Diabetic Retinopathy
Conditions
Keywords
Diabetic Retinopathy, Fundus photo, Artificail Intelligence, Diabetes Melitus, Screening, CheckEye, Fundus image, nonmydriatic camera
Brief summary
The purpose of this study is to create a patient-centric environment for early detection of DR with AI-driven solutions.
Detailed description
The purpose of this study is to create a patient-centric environment for early detection of DR with AI-driven solutions. This study is planned as a follow-up. Participants who meet the eligibility criteria will be recruited from sites staffed by the trained photographers. After assessing eligibility and securing written informed consent, fundus photographs will be captured using a nonmydriatic ocular fundus camera. Images will be taken according to a specific RAssbyAI Check Eye's imaging protocol provided to camera operator, and then analyzed by the RAssbyAI Check Eye's. The photography protocol consists of two images of the ocular fundus (one optic disc centered, one fovea centered).
Interventions
DEVICEtaking fundus photos using non-mydriatic fundus camera - FundusScope Rodenstock
using artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography.
Sponsors
Komisarenko Institute of Endocrinology and Metobolism
CheckEye LLC
The Filatov Institute of Eye Diseases and Tissue Therapy
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 90 Years
Healthy volunteers
Yes
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The accuracy | Baseline-Month 12 | The accuracy of detecting of DR |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| The percent of invalid images | Baseline-Month 12 | The percent of invalid images for analysing by neural network |
| The percent of false positive detection of DR | Baseline-Month 12 | The percent of false positive detection of DR in individuals without DR |
Countries
Ukraine
Contacts
Primary ContactAndrii MD Korol, PhD
Backup ContactOlha MD Pohosian
Outcome results
None listed