Statistical Versus Individual Forecasting of Life-Threatening Cardiac Arrhythmias

Abstract

Ventricular tachycardia or fibrillation (VT) as fatal cardiac arrhythmias are the main factors triggering sudden cardiac death. The objective of this investigation is to find early signs of sustained VT in patients with an implanted cardioverter-defibrillator (ICD). These devices are able to safeguard patients by returning their hearts to a normal rhythm via strong defibrillatory shocks; additionally, they are able to store at least 1000 beat-to-beat intervals immediately before the onset of a life-threatening arrhythmia. We study these 1000 beat-to-beat intervals of 63 chronic heart failure ICD patients before the onset of a life-threatening arrhythmia and at a control time, i.e. without VT event. To characterize these rather short data sets, we calculate heart rate variability (HRV) parameters from time and frequency domain, from symbolic dynamics as well as the finite-time growth rates. We find that no linear parameter shows significant differences in HRV between the VT and the control time series. However, the nonlinear parameters detected a significant increase in short phases with low variability before the onset of VT (p<0.05, for time series with less than 10% ectopy). Finally, we are investigating whether these results may lead to individual predictions of VT