AI model accurately predicts sudden cardiac death in overall population

A novel prediction model for sudden cardiac death was able to calculate the risk for sudden cardiac death with high accuracy. The model, based on artificial intelligence (AI), included both cardiac risk factors and non-cardiac risk factors. A subsequent study will aim to enhance the prediction of sudden cardiac death by identifying relevant clinical subgroups.

Prof. Xavier Jouven (Georges-Pompidou European Hospital, France) and co-authors aimed to develop a sudden cardiac death prediction with a particular focus on the low-risk general population since they comprise the highest absolute number of sudden cardiac death and are more difficult to capture than patients with known high-risk factors, such as previous myocardial infarctions [1]. The study group included 12,784 cases of sudden cardiac death from the Paris Sudden Death Expertise Center and 10,000 matched controls. Using AI, an individualised 1-year predicted risk score for sudden cardiac death was calculated.

Selected were 200 variables from 10,000 medical codes. The developed deep-learning model displayed an area under the curve (AUC) of 0.88, a sensitivity of 81%, and a positive predictive value of 88%. Notably, when non-cardiovascular variables were added, the AUC of the model was elevated from 0.81 to 0.88. Furthermore, the model was able to identify participants who had a risk of 90% or more of experiencing sudden cardiac death in the coming year with a positive predictive value of 95%, capturing 43% of the total number of sudden cardiac death cases. The study group will be working to improve the sudden cardiac death risk prediction model by identifying clinical subgroups of interest in a successive study.

1. Jouven X, et al. Prediction of sudden cardiac death using artificial intelligence. Late-breaking science 1, EHRA 2022, 3–5 April, Copenhagen, Denmark.

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Posted on 1 June 202213 June 2022