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Not yet recruiting NCT06763952

Leveraging Artificial Intelligence to Prevent Vision Loss From Diabetes

No phase Interventional Diabetic Retinopathy Diabetes Mellitus

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: AI.
Who it may be relevant to
Registry conditions: Diabetic Retinopathy, Diabetes Mellitus. Basic parameters: from 22 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
United States
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Multicenter National Parallel Cluster Randomized Controlled Superiority Trial Comparing an Artificial Intelligence-Based Screening Strategy to Usual Care for Improving Eye-Care Follow-Up Among Patients With Diabetes (AI-BRIDGE Trial)

Overview

This study aims to investigate whether a novel artificial intelligence based screening strategy (AI-Based point of caRe, Incorporating Diagnosis, SchedulinG, and Education or AI-BRIDGE), which allows primary care providers to screen patients for vision-threatening diabetic eye disease in the primary care clinic, improves screening and follow-up care rates across race/ethnicity groups and reduces racial/ethnic disparities in screening.

Detailed description

This is a multicenter clinical trial and University of Wisconsin is the coordinating center of the study.

A stepped-wedge cluster randomized clinical trial will be conducted. The investigators will evaluate the effectiveness of two standard diabetic retinopathy screening strategies at primary care clinics; (1) AI-based eye screening program called AI-BRIDGE, eye photos of the patients will be obtained in the primary care clinic by trained clinic staff. Images will be reviewed using autonomous artificial-intelligence (AI) algorithm (Digital Diagnostics). Patients with referrable diabetic retinopathy are detected within minutes and patients with referrable disease will be assisted with scheduling an in-person follow-up eye care visit (2) usual care screening, primary care providers refer patients with diabetes to an eye care provider for an in-person dilated eye exam.

After adapting AI-BRIDGE protocols to clinics and training of clinic personnel, stepped wedge randomized clinical trial begins with sites transitioning from usual-care to AI-BRIDGE in 4 steps.

Primary Objective:

* Compare the proportion of patients, by race and ethnicity, who follow-up with recommended eye care in the AI-BRIDGE and usual-care arms within 6 months of the recommendation.

Secondary Objectives:

* Compare the difference in proportion of White vs Hispanic and White vs Black patients who get screening in the AI-BRIDGE and usual-care arms within 6 months of the recommendation. * Compare proportion of patients, by race and ethnicity, who receive eye screening in the AI-BRIDGE and usual-care arms within 6 months of the recommendation.

Interventions

  • Other AI
    AI-based eye screening program

Primary outcome measures

  • Proportion of Participants Who Follow Up With Recommended Eye Care [Time frame: up to 6 months]
Secondary outcome measures (2)
  • Difference in Proportion of White vs Hispanic and White vs Black Participants Who Get Eye Screening [Time frame: up to 6 months]
  • Proportion of Participants By Race and Ethnicity Who Get Eye Screening [Time frame: up to 6 months]

Eligibility criteria

Inclusion criteria

  • Diagnosed with type 1 or 2 diabetes
  • No known diabetic eye disease
  • Medicaid as their primary insurance
  • Not had an eye exam in the prior year

Exclusion criteria

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Randomized
Model
Sequential
Masking
Open label
Primary purpose
Health services research

Study locations

United States · 1 center
  • UW School of Medicine and Public Health — Madison

Identifiers

NCT: NCT06763952 · 2026-0446 · Protocol Version 2/20/26 · A536000 · 2024-0030 · 1R01EY035994

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗