Using AI for early detection of diabetic retinopathy in Chernivtsi

USING ARTIFICIAL INTELLIGENCE FOR MASS SCREENING OF THE DIABETIC RETINOPATHY

This study is testing whether using artificial intelligence to analyze eye images can help catch early signs of diabetic retinopathy in people with diabetes in Chernivtsi.

Quick facts

• Study type: Observational
• Enrollment: 660 (estimated)
• Ages: 18 Years to 90 Years
• Sex: All
• Sponsor: The Filatov Institute of Eye Diseases and Tissue Therapy (Academic / other)
• Locations: 1 site (Odessa)
• Trial ID: NCT06112691 on ClinicalTrials.gov

What this trial studies

This pilot study aims to establish a patient-centric approach for the early detection of diabetic retinopathy (DR) using artificial intelligence. Participants diagnosed with diabetes will have their fundus photographs taken by trained photographers using a non-mydriatic ocular fundus camera. The captured images will be analyzed by the RAssbyAI Check Eye's imaging protocol to identify signs of DR. This observational study focuses on improving screening methods for diabetic patients in the Chernivtsi region.

Who should consider this trial

Good fit: Ideal candidates for this study are adults aged 18 and older with a documented diagnosis of diabetes mellitus.

Not a fit: Patients under 18 years of age or those with existing retinal diseases may not benefit from this study.

Why it matters

Potential benefit: If successful, this study could enhance early detection and management of diabetic retinopathy, potentially preventing vision loss in diabetic patients.

How similar studies have performed: Other studies utilizing AI for screening diabetic retinopathy have shown promising results, indicating potential for success in this approach.

Eligibility criteria

Inclusion Criteria:

1. Documented diagnosis of Diabetes mellitus as defined by:

   A. Having met the criteria established by either the World Health Organization (WHO) or the American Diabetes Association (ADA) B. Hemoglobin A1c (HbA1c)\>= 6.5% based on repeated assessments C. Fasting Plasma Glucose (FPG) \>= 126 mg/dL (7.0 mmol/L) based on repeated assessments D. Oral Glucose Tolerance test with 2 hr plasma glucose \>= 200 mg/dL (11.1mmol/L) using equivalent of 75g anhydrous glucose dose in water.

   E. Symptoms of hyperglycemia or hyperglycemic crisis with random plasma glucose \>=200mg/dL (11.1 mmol/L).
2. Understanding of the Study and willingness and ability to sign informed consent
3. Patient age 18 or above
4. Diagnostic for diabetes: 4a) Type 1 diabetes of a lest 5 years of evolution; or 4b) Type 2 diabetes

   -

Exclusion Criteria:

1. Patients under 18 years of age;
2. Failure to give informed consent;
3. Presence of retinal diseases - acquired disease: age-related macular degeneration (AMD), occlusion of retinal vessels (ORV), etc.; birth defects: coloboma of choroid or optic nerve disc, etc.; hereditary diseases: retinitis pigmentosa, angioid streaks of the retina, etc.
4. A patient who has already undergone treatment (surgery, laser, etc.) for any disease of the retina: age-related macular degeneration (AMD), retinal vascular occlusion (ARV), etc. These patients should be excluded or allocated to a separate group.

Where this trial is running

Odessa

• The Filatov Institute of Eye Diseases and Tissue Therapy — Odessa, Ukraine (Recruiting)

Study contacts

• Principal investigator: Andrii MD Korol, PhD — The Filatov Institute of Eye Diseases and Tissue Therapy
• Study coordinator: Andrii MD Korol, PhD

Conditions Diabetic Retinopathy; Fundus photo; Artificail Intelligence; Diabetes Melitus; Screening; CheckEye; Fundus image; nonmydriatic camera