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NCT Number: NCT04749927

Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease

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.

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Key information

Age range

20 year–79 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Yonsei University College of Medicine

Seoul, 03722, South Korea

Location status: Recruiting

Location contact

Sungha Park

CONTACT

[email protected]

+82-2228-8460

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Myocardial infarction (Patients diagnosed with myocardial infarction within 5 years and confirmed significant coronary artery stenosis by cardiovascular angiography)
  • Heart failure with reduced EF (<40% of LVEF on echocardiography or magnetic resonance imaging)
  • 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))
  • 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)
  • 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)
  • High risk dyslipidemia (LDL-cholesterol >190 mg/dL or > 160 mg/dL inspire of use of moderate or high intensity statin)
  • Diabetes (Type 2 diabetes with more than 5 years of diagnosis or type 1 diabetes with more than 10 years of diagnosis)
  • 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

  • Serious eye diseases that make it impossible to take adequate quality fundus photography
  • If the subject cannot read and sign the consent form in person

Treatment and study plan

Primary outcomes

  1. Major adverse cardiovascular disease

    Time frame: 4 years

    Composite of myocardial infarction, stroke, coronary revascularization including percutaneous coronary intervention and coronary bypass graft, and hospitalization for heart failure

Study contacts

Contact information is provided by the study sponsor or research team.

Sungha Park

CONTACT

[email protected]

+82-2228-8460

Sponsors and collaborators

Lead sponsor

Yonsei University

Other

Registry information

Official study title

Prediction of Incident Atherosclerotic Cardiovascular Disease From Retinal Photographs Via Deep Learning

Important dates

Study start
2020
Primary completion
2029
Study completion
2029
First posted
Feb 11, 2021
Registry last updated
Feb 11, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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