ACCESS 2: AI for pediatriC diabetiC Eye examS Study 2

NCT05463289 | Recruiting DMC FDA Device

• 2 other identifiers: IRB001806921R01EY033233-01
• Study Type: interventional
• Target: 500
• Locations: 1 country
• Sites: 1

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.

Conditions

Type 2 Diabetes; Cystic Fibrosis-related Diabetes; Type 1 Diabetes

Keywords

Diabetic Retinopathy

Outcome Measures

Primary Outcomes (1)

• Proportion screened for diabetic retinopathy

  Equivalence in proportion screened for diabetic retinopathy of white and non-white youth with autonomous AI

  Day 1

Secondary Outcomes (4)

• Percentage of agreement in interpretation of retinal images

  Day 1

• Sensitivity of autonomous AI vs. prognostic standard

  Day 1

• Specificity of autonomous AI vs. prognostic standard

  Day 1

• Proportion with diabetic retinopathy

  Day 1

Study Arms (1)

Diabetic Retinopathy Exam at the point of care

OTHER

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

Interventions

Point of Care Autonomous AI diabetic retinopathy exam DIAGNOSTIC_TEST

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.

Also known as: IDx-DR

Diabetic Retinopathy Exam at the point of care

Eligibility Criteria

• Age: 8 Years - 21 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64)

You may qualify if:

• 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,
• years of age with known diabetic retinopathy (true positives).
• No time limit on last diabetic eye exam.

You may not qualify if:

• Known diabetic eye exam in the last 12 months

Sponsors & Collaborators

• Juvenile Diabetes Research Foundation: collaborator
• Johns Hopkins University: lead
• National Eye Institute (NEI): collaborator

Study Sites (1)

Johns Hopkins Pediatric Diabetes Center

Baltimore, Maryland, 21287, United States

RECRUITING

Related Publications (5)

• 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.

  PMID: 32126819 BACKGROUND

• 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.

  PMID: 34042939 BACKGROUND

• 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.

  PMID: 32880616 BACKGROUND

• 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.

  PMID: 33479160 BACKGROUND

• 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.

  PMID: 32410329 BACKGROUND

MeSH Terms

Conditions

Diabetes Mellitus, Type 1; Diabetes Mellitus, Type 2; Diabetic Retinopathy

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Autoimmune Diseases; Immune System Diseases; Retinal Diseases; Eye Diseases; Diabetic Angiopathies; Vascular Diseases; Cardiovascular Diseases; Diabetes Complications

Study Officials

• Risa M Wolf, MD

  Johns Hopkins University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Risa M Wolf, MD

CONTACT

4109556463; RWolf@jhu.edu

Alvin Liu, MD

CONTACT

tliu25@jhmi.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Masking Details: 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.
• Purpose: SCREENING
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 14, 2022
• First Posted: July 18, 2022
• Study Start: July 11, 2022
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): June 30, 2026
• Last Updated: March 27, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)