Assessment of Hypertensive Retinopathy Using Convolutional Neural Network "RetinAIcheck"

NCT07471971 | Completed

• 1 other identifier: RetinAIcheck-01
• Study Type: observational
• Target: 729
• Locations: 1 country
• Sites: 1

Brief Summary

The current study is aimed at estimating the diagnostic effectiveness of a developed convolutional neural network (CNN) "RetinAIcheck" in grading the severity of hypertensive retinopathy in patients of the Russian population. The training data set was obtained from an open source and relabeled by seven independent retina specialists, the sample size was 30,000 fundus photographs. The test sample included 729 patients (1401 eyes) with HR. The reference standard was the result of independent grading of HR stage by two ophthalmologists, controversial clinical cases were evaluated with the involvement of a third ophthalmologist.

Conditions

Hypertensive Retinopathy

Keywords

convolutional neural network; hypertensive retinopathy

Outcome Measures

Primary Outcomes (1)

• Accuracy

  The ability of a test to correctly identify the proportion of true positive cases

  The ability to correctly identify the presence or absence of condition

Secondary Outcomes (2)

• Sensitivity

  February 2026

• Specificity

  February 2026

Study Arms (5)

Class 1 hypertensive retinopathy

Diagnostic Test: Convolutional neural network "RetinAIcheck"

Class 2 hypertensive retinopathy

Diagnostic Test: Convolutional neural network "RetinAIcheck"

Class 3 hypertensive retinopathy

Diagnostic Test: Convolutional neural network "RetinAIcheck"

Class 3+4 hypertensive retinopathy

Diagnostic Test: Convolutional neural network "RetinAIcheck"

Class 0 without signs of hypertensive retinopathy

Diagnostic Test: Convolutional neural network "RetinAIcheck"

Interventions

Convolutional neural network "RetinAIcheck" DIAGNOSTIC_TEST

A convolutional neural network is a medical decision support system that processes digital fundus photographs obtained during mydriasis and determines the probability of the presence/absence of hypertensive retinopathy and it's grading due to Keith Wagener Barker's classification.

Class 0 without signs of hypertensive retinopathy; Class 1 hypertensive retinopathy; Class 2 hypertensive retinopathy; Class 3 hypertensive retinopathy; Class 3+4 hypertensive retinopathy

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

The test sample was collected at the Cardiology Clinic of the Sechenov University Clinical Hospital № 1, at the Research Institute of Eye Diseases named after M.M. Krasnov and in the Moscow Regional Clinical Research Institute named after M.F. Vladimirsky (MONIKI).

You may qualify if:

• \- The presence of a diagnosis of hypertension in the patient's electronic medical record.

You may not qualify if:

• anophthalmia,
• optic nerve atrophy,
• eyeball injuries,
• age-related macular degeneration,
• central serous chorioretinopathy,
• central serous chorioretinitis,
• clouding of the optical media of the eye, which affects the quality of the image.

Sponsors & Collaborators

• I.M. Sechenov First Moscow State Medical University: lead

Study Sites (1)

University Clinical Hospital №1, Sechenov University

Moscow, Russia

Location

Related Links

• Related Info

MeSH Terms

Conditions

Hypertensive Retinopathy

Condition Hierarchy (Ancestors)

Retinal Diseases; Eye Diseases; Hypertension; Vascular Diseases; Cardiovascular Diseases

Study Officials

• Philipp Yu Kopylov, Prof.

  Sechenov First Moscow State Medical University (Sechenov University)

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 10, 2026
• First Posted: March 13, 2026
• Study Start: March 11, 2021
• Primary Completion: February 26, 2026
• Study Completion: February 26, 2026
• Last Updated: March 16, 2026

Record last verified: 2021-09

Data Sharing

• IPD Sharing: Will not share

Locations

RU (1)