Artificial Intelligence for Diagnosing Diabetic Retinopathy in Primary Care
NCT ID: NCT07236879
Last Updated: 2025-11-19
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
922 participants
INTERVENTIONAL
2024-08-08
2026-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
SCREENING
QUADRUPLE
Study Groups
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RDIA group
The proposed intervention is the provision of universal screening for DR with retinography performed on a mobile fundus camera under mydriasis supported by a computer program in adults with diabetes mellitus; based on the diagnosis made by the computer program, patients will be classified as having referable DR or not, and referral to a specialist will be based on this classification.
Mobile retinography interpreted by artificial intelligence
All participants will undergo mobile retinal photography in primary care by a trained nursing assistant. If randomized to RDIA group, their photos will be analyzed by artificial intelligence.
RDOF group
The proposed control is the provision of universal screening for DR in adults with diabetes mellitus with retinography performed on a mobile fundus camera under mydriasis and with obtained images being interpreted remotely by ophthalmologists; based on the diagnosis made by the ophthalmologist, patients will be classified as having referable DR or not, and referral to a specialist will be based on this classification.
Mobile retinography interpreted by ophthalmologists
All participants will undergo mobile retinal photography in primary care by a trained nursing assistant. If randomized to RDOF group, their photos will be interpreted remotely by ophthalmologists.
Interventions
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Mobile retinography interpreted by artificial intelligence
All participants will undergo mobile retinal photography in primary care by a trained nursing assistant. If randomized to RDIA group, their photos will be analyzed by artificial intelligence.
Mobile retinography interpreted by ophthalmologists
All participants will undergo mobile retinal photography in primary care by a trained nursing assistant. If randomized to RDOF group, their photos will be interpreted remotely by ophthalmologists.
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Life expectancy less than 6 months
18 Years
ALL
No
Sponsors
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Fundação de Amparo à Pesquisa do Estado de São Paulo
OTHER_GOV
Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul, Brazil
OTHER
TelessaúdeRS / UFRGS
UNKNOWN
Hospital de Clinicas de Porto Alegre
OTHER
Responsible Party
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Principal Investigators
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Beatriz D Schaan, MD, PhD
Role: PRINCIPAL_INVESTIGATOR
Hospital de Clínicas de Porto Alegre
Locations
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Hospital de Clínicas de Porto Alegre
Porto Alegre, Rio Grande do Sul, Brazil
Countries
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Central Contacts
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Facility Contacts
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References
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Chagas TA, Dos Reis MA, Leivas G, Santos LP, Gossenheimer AN, Melo GB, Malerbi FK, Schaan BD. Prevalence of diabetic retinopathy in Brazil: a systematic review with meta-analysis. Diabetol Metab Syndr. 2023 Mar 2;15(1):34. doi: 10.1186/s13098-023-01003-2.
Schneiders J, Telo GH, Lavinsky D, Dos Reis MA, Correa BG, Schaan BD. Organizational intervention to improve access to retinopathy screening for patients with diabetes mellitus: health care service improvement project in a tertiary public hospital. Prim Care Diabetes. 2023 Aug;17(4):354-358. doi: 10.1016/j.pcd.2023.05.007. Epub 2023 Jun 14.
Dos Reis MA, Kunas CA, da Silva Araujo T, Schneiders J, de Azevedo PB, Nakayama LF, Rados DRV, Umpierre RN, Berwanger O, Lavinsky D, Malerbi FK, Navaux POA, Schaan BD. Advancing healthcare with artificial intelligence: diagnostic accuracy of machine learning algorithm in diagnosis of diabetic retinopathy in the Brazilian population. Diabetol Metab Syndr. 2024 Aug 29;16(1):209. doi: 10.1186/s13098-024-01447-0.
Other Identifiers
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2024-0238
Identifier Type: -
Identifier Source: org_study_id
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