Type 2 Diabetes Clinical Trial
— ACCESS2Official title:
Implementing Digital Retinal Exams Into Comprehensive Pediatric Diabetes Care
The purpose of this study is to determine if use of a nonmydriatic fundus camera using autonomous artificial intelligence software at the point of care increases the proportion of underserved youth with diabetes screened for diabetic retinopathy.
| Status | Recruiting |
| Enrollment | 500 |
| Est. completion date | May 15, 2024 |
| Est. primary completion date | May 15, 2024 |
| Accepts healthy volunteers | No |
| Gender | All |
| Age group | 8 Years to 21 Years |
| Eligibility | Inclusion Criteria: Meets American Diabetes Association (ADA) criteria for diabetic retinopathy screening: - Diagnosis of Type 1 diabetes for =3 years, and age 11 or in puberty - Diagnosis of Type 2 diabetes Exclusion Criteria: - Known diabetic eye exam in the last 12 months |
| Country | Name | City | State |
|---|---|---|---|
| United States | Johns Hopkins Pediatric Diabetes Center | Baltimore | Maryland |
| Lead Sponsor | Collaborator |
|---|---|
| Johns Hopkins University | Juvenile Diabetes Research Foundation, National Eye Institute (NEI) |
United States,
Channa R, Wolf R, Abramoff MD. Autonomous Artificial Intelligence in Diabetic Retinopathy: From Algorithm to Clinical Application. J Diabetes Sci Technol. 2021 May;15(3):695-698. doi: 10.1177/1932296820909900. Epub 2020 Mar 4. — View Citation
Porter M, Channa R, Wagner J, Prichett L, Liu TYA, Wolf RM. Prevalence of diabetic retinopathy in children and adolescents at an urban tertiary eye care center. Pediatr Diabetes. 2020 Aug;21(5):856-862. doi: 10.1111/pedi.13037. Epub 2020 May 31. — View Citation
Thomas CG, Channa R, Prichett L, Liu TYA, Abramoff MD, Wolf RM. Racial/Ethnic Disparities and Barriers to Diabetic Retinopathy Screening in Youths. JAMA Ophthalmol. 2021 Jul 1;139(7):791-795. doi: 10.1001/jamaophthalmol.2021.1551. — View Citation
Wolf RM, Channa R, Abramoff MD, Lehmann HP. Cost-effectiveness of Autonomous Point-of-Care Diabetic Retinopathy Screening for Pediatric Patients With Diabetes. JAMA Ophthalmol. 2020 Oct 1;138(10):1063-1069. doi: 10.1001/jamaophthalmol.2020.3190. — View Citation
Wolf RM, Liu TYA, Thomas C, Prichett L, Zimmer-Galler I, Smith K, Abramoff MD, Channa R. The SEE Study: Safety, Efficacy, and Equity of Implementing Autonomous Artificial Intelligence for Diagnosing Diabetic Retinopathy in Youth. Diabetes Care. 2021 Mar;44(3):781-787. doi: 10.2337/dc20-1671. Epub 2021 Jan 21. — View Citation
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Proportion screened for diabetic retinopathy | Equivalence in proportion screened for diabetic retinopathy of white and non-white youth with autonomous AI | 2 years | |
| Secondary | Percentage of agreement in interpretation of retinal images | Agreement in interpretation of retinal images between autonomous AI and consensus grading by ophthalmologists | 2 years | |
| Secondary | Diagnostic Accuracy | Sensitivity, specificity and diagnosability of autonomous AI in detecting diabetic retinopathy in youth compared to the prognostic standard | Day 1 |
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