Heart Rate Variability and Nonlinear Dynamics in Risk Stratification
The time domain measures and power spectral analysis of heart rate variability (HRV) are classic conventional methods to assess the complex regulatory system between autonomic nervous system and heart rate and are most widely used. There are abundant scientific data about the prognostic significance...
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doaj-c11026ee6a054b229f84c0fbe06eade82020-11-24T21:02:06ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2011-11-01210.3389/fphys.2011.0008115099Heart Rate Variability and Nonlinear Dynamics in Risk StratificationJuha ePerkiömäki0Óulu University HospitalThe time domain measures and power spectral analysis of heart rate variability (HRV) are classic conventional methods to assess the complex regulatory system between autonomic nervous system and heart rate and are most widely used. There are abundant scientific data about the prognostic significance of the conventional measurements of HRV in patients with various conditions, particularly with myocardial infarction. Some studies have suggested that some newer measures describing nonlinear dynamics of heart rate, such as fractal measures, may reaveal prognostic information beyond that obtained by the conventional measures of HRV. An ideal risk indicator could specifically predict sudden arrhythmic death as the implantable cardioverter-defibrillator (ICD) therapy can prevent such events. In postinfarction patients, numerically the highest number of sudden deaths occur in patients with better preserved left ventricular function than in those with severe left ventricular dysfunction. Recent data support the concept that HRV measurements, when analyzed several weeks after acute myocardial infarction, predict life-threatening ventricular tachyarrhythmias in patients with moderately depressed left ventricular function. However, well-designed prospective randomized studies are needed to evaluate whether the ICD therapy based on the assessment of HRV alone or with other risk indicators improves the patients´ prognosis. Several issues, such as the optimal target population, optimal timing of HRV measurements, optimal methods of HRV analysis and optimal cutpoints for different HRV parameters, need clarification before the HRV analysis can be a widespread clinical tool in risk stratification.http://journal.frontiersin.org/Journal/10.3389/fphys.2011.00081/fullHeart RateMortalityHeart rate variabilitysudden deathnonlinear methods |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Juha ePerkiömäki |
spellingShingle |
Juha ePerkiömäki Heart Rate Variability and Nonlinear Dynamics in Risk Stratification Frontiers in Physiology Heart Rate Mortality Heart rate variability sudden death nonlinear methods |
author_facet |
Juha ePerkiömäki |
author_sort |
Juha ePerkiömäki |
title |
Heart Rate Variability and Nonlinear Dynamics in Risk Stratification |
title_short |
Heart Rate Variability and Nonlinear Dynamics in Risk Stratification |
title_full |
Heart Rate Variability and Nonlinear Dynamics in Risk Stratification |
title_fullStr |
Heart Rate Variability and Nonlinear Dynamics in Risk Stratification |
title_full_unstemmed |
Heart Rate Variability and Nonlinear Dynamics in Risk Stratification |
title_sort |
heart rate variability and nonlinear dynamics in risk stratification |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Physiology |
issn |
1664-042X |
publishDate |
2011-11-01 |
description |
The time domain measures and power spectral analysis of heart rate variability (HRV) are classic conventional methods to assess the complex regulatory system between autonomic nervous system and heart rate and are most widely used. There are abundant scientific data about the prognostic significance of the conventional measurements of HRV in patients with various conditions, particularly with myocardial infarction. Some studies have suggested that some newer measures describing nonlinear dynamics of heart rate, such as fractal measures, may reaveal prognostic information beyond that obtained by the conventional measures of HRV. An ideal risk indicator could specifically predict sudden arrhythmic death as the implantable cardioverter-defibrillator (ICD) therapy can prevent such events. In postinfarction patients, numerically the highest number of sudden deaths occur in patients with better preserved left ventricular function than in those with severe left ventricular dysfunction. Recent data support the concept that HRV measurements, when analyzed several weeks after acute myocardial infarction, predict life-threatening ventricular tachyarrhythmias in patients with moderately depressed left ventricular function. However, well-designed prospective randomized studies are needed to evaluate whether the ICD therapy based on the assessment of HRV alone or with other risk indicators improves the patients´ prognosis. Several issues, such as the optimal target population, optimal timing of HRV measurements, optimal methods of HRV analysis and optimal cutpoints for different HRV parameters, need clarification before the HRV analysis can be a widespread clinical tool in risk stratification. |
topic |
Heart Rate Mortality Heart rate variability sudden death nonlinear methods |
url |
http://journal.frontiersin.org/Journal/10.3389/fphys.2011.00081/full |
work_keys_str_mv |
AT juhaeperkiomaki heartratevariabilityandnonlineardynamicsinriskstratification |
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