Sudden cardiac death, a public health burden, represents 10 per cent to 20 per cent of overall deaths. Predicting it is difficult, and the usual approaches fail to identify high-risk people, particularly at an individual level,” said lead author Xavier Jouven, professor of cardiology and epidemiology at the Paris Cardiovascular Research Center, Inserm and University of Paris in France
Predicting sudden cardiac death, and perhaps even addressing a person’s risk to prevent future death, may be possible through artificial intelligence (AI), according to a research that could offer a new move toward prevention and global health strategies.
The AI analysis was able to identify people who had more than 90 per cent of risk of dying suddenly, and they represented more than one fourth of all cases of sudden cardiac death. “
Sudden cardiac death, a public health burden, represents 10 per cent to 20 per cent of overall deaths. Predicting it is difficult, and the usual approaches fail to identify high-risk people, particularly at an individual level,” said lead author Xavier Jouven, professor of cardiology and epidemiology at the Paris Cardiovascular Research Center, Inserm and University of Paris in France.
“We proposed a new approach not restricted to the usual cardiovascular risk factors but encompassing all medical information available in electronic health records,”Jouven added.
The findings will be presented at the American Heart Association’s Scientific Sessions 2023, to be held between November 11 and 13, in Philadelphia, US.
The team analysed medical information with AI from registries and databases in Paris, France and Seattle for 25,000 people who had died from sudden cardiac arrest and 70,000 people from the general population, with data from the two groups matched by age, sex and residential area.
The data, which represented more than one million hospital diagnoses and 10 million medication prescriptions, was gathered from medical records up to 10 years prior to each death.
Using AI to analyse the data, researchers built nearly 25,000 equations with personalised health factors used to identify those people who were at very high risk of sudden cardiac death.
Additionally, they developed a customised risk profile for each of the individuals in the study.
The personalised risk equations included a person’s medical details, such as treatment for high blood pressure and history of heart disease, as well as mental and behavioural disorders including alcohol abuse.
The analysis identified those factors most likely to decrease or increase the risk of sudden cardiac death at a particular percentage and time frame, for example, 89 per cent risk of sudden cardiac death within three months.
“While doctors have efficient treatments such as correction of risk factors, specific medications and implantable defibrillators, the use of AI is necessary to detect in a given subject a succession of medical information registered over the years that will form a trajectory associated with an increased risk of sudden cardiac death,” Jouven said.
“We hope that with a personalised list of risk factors, patients will be able to work with their clinicians to reduce those risk factors and ultimately decrease the potential for sudden cardiac death.”