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, and to determine the diagnostic accuracy of the autonomous AI system in detecting diabetic retinopathy from retinal images of youth with diabetes.
⁃ 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.