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This study is intended to demonstrate the superiority of colorectal polyp detection using computer-assisted colonoscopy compared to conventional colonoscopy.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| CAC Group | Experimental | Inspection with computer assisted colonoscopy. |
|
| CC Group | No Intervention | Inspection with conventional colonoscopy |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| EW10-EC02 (Endoscopy Support Program) | Device | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Adenoma per colonoscopy (APC) | Total number of histologically confirmed adenomas and carcinomas detected in the colonoscopy divided by the total number of colonoscopies | 1 day/procedure |
| Measure | Description | Time Frame |
|---|---|---|
| Positive predictive value (PPV) | Total number of histologically confirmed adenomas and carcinomas detected during the colonoscopy, divided by the total number of excisions in the colonoscopy | 1 day/procedure |
| Adenoma detection rate (ADR) |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Prateek Sharma, MD | Kansas City VA Medical Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Keck Medicine University of Southern California | Los Angeles | California | 90033 | United States | ||
| Largo Medical Center (HCA) |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38235741 | Derived | 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. |
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Patients will be randomized 1:1, inspection with computer assisted colonoscopy: inspection with conventional colonoscopy.
|
proportion of patients with at least one histologically confirmed adenoma or carcinoma detected in the colonoscopy
| 1 day/procedure |
| Largo |
| Florida |
| 33770 |
| United States |
| Brigham and Women's Hospital | Chestnut Hill | Massachusetts | 02467 | United States |
| GI Associates | Flowood | Mississippi | 39232 | United States |
| Saint Luke's Hospital of Kansas City | Kansas City | Missouri | 64111 | United States |
| Kansas City VA Medical Center | Kansas City | Missouri | 64128 | United States |
| New York University/Manhattan Endoscopy | New York | New York | 10016 | United States |
| Columbia University Medical Center | New York | New York | 10032 | United States |
| Virginia Mason Medical Center | Seattle | Washington | 98101 | United States |
| Swedish Medical Center | Seattle | Washington | 98104 | United States |