Traditional and emerging risk factors, including diabetes, obesity, and electrocardiographic biomarkers, contribute to the risk prediction of sudden cardiac arrest in the general population.
What are the traditional and emerging risk factors predictive of sudden cardiac arrest in the general population?
This review highlights the importance of traditional and emerging risk factors, including electrocardiographic biomarkers and machine learning, for predicting sudden cardiac arrest in the general population.
Sudden cardiac death (SCD) is the most common and devastating outcome of sudden cardiac arrest (SCA), defined as an abrupt and unexpected cessation of cardiovascular function leading to circulatory collapse. The incidence of SCD is relatively infrequent for individuals in the general population, in the range of 0.03%-0.10% per year. Yet, the absolute number of cases around the world is high because of the sheer size of the population at risk, making SCA/SCD a major global health issue. On the basis of conservative estimates, there are at least 2 million cases of SCA occurring worldwide on a yearly basis. As such, identification of risk factors associated with SCA in the general population is an important objective from a clinical and public health standpoint. This review will provide an in-depth discussion of established and emerging factors predictive of SCA/SCD in the general population beyond coronary artery disease and impaired left ventricular ejection fraction. Contemporary studies on the association of age, sex, race, socioeconomic status, and the emerging contribution of diabetes and obesity to SCD risk beyond their role as atherosclerotic risk factors are reviewed. In addition, the role of biomarkers, particularly electrocardiographic ones, on SCA/SCD risk prediction in the general population are discussed. Finally, the use of machine learning as a tool to facilitate SCA/SCD risk prediction is examined.
Ha et al. (2022) conducted a review in Sudden cardiac arrest. Traditional and emerging risk factors was evaluated on Sudden cardiac arrest or sudden cardiac death. Traditional and emerging risk factors, including diabetes, obesity, and electrocardiographic biomarkers, contribute to the risk prediction of sudden cardiac arrest in the general population.
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