Purpose of review
Sudden cardiac arrest (SCA) remains a major health burden around the globe, most often occurring in the community (out-of-hospital cardiac arrest [OHCA]). SCA accounts for 15–20% of all natural deaths in adults in the USA and Western Europe, and up to 50% of all cardiovascular deaths. To reduce this burden, more knowledge is needed about its key facets such as its incidence in various geographies, its risk factors, and the populations that may be at risk.
SCA results from a complex interaction of inherited and acquired causes, specific to each individual. Resolving this complexity, and designing personalized prevention and treatment, requires an integrated approach in which big datasets that contain all relevant factors are collected, and a multimodal analysis. Such datasets derive from multiple data sources, including all players in the chain-of-care for OHCA. This recognition has led to recently started large-scale collaborative efforts in Europe.
Our insights into the causes of SCA are steadily increasing thanks to the creation of big datasets dedicated to SCA research. These insights may be used to earlier recognize of individuals at risk, the design of personalized methods for prevention, and more effective resuscitation strategies for OHCA.