Prevalence of diabetic retinopathy in Brazil: a systematic review with meta-analysis.
Thiago Alves Chagas, Mateus Augusto Dos Reis, Gabriel Leivas...
https://pubmed.ncbi.nlm.nih.gov/36864478Actively Recruiting
Phase Not Applicable
Age: 18Years +
All Genders
ID07236879
Effects of Artificial Intelligence-based Diabetic Retinopathy Screening on Timely Access to Treatment in Individuals With Diabetes
Led by Hospital de Clinicas de Porto Alegre · Updated on 2025-11-19
922
Participants Needed
1
Research Sites
17 weeks
Total Duration
On this page
Sponsors
H
Hospital de Clinicas de Porto Alegre
Lead Sponsor
F
Fundação de Amparo à Pesquisa do Estado de São Paulo
Collaborating Sponsor
AI-Summary
What this Trial Is About
Researchers are evaluating the effects of universal screening for diabetic retinopathy (DR) and diabetic macular edema (DME) using artificial intelligence (AI) to interpret fundus photographs taken by trained nursing assistants with a portable fundus camera in a primary care setting. This study compares AI interpretation with images interpreted remotely by ophthalmologists to understand how AI might impact timely access to treatment for people with diabetes. Participants undergo mobile retinal photography performed by a trained nursing assistant under pupil dilation. Those in the AI group have their images analyzed by an AI program to determine if they have referable DR, while those in the ophthalmologist group have their images interpreted remotely by eye specialists. Based on these results, patients are classified for referral to a specialist for further care. During the study, researchers will track the number of appropriate referrals to ophthalmologists and monitor referrals for laser treatment or pharmacological intraocular treatments over about one year. They will also observe any referral failures for an average of 15 months after study completion. The study involves a randomized design with quadruple masking to ensure unbiased results.
CONDITIONS
Brief Title
Artificial Intelligence for Diagnosing Diabetic Retinopathy in Primary Care
Who Can Participate
Age: 18Years +
All Genders
Eligibility Criteria
You may qualify if you...
- Adults over 18 years old diagnosed with diabetes mellitus who agree to participate in the study
You will not qualify if you...
- Contraindications for pharmacological pupil dilation, such as known closed-angle glaucoma or pregnancy
- Life expectancy less than 6 months
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
1
2
3
Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
Surveillance
Duration - Approximately 1 year
Participants undergo mobile retinal photography in primary care to screen for diabetic retinopathy, with images interpreted either by artificial intelligence or ophthalmologists depending on group assignment.
1 visit (in-person) for retinal photography with follow-up as needed based on results
Trial Site Locations
Total: 1 location
1
Hospital de Clínicas de Porto Alegre
Porto Alegre, Rio Grande do Sul, Brazil, 90035-903
Actively Recruiting
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Research Team
B
Beatriz D Schaan, MD, PhD
How is the study designed?
Study Type
INTERVENTIONAL
Masking
QUADRUPLE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
SCREENING
Number of Arms
2
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Published Research Related To This Trial
Organizational intervention to improve access to retinopathy screening for patients with diabetes mellitus: health care service improvement project in a tertiary public hospital.
Josiane Schneiders, Gabriela H Telo, Daniel Lavinsky...
https://pubmed.ncbi.nlm.nih.gov/37328386Advancing healthcare with artificial intelligence: diagnostic accuracy of machine learning algorithm in diagnosis of diabetic retinopathy in the Brazilian population.
Mateus A Dos Reis, Cristiano A Künas, Thiago da Silva Araújo...
https://pubmed.ncbi.nlm.nih.gov/39210394