Development of CV Risk Prediction Tools Based on AI and Fundus Imaging Technology Study (PERFECT)
PERFECT
Development of Cardiovascular Risk Prediction Tools Based on Artificial Intelligence and Fundus Imaging Technology Study
1 other identifier
observational
1,072
0 countries
N/A
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Dec 2023
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
November 9, 2023
CompletedStudy Start
First participant enrolled
December 1, 2023
CompletedFirst Posted
Study publicly available on registry
December 26, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 1, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
June 1, 2025
CompletedDecember 26, 2023
December 1, 2023
1.2 years
November 9, 2023
December 20, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Diagnosis of ASCVD at baseline
Whether participants have established ASCVD at baseline
At enrollment
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
Study Arms (2)
Participants with CVD
Meeting any of the following: 1. 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 (indicated by stress electrocardiogram or stress imaging) 2. Stroke
Participants with high CVD risk
Participants without CVD, but 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.
Interventions
All the participants will undergo fundus photography.
All the participants will undergo OCT examination.
All the participants will undergo OCT-A examination.
Eligibility Criteria
Participants with CVD, or otherwise with high CVD risk will be enrolled.
You may qualify if:
- 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:
- Men aged ≥ 60 years old, or women aged ≥ 65 years old;
- Diabetes;
- Total cholesterol\>5.2 mmol/L, or LDL-C\>3.4 mmol/L, or HDL-C\<1.0 mmol/L;
- Currently smoking, defined as daily smoking lasting for 1 year or more.
You may not qualify if:
- Participants unable to provide fundus imaging data required for the study due to the following reasons:
- Permanent blindness, blurred vision, flying mosquito disease, or refractive medium opacity seriously affecting fundus examination, such as severe cataracts, vitreous hemorrhage, etc.
- Macular edema, severe nonproliferative retinopathy in diabetes, proliferative vitreoretinopathy, radiation ophthalmopathy or retinal vein occlusion
- Eyeball enucleation, eye deformities, etc.
- Previous retinal laser therapy, injection therapy for any eye, or history of retinal surgery
- Photosensitivity, or taking medication that can cause photosensitivity, or currently undergoing photodynamic therapy
- Unable to cooperate with examination for collection of fundus imaging data
- 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
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Related 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. Epub 2018 Feb 19.
PMID: 31015713RESULT
MeSH Terms
Conditions
Interventions
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Jing Li, PhD, MD
National Center for Cardiovascular Diseases, Fuwai Hospital
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER GOV
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
November 9, 2023
First Posted
December 26, 2023
Study Start
December 1, 2023
Primary Completion
March 1, 2025
Study Completion
June 1, 2025
Last Updated
December 26, 2023
Record last verified: 2023-12