Cardiovascular Diseases
Conditions
Keywords
cardiovascular risk prediction, fundus imaging
Brief summary
This study aims to develop a cardiovascular disease (CVD) screening tool and cardiovascular risk prediction tool based on fundus imaging data with the method of artificial intelligence.
Detailed description
This study will establish a cohort of individuals including patients with CVD and participants with high CVD risk, and all the study participants will be follow-up for 1 year. By collecting baseline clinical data, fundus imaging data, and CVD events during the follow up, this study aims to distinguish CVD status based on the fundus imaging data, and explore the association between fundus imaging data and occurence of CVD during the follow up. By using machine learning approach, this study aims to construct a CVD screening tool and CVD prediction tool based on fundus imaging data.
Interventions
DIAGNOSTIC_TESTfundus photograpgy
All the participants will undergo fundus photography.
DIAGNOSTIC_TESToptical coherence tomography
All the participants will undergo OCT examination.
DIAGNOSTIC_TESToptical coherence tomography angiography
All the participants will undergo OCT-A examination.
Sponsors
Beijing Tongren Hospital
China National Center for Cardiovascular Diseases
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
Three types of participants will be included, which are: * Participants with established coronary heart disease, including previously diagnosed myocardial infarction, previous treatment with coronary intervention or coronary artery bypass grafting, coronary artery stenosis ≥50%, or chest pain with objective evidence of myocardial ischemia (myocardial ischemia indicated by stress electrocardiogram or stress imaging) * Participants with established stroke. * Participants without coronary heart disease or stroke, but are at high risk for CVD, defined as meeting at least two of the following: 1. Men aged ≥ 60 years old, or women aged ≥ 65 years old; 2. Diabetes; 3. Total cholesterol\>5.2 mmol/L, or LDL-C\>3.4 mmol/L, or HDL-C\<1.0 mmol/L; 4. Currently smoking, defined as daily smoking lasting for 1 year or more.
Exclusion criteria
* Participants unable to provide fundus imaging data required for the study due to the following reasons: 1. Permanent blindness, blurred vision, flying mosquito disease, or refractive medium opacity seriously affecting fundus examination, such as severe cataracts, vitreous hemorrhage, etc. 2. Macular edema, severe nonproliferative retinopathy in diabetes, proliferative vitreoretinopathy, radiation ophthalmopathy or retinal vein occlusion 3. Eyeball enucleation, eye deformities, etc. 4. Previous retinal laser therapy, injection therapy for any eye, or history of retinal surgery 5. Photosensitivity, or taking medication that can cause photosensitivity, or currently undergoing photodynamic therapy 6. Unable to cooperate with examination for collection of fundus imaging data 7. Other situations that the participants fail to provide fundus imaging data required for the study * Suffering from other serious diseases with an expected survival period of less than one year, such as advanced malignant tumors * Unable to adhere to follow-up * Other conditions which the researchers consider inappropriate for participants to enroll in the study
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnosis of ASCVD at baseline | At enrollment | Whether participants have established ASCVD at baseline |
| Major cardiovascular events | during the 1 year follow-up | a composite of myocardial infarction, coronary or non coronary revascularization surgery, hospitalization or emergency treatment due to new-onset or worsening heart failure, stroke or cardiovascular death |
Contacts
Primary ContactJing Li, PhD, MD
Backup ContactBin Wang, PhD, MD
Outcome results
None listed