ACCESS 2: AI for pediatriC diabetiC Eye examS Study 2

Study Overview
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Brief Summary
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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.

Detailed Description
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This study will recruit 500 individuals ages 8-21 with type 1 and type 2 diabetes. 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. The autonomous AI interpretation will also be compared to consensus grading of retinal specialists to determine if there is agreement.

Official Title
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Implementing Digital Retinal Exams Into Comprehensive Pediatric Diabetes Care

Conditions
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Cystic Fibrosis-related Diabetes, Type 1 Diabetes, Type 2 Diabetes

Intervention / Treatment
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* Diagnostic Test: Point of Care Autonomous AI diabetic retinopathy exam


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 8 Years
Maximum Age: 21 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Screening
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Other: Diabetic Retinopathy Exam at the point of care<br>Participants will undergo a point of care diabetic retinopathy eye exam using autonomous AI. Those that test positive will be referred to Eye Care Provider for dilated eye exam. | Diagnostic Test: Point of Care Autonomous AI diabetic retinopathy exam<br>* 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.<br>* Other names: IDx-DR;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Proportion screened for diabetic retinopathy | Equivalence in proportion screened for diabetic retinopathy of white and non-white youth with autonomous AI | 2 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Percentage of agreement in interpretation of retinal images | Agreement in interpretation of retinal images between autonomous AI and consensus grading by ophthalmologists | 2 years | 
| Diagnostic Accuracy | Sensitivity, specificity and diagnosability of autonomous AI in detecting diabetic retinopathy in youth compared to the prognostic standard | Day 1 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Diabetic Retinopathy