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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT06181552
Other study ID # 2023-GSP-GG-10
Secondary ID
Status Not yet recruiting
Phase
First received
Last updated
Start date December 2023
Est. completion date June 2025

Study information

Verified date December 2023
Source China National Center for Cardiovascular Diseases
Contact Jing Li, PhD, MD
Phone +86 60866077
Email jing.li@fwoxford.org
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial 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.


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.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 1072
Est. completion date June 2025
Est. primary completion date March 2025
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility 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

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
fundus photograpgy
All the participants will undergo fundus photography.
optical coherence tomography
All the participants will undergo OCT examination.
optical coherence tomography angiography
All the participants will undergo OCT-A examination.

Locations

Country Name City State
n/a

Sponsors (2)

Lead Sponsor Collaborator
China National Center for Cardiovascular Diseases Beijing Tongren Hospital

References & Publications (1)

Poplin R, Varadarajan AV, Blumer K, Liu Y, McConnell MV, Corrado GS, Peng L, Webster DR. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nat Biomed Eng. 2018 Mar;2(3):158-164. doi: 10.1038/s41551-018-0195-0. Ep — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Diagnosis of ASCVD at baseline Whether participants have established ASCVD at baseline At enrollment
Primary Major cardiovascular events 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 during the 1 year follow-up
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