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Recruiting NCT04749927

Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease

Observational Cardiovascular Disease

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
This is an observational study: the protocol does not assign a study treatment.
Who it may be relevant to
Registry conditions: Cardiovascular Disease. Basic parameters: 20 years — 79 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
South Korea
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

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

Overview

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.

Primary outcome measures

  • Major adverse cardiovascular disease [Time frame: 4 years]

Eligibility criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model
Cohort

Study locations

South Korea · 1 center
  • Yonsei University College of Medicine — Seoul

Identifiers

NCT: NCT04749927 · 4-2020-0951

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗