Overview
This is a multi-site, observational clinical study to validate the performance of the CLAiR AI software in identifying elevated atherosclerotic cardiovascular disease (ASCVD) risk from retinal (eye) images obtained from two different retinal image camera models.
Description
This is a prospective observational clinical study to collect retinal images and clinical biomarker data in order to analyze the performance of the CLAiR SaMD compared to the reference PCE risk score. CLAiR is a deep learning (DL) model that uses retinal photographs and limited demographic data to classify an individual's risk of developing ASCVD over the next 10 years as elevated (≥7.5%) or non-elevated (<7.5%). For validation, the output of the algorithm can be directly compared to the PCE output, a widely accepted algorithm used by Healthcare Providers to predict ASCVD risk in patients.
The primary hypothesis is that the CLAiR SaMD can achieve high sensitivity and specificity in the binary determination of Yes/No elevated ASCVD risk with PCE risk score ≥7.5% as the reference standard.
Eligibility
Inclusion Criteria:
- Male or female, aged 40-75 years
- Participants must be capable of providing informed consent, demonstrating understanding of the study details, and willingly sign a consent form or verbally confirm their consent in the presence of a witness.
- Stated willingness to comply with all study procedures and availability for the duration of the study
Exclusion Criteria:
An individual who meets any of the following criteria will be excluded from participation in this study:
- Known history of atherosclerotic cardiovascular disease, including stroke, heart attack, coronary artery surgery, or stenting
- Current use of cholesterol-lowering medication, such as a statin
- Pregnancy
- A person who has (in at least one eye):
- Persistent vision impairment: legally blind when wearing current driving glasses or known VA<20/400
- Known pathological myopia
- Previous treatment or currently under the care for a retinal disease by a specialist (e.g., ophthalmologist)