Clinical trial NCT05463289: ACCESS 2: AI for pediatriC diabetiC Eye examS Study 2
Official title: Implementing Digital Retinal Exams Into Comprehensive Pediatric Diabetes Care
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Type 1 Diabetes
Type 2 Diabetes
Cystic Fibrosis-related Diabetes
Keywords: Diabetic Retinopathy
Lead sponsor: Johns Hopkins University
Sponsor class: OTHER
Collaborators: name: National Eye Institute (NEI)
name: Juvenile Diabetes Research Foundation
First posted: 2022-07-18
Enrollment: 500
Sex: ALL
Minimum age (years): 8
Maximum age (years): 21
Standard ages: CHILD
ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: SCREENING

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.

Detailed description: 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.

Eligibility criteria: 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

Primary outcomes:
measure: Proportion screened for diabetic retinopathy
timeFrame: 2 years
Secondary outcomes:
measure: Percentage of agreement in interpretation of retinal images
timeFrame: 2 years
measure: Diagnostic Accuracy
timeFrame: Day 1
Other outcomes:
Locations:
city: Baltimore
country: United States
facility: Johns Hopkins Pediatric Diabetes Center
state: Maryland
Study officials:
affiliation: Johns Hopkins University
name: Risa M Wolf, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
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.
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.
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.
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.