Key result
Individualized dynamical models based on measured anatomy and physiology may improve risk stratification for sudden cardiac death and lay a foundation for personalized medicine.
Individualized dynamical modeling of ventricular arrhythmia dynamics represents an emerging approach to improve sudden cardiac death risk stratification.
Sudden cardiac death (SCD) is the result of a change of cardiac activity from normal (typically sinus) rhythm to a rhythm that does not pump adequate blood to the brain. The most common rhythms leading to SCD are ventricular tachycardia (VT) or ventricular fibrillation (VF). These result from an accelerated ventricular pacemaker or ventricular reentrant waves. Despite significant efforts to develop accurate predictors for the risk of SCD, current methods for risk stratification still need to be improved. In this article we briefly review current approaches to risk stratification. Then we discuss the mathematical basis for dynamical transitions (called bifurcations) that may lead to VT and VF. One mechanism for transition to VT or VF involves a perturbation by a premature ventricular complex (PVC) during sinus rhythm. We describe the main mechanisms of PVCs (reentry, independent pacemakers and abnormal depolarizations). An emerging approach to risk stratification for SCD involves the development of individualized dynamical models of a patient based on measured anatomy and physiology. Careful analysis and modelling of dynamics of ventricular arrhythmia on an individual basis will be essential in order to improve risk stratification for SCD and to lay a foundation for personalized (precision) medicine in cardiology.
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Lerma et al. (2015) conducted a review in Sudden cardiac death. Individualized dynamical models was evaluated. Individualized dynamical models based on measured anatomy and physiology may improve risk stratification for sudden cardiac death and lay a foundation for personalized medicine.
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