International Journal of Biomedicine. 2020;10(3):189-197.
Originally published September 10, 2020
According to the World Health Organization (WHO), cardiovascular diseases (CVD) are the number one cause of death globally, taking an estimated 18 million lives each year. Framingham Heart Study Group in Boston developed, the very first 10-year CVD risk prediction model. The WHO recently derived a 10-year risk prediction model, for fatal and non-fatal CVD events using individual participant data, from the Emerging Risk Factor Collaboration. This CVD risk model, derivation involved participation of 376,177 individuals from 85 cohorts, and 19,333 incident CVD events. Cardiometabolic diseases in general, - and metabolic diseases like hypertension, excess weight, obesity, type-2 diabetes, and vascular diseases collectively, contribute to the overall morbidity and mortality related to CVDs. Of the 18 million CVD-related deaths in 2017, more than three quarters were in low-income and middle-income countries. Risk stratification, management, and prevention models can be very important components of disease prevention and control efforts. In view of this very important role the risk assessment plays, we have reviewed and discussed three specific areas of integration of emerging diagnostic technologies,-population level, individual level, and novel ways of collecting, collating, derivation, and validation of individual risks, risk scores for cluster of risks, and for the use of such data for treatment management. For collection of massive data from general population, we have discussed the National Institutes of Health’s flagship program, -All of Us. For empowering individuals in risk assessment and management of identified risks, we have discussed ambulatory diagnostic devices, blood pressure monitors, and continuous glucose monitors. As an example of futuristic approach for the integration of diagnostic tools, we have discussed the products developed by LD-Technologies, Miami, Florida by Dr. Albert Maarek and associates. There are thousands of mHealth apps available for download, and not all are of great use in developing, a seamless diagnostic platform, that we at AayuSmart are trying to put together for cardiometabolic risk stratification, risk prediction, and risk management. We have provided, just a brief glimpse of available tracking, computing, collating, and the software analytical capabilities that exists, and discussed how innovators are trying to use them to build novel diagnostic tools. Despite the important role of telemedicine and internet of things (IOT) in disease management, and healthcare delivery, we have not discussed those applications. In this overview, we have discussed the use of emerging diagnostic tools, for obtaining data at the population level, personal level, as well as for clinical settings. Having said that, we must inform the readers, that there is a great difference between the consumer devices (wrist-worn activity trackers), medical devices (FDA cleared or CE Marked), and a variety of technologies that are in use, but not yet considered clinical testing devices.
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Received June 28, 2020.
Accepted July 27, 2020.
©2020 International Medical Research and Development Corporation.