None listed
Conditions
Brief summary
Researchers at the Centre for Eye Research Australia (CERA) in collaboration with industry partner Eyetelligence Pty Ltd have developed a system integrating retinal photography and artificial intelligence (AI) to predict the risk of heart diseases. The retina is located at the back of the eye and has the important ability to sense vision. When the retina is photographed, it shows small vessels that can indicate the health of your heart. The cardiovascular disease (CVD) risk score refers to the probability of developing CVD events in the future. This project aims to assess the real-world impact, accuracy, and feasibility of the rpCVD screening system in primary care settings in Australia.
Interventions
Upon consent, participants will undergo non-mydriatic retinal photography for both eyes. Participants will not be dilated and images will be taken for both eyes. A trained clinical trial research assistant of the research team will take the retinal images for the participants, which takes around 5-10 minutes. If the image quality is insufficient (graded as "ungradable" by the artificial intelligence system), research assistants will try up to three attempts to get good-quality images. The sessio
Upon consent, participants will undergo non-mydriatic retinal photography for both eyes. Participants will not be dilated and images will be taken for both eyes. A trained clinical trial research assistant of the research team will take the retinal images for the participants, which takes around 5-10 minutes. If the image quality is insufficient (graded as "ungradable" by the artificial intelligence system), research assistants will try up to three attempts to get good-quality images. The session will be delivered in a one-on-one and face-to-face mode. Retinal images taken will then be transferred to an artificial intelligence system that we are testing and a retina-predicted cardiovascular disease (CVD) risk score will be generated. Image quality will be assessed by the artificial intelligence system before generating the retina-predicted CVD risk score. If the image quality is ungradable, the retina-predicted CVD risk score will be shown as not applicable. Besides retinal photography, participants will be asked to complete a health survey, and a satisfaction survey about their experiences of using the artificial intelligence system. Information used for well-established CVD risk score calculation, including blood pressure and lipid results is collected. If lipids are not available, research assistants will measure the weight and height of the participants. The whole session requires a once-off visit of 40 minutes to one hour. The trial is carried out at general practitioner clinics. Adherence will be determined by the completion status on the RedCap platform which is recorded by the research assistants.
Sponsors
Centre for Eye Research Australia
Study design
Allocation
Non-randomised trial
Intervention model
Single group
Primary purpose
Prevention
Masking
Open (masking not used)
Eligibility
Sex/Gender
All
Age
45 Years to 70 Years
Healthy volunteers
No
Inclusion criteria
Patients who have completed all or parts of a cardiovascular disease risk assessment in the past six months and are aged between 45 and 70 years old, will be identified by the research team as eligible to participate.
Exclusion criteria
Participants with medical conditions necessitating immediate or urgent medical interventions.
Outcome results
None listed