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Heart rate variability before the onset of ventricular tachycardia: differences between slow and fast arrhythmias
Udo Meyerfeldt1, Niels Wessel, Henry Schütt
1HELIOS Klinikum Berlin, Franz-Volhard-Hospital, Charité, Humboldt-University, Wiltbergstrasse 50, D-13125 Berlin, Germany. meyerfeldt@fvk-berlin.de
Insights
Nonlinear heart rate variability (HRV) parameters can predict ventricular tachycardia (VT) onset in implantable cardioverter defibrillator (ICD) patients. These findings may lead to improved VT detection algorithms and prevention strategies.
Area of Science:
- Cardiology
- Biomedical Engineering
- Nonlinear Dynamics
Background:
- Heart rate variability (HRV) analysis is crucial for understanding cardiac electrophysiology.
- Ventricular tachycardia (VT) poses a significant risk in patients with implantable cardioverter defibrillators (ICDs).
- Early detection of VT is essential for timely intervention and improved patient outcomes.
Purpose of the Study:
- To investigate if changes in HRV can serve as early indicators of VT.
- To determine if HRV can predict the onset of both slow and fast VT in ICD patients.
- To explore the utility of nonlinear HRV parameters for VT prediction.
Main Methods:
- Analysis of 1000 beat-to-beat intervals before VT episodes and during control periods in 63 chronic heart failure ICD patients.
- Calculation of standard linear HRV parameters and nonlinear parameters ('Polvar10', 'Fitgra9').
- Comparison of HRV parameters between control periods and the pre-VT onset phase.
Main Results:
- No significant differences were observed in linear HRV parameters before VT onset.
- Nonlinear HRV parameters ('Polvar10', 'Fitgra9') showed a significant increase in short phases with low variability preceding VT (P<0.05).
- Slow VT onset was associated with increased heart rate, while fast VT onset occurred during decreased heart rates compared to controls.
Conclusions:
- Nonlinear dynamic HRV parameters show promise for predicting VT before its occurrence.
- The findings support the development of advanced ICD algorithms for automatic VT prediction.
- Improved prevention strategies for VT may be facilitated by these nonlinear HRV analyses.
Background:
We tested whether or not heart rate variability (HRV) changes can serve as early signs of ventricular tachycardia (VT) and predict slow and fast VT in patients with an implantable cardioverter defibrillator (ICD).
Methods And Results:
We studied the ICD stored 1000 beat-to-beat intervals before the onset of VT (131 episodes) and during a control time without VT (74 series) in 63 chronic heart failure ICD patients. Standard HRV parameters as well as two nonlinear parameters, namely 'Polvar10' from symbolic dynamics and the finite time growth rates 'Fitgra9' were calculated. Comparing the control and the VT series, no linear HRV parameter showed a significant difference. The nonlinear parameters detected a significant increase in short phases with low variability before the onset of VT (for time series with less than 10% ectopy, P<0.05). Subdividing VT into fast (cycle length
Conclusions:
Our data may permit the development of automatic ICD algorithms based on nonlinear dynamic HRV parameters to predict VT before it starts. Furthermore, they may facilitate improved prevention strategies.