study_id
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