Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease

NCT ID: NCT04749927

Last Updated: 2021-02-11

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 2400 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2020-10-11
• Study Completion Date: 2029-10-10

Brief Summary

The research team has developed a deep learning algorithm that predicts anthropometric factors from fundus photographs and an algorithm that predicts cardiovascular disease risk. Fundus photographs are taken for various cardiovascular diseases (myocardial infarction, heart failure, hypertension with target organ damage, high-risk dyslipidemia, diabetic patients, and low-risk hypertension patients), and a deep learning algorithm for predicting developed anthropometric factors will be validated. Fundus photographs will also be taken twice in the first year, and additional fundus photographs will be taken two years later. Major cardiovascular events will be followed up for 5 years to verify the deep learning algorithm predicting cardiovascular disease risk prospectively.

Conditions

Cardiovascular Disease

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Eligibility Criteria

Inclusion Criteria

1. Myocardial infarction (Patients diagnosed with myocardial infarction within 5 years and confirmed significant coronary artery stenosis by cardiovascular angiography)

2. Heart failure with reduced EF (<40% of LVEF on echocardiography or magnetic resonance imaging)

3. Heart failure with preserved EF (≥40% of LVEF on echocardiography and NT-proBNP ≥200 pg/mL and LAVI ≥ 34 ml/m2 or LVMI ≥115 g/m2 (men) or LVMI ≥95 g/m2 (women))

4. High risk subclinical atherosclerosis (no symptom and ≥50% stenosis of coronary artery on coronary angio CT or asymptomatic PAOD or cerebral aneurysm or ≥50% stenosis of cerebral artery or ABI <0.9 or ≥2mm of atherosclerotic plaque or hypoechogenic plaque on carotid ultrasound)

5. Hypertension with target organ damage (proteinuria [urine albumin/creatinine ratio ≥ 30 mg/g or protein/creatinine ratio ≥ 150 mg/g or 24 hour urine albumin ≥30mg/day or 24 hour urine protein ≥ 150mg/day] or LV hypertrophy [on EKG or echocardiography] or cfPWV > 10 m/sec or baPWV > 1800 cm/sec or eGFR < 60 ml/min/1.72 m2 or atherosclerotic cardiovascular disease or white matter hyperintensity on brain MRI)

6. High risk dyslipidemia (LDL-cholesterol >190 mg/dL or > 160 mg/dL inspire of use of moderate or high intensity statin)

7. Diabetes (Type 2 diabetes with more than 5 years of diagnosis or type 1 diabetes with more than 10 years of diagnosis)

8. Low risk (Hypertension that does not meet the above criteria and is controlled by 3 drugs or less 2) Dyslipidemia that does not meet the above criteria and is controlled below the target LDL)

Exclusion Criteria

1. Serious eye diseases that make it impossible to take adequate quality fundus photography

2. If the subject cannot read and sign the consent form in person

• Minimum Eligible Age: 20 Years
• Maximum Eligible Age: 79 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Yonsei University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Sungha Park

Role: PRINCIPAL_INVESTIGATOR

Severance Hospital

Locations

Yonsei University College of Medicine

Seoul, , South Korea

Site Status: RECRUITING

Countries

South Korea

Central Contacts

Sungha Park

Role: CONTACT

shpark0530@yuhs.ac

+82-2228-8460

Facility Contacts

Sungha Park

Role: primary

shpark0530@yuhs.ac

+82-2228-8460

Other Identifiers

4-2020-0951

Identifier Type: -

Identifier Source: org_study_id