CUHK Develops Highly Accurate Retinal Approach to Assess Heart Disease Risk in People Living With HIV
Since people living with HIV are at an increased risk for developing cardiovascular diseases, regular risk screening is recommended. However, conventional cardiovascular risk prediction models are not accurate enough due to their failure to consider crucial variables such as race and health status, including conditions like AIDS. To address this issue, the researchers at the Faculty of Medicine of the Chinese University of Hong Kong (CUHK), utilized an innovative technique called “Automatic Retinal Image Analysis,” which analyzes retinal features by capturing retinal images, also known as digital fundus photographs. By combining these images with traditional models, the researchers were able to accurately calculate the risk of two types of coronary heart disease in HIV-infected patients with a sensitivity and specificity exceeding 90 percent. The study’s findings were published in the international medical journal PLOS ONE. People with HIV are twice as likely to develop cardiovascular disease as the general population, and are at higher risk of developing diabetes and hypertension, which are risk factors for cardiovascular disease. Dr. Grace Lui Chung-yan, clinical associate professor (honorary) from the Department of Medicine and Therapeutics at CU Medicine, said, “Current clinical guidelines recommend that people living with HIV have regular cardiovascular risk screenings. Though there are various traditional risk prediction models, none has been developed for HIV-infected populations, so there is a need to look for the best model for them.” Professor Benny Zee Chung-ying, director of the Centre for Clinical Research and Biostatistics at The Jockey Club School of Public Health and Primary Care at CU Medicine, added, “Recent studies have shown retinal image characteristics are closely linked with multiple cardiovascular risk factors and major cardiovascular events. Features including arteriolar and venular calibre, curvature tortuosity and branching complexity have been shown to have associations with coronary artery disease.” For this purpose, a research team at CU Medicine recently recruited 115 patients who were HIV-infected and had one or more risk factors for cardiovascular disease. The team analyzed the patients’ retinal features in combination with traditional cardiovascular risk factors. The results showed that out of the study population, 71 individuals (62 percent) had coronary atherosclerosis, and 23 individuals (20 percent) had obstructive coronary artery disease, which was detected through computerized tomography. Researchers used instruments to capture retinal images of participants and utilized machine learning and deep learning to identify pertinent retinal features. The results showed this new risk prediction model was more than 90 percent sensitive and specific in assessing the risk of these two major coronary heart diseases in HIV-infected patients. (CUHK)
Udumbara
Since people living with HIV are at an increased risk for developing cardiovascular diseases, regular risk screening is recommended. However, conventional cardiovascular risk prediction models are not accurate enough due to their failure to consider crucial variables such as race and health status, including conditions like AIDS.
To address this issue, the researchers at the Faculty of Medicine of the Chinese University of Hong Kong (CUHK), utilized an innovative technique called “Automatic Retinal Image Analysis,” which analyzes retinal features by capturing retinal images, also known as digital fundus photographs. By combining these images with traditional models, the researchers were able to accurately calculate the risk of two types of coronary heart disease in HIV-infected patients with a sensitivity and specificity exceeding 90 percent. The study’s findings were published in the international medical journal PLOS ONE.
People with HIV are twice as likely to develop cardiovascular disease as the general population, and are at higher risk of developing diabetes and hypertension, which are risk factors for cardiovascular disease.
Dr. Grace Lui Chung-yan, clinical associate professor (honorary) from the Department of Medicine and Therapeutics at CU Medicine, said, “Current clinical guidelines recommend that people living with HIV have regular cardiovascular risk screenings. Though there are various traditional risk prediction models, none has been developed for HIV-infected populations, so there is a need to look for the best model for them.”
Professor Benny Zee Chung-ying, director of the Centre for Clinical Research and Biostatistics at The Jockey Club School of Public Health and Primary Care at CU Medicine, added, “Recent studies have shown retinal image characteristics are closely linked with multiple cardiovascular risk factors and major cardiovascular events. Features including arteriolar and venular calibre, curvature tortuosity and branching complexity have been shown to have associations with coronary artery disease.”
For this purpose, a research team at CU Medicine recently recruited 115 patients who were HIV-infected and had one or more risk factors for cardiovascular disease. The team analyzed the patients’ retinal features in combination with traditional cardiovascular risk factors. The results showed that out of the study population, 71 individuals (62 percent) had coronary atherosclerosis, and 23 individuals (20 percent) had obstructive coronary artery disease, which was detected through computerized tomography.
Researchers used instruments to capture retinal images of participants and utilized machine learning and deep learning to identify pertinent retinal features. The results showed this new risk prediction model was more than 90 percent sensitive and specific in assessing the risk of these two major coronary heart diseases in HIV-infected patients.
