Cystic Fibrosis-related Diabetes, Type 1 Diabetes, Type 2 Diabetes
Conditions
Keywords
Diabetic Retinopathy
Brief summary
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, and to determine the diagnostic accuracy of the autonomous AI system in detecting diabetic retinopathy from retinal images of youth with diabetes.
Detailed description
This study will recruit up to 500 individuals ages 8-21 with type 1 or type 2 diabetes. In this study, participants will undergo a point-of-care diabetic eye exam using autonomous AI software on a non-mydriatic fundus camera. Participants will receive the diabetic eye exam results immediately from the autonomous AI system, and if abnormal will be referred to an eye care provider for a dilated eye exam. In the AI for ChildrenS Diabetic Eye ExamS Study (ACCESS2), 398 participants will be enrolled to determine if point of care autonomous AI increases the proportion of minority and underserved youth screened for diabetic retinopathy. The autonomous AI interpretation will also be compared to consensus grading of retinal specialists to determine if there is agreement and to determine the diagnostic accuracy of the system in youth. A cohort of youth with known diabetic retinopathy (true positives) will also be enrolled as an enriched population to determine the diagnostic accuracy of autonomous AI compared to the prognostic standard interpretation of a central reading center.
Interventions
DIAGNOSTIC_TESTPoint of Care Autonomous AI diabetic retinopathy exam
Participants will undergo point-of-care diabetic retinopathy screening using autonomous artificial intelligence software to interpret retinal images taken with a non-mydriatic fundus camera and providing an immediate result.
Sponsors
Johns Hopkins University
National Eye Institute (NEI)
Juvenile Diabetes Research Foundation
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SCREENING
Masking
NONE
Masking description
All participants will undergo point-of-care diabetic retinopathy screening. Participants will know that they will undergo point-of-care diabetic retinopathy screening at the time of consenting.
Eligibility
Sex/Gender
ALL
Age
8 Years to 21 Years
Healthy volunteers
No
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 Enriched cohort: * Patients with Type 1 or Type 2 diabetes, * 8-21 years of age with known diabetic retinopathy (true positives). * No time limit on last diabetic eye exam.
Exclusion criteria
* Known diabetic eye exam in the last 12 months
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proportion screened for diabetic retinopathy | Day 1 | Equivalence in proportion screened for diabetic retinopathy of white and non-white youth with autonomous AI |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Percentage of agreement in interpretation of retinal images | Day 1 | Agreement in interpretation of retinal images between autonomous AI and consensus grading by ophthalmologists |
| Sensitivity of autonomous AI vs. prognostic standard | Day 1 | Sensitivity of autonomous AI in detecting diabetic retinopathy in youth compared to the prognostic standard. This will be analyzed in the ACCESS2 trial cohort alone, and also in the ACCESS2 trial cohort with the enriched cohort of youth with known diabetic retinopathy. |
| Specificity of autonomous AI vs. prognostic standard | Day 1 | Specificity of autonomous AI in detecting diabetic retinopathy in youth compared to the prognostic standard. This will be analyzed in the ACCESS2 trial cohort alone, and also in the ACCESS2 trial cohort with the enriched cohort of youth with known diabetic retinopathy. |
| Proportion with diabetic retinopathy | Day 1 | Proportion of participants with diabetic retinopathy, including none, mild, moderate or severe DR. |
Countries
United States
Contacts
CONTACTRisa M Wolf, MD
CONTACTAlvin Liu, MD
PRINCIPAL_INVESTIGATORRisa M Wolf, MD
Johns Hopkins University
Outcome results
None listed