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.
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.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SCREENING
Masking
NONE
Enrollment
500
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.
Johns Hopkins Pediatric Diabetes Center
Baltimore, Maryland, United States
RECRUITINGProportion screened for diabetic retinopathy
Equivalence in proportion screened for diabetic retinopathy of white and non-white youth with autonomous AI
Time frame: Day 1
Percentage of agreement in interpretation of retinal images
Agreement in interpretation of retinal images between autonomous AI and consensus grading by ophthalmologists
Time frame: Day 1
Sensitivity of autonomous AI vs. prognostic standard
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.
Time frame: Day 1
Specificity of autonomous AI vs. prognostic standard
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.
Time frame: Day 1
Proportion with diabetic retinopathy
Proportion of participants with diabetic retinopathy, including none, mild, moderate or severe DR.
Time frame: Day 1
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