A senior woman experiencing chest pain. A senior man is in the background.
At the present stage of development of diagnostic medicine, the diagnosis of the potential risk of a heart attack most often consists in studying various personal factors of human health – among which smoking, diabetes, and family genetics stand out. However, the current diagnostic tools do not have the necessary accuracy and most often begin to be used only when a person reaches the age of about forty years old – thus missing a significant part of other potential factors developed during his life. In order to improve this diagnosis, a team of researchers from the United States introduced their new GRS system.
The GRS system stands for Genomic Risk Score and is primarily engaged in the study, analysis and decoding of gene variants and gene expressions of a person who is being diagnosed to identify a potential heart attack. It is worth noting that the GRS system was developed as a constantly updated genetic base that compares the indices of an individual patient with those of more than two million patients who participated in this program.
The main factors for genetic diagnosis are related to smoking, diabetes, cholesterol, physical activity and family genotype, but the system also takes into account many other factors that develop with age. Its main advantage is that it begins its action in fact from the early childhood of a person, thus covering a really significant set of potential factors contributing to the occurrence of a heart attack.
So far, the system continues to undergo preliminary testing and debugging machine learning algorithms, but experts are confident that it will soon become one of the most powerful and accurate tools to predict the occurrence of a risk of a heart attack and related symptoms. It remains to expect reports and results on the further work of specialists and thus make opinions on the success of the development.