Document Detail


Heart rate variability analysis based on time-frequency representation and entropies in hypertrophic cardiomyopathy patients.
MedLine Citation:
PMID:  18367814     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In hypertrophic cardiomyopathy (HCM) patients there is an increased risk of premature death, which can occur with little or no warning. Furthermore, classification for sudden cardiac death on patients with HCM is very difficult. The aim of our study was to improve the prognostic value of heart rate variability (HRV) in HCM patients, giving insight into changes of the autonomic nervous system. In this way, the suitability of linear and nonlinear measures was studied to assess the HRV. These measures were based on time-frequency representation (TFR) and on Shannon and Rényi entropies, and compared with traditional HRV measures. Holter recordings of 64 patients with HCM and 55 healthy subjects were analyzed. The HCM patients consisted of two groups: 13 high risk patients, after aborted sudden cardiac death (SCD); 51 low risk patients, without SCD. Five-hour RR signals, corresponding to the sleep period of the subjects, were considered for the analysis as a comparable standard situation. These RR signals were filtered in the three frequency bands: very low frequency band (VLF, 0-0.04 Hz), low frequency band (LF, 0.04-0.15 Hz) and high frequency band (HF, 0.15-0.45 Hz). TFR variables based on instantaneous frequency and energy functions were able to classify HCM patients and healthy subjects (control group). Results revealed that measures obtained from TFR analysis of the HRV better classified the groups of subjects than traditional HRV parameters. However, results showed that nonlinear measures improved group classification. It was observed that entropies calculated in the HF band showed the highest statistically significant levels comparing the HCM group and the control group, p-value < 0.0005. The values of entropy measures calculated in the HCM group presented lower values, indicating a decreasing of complexity, than those calculated from the control group. Moreover, similar behavior was observed comparing high and low risk of premature death, the values of the entropy being lower in high risk patients, p-value < 0.05, indicating an increase of predictability. Furthermore, measures from information entropy, but not from TFR, seem to be useful for enhanced risk stratification in HCM patients with an increased risk of sudden cardiac death.
Authors:
F Clariá; M Vallverdú; R Baranowski; L Chojnowska; P Caminal
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-03-07
Journal Detail:
Title:  Physiological measurement     Volume:  29     ISSN:  0967-3334     ISO Abbreviation:  Physiol Meas     Publication Date:  2008 Mar 
Date Detail:
Created Date:  2008-03-27     Completed Date:  2008-06-23     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9306921     Medline TA:  Physiol Meas     Country:  England    
Other Details:
Languages:  eng     Pagination:  401-16     Citation Subset:  IM    
Affiliation:
Department ESAII, Centre for Biomedical Engineering Research, Technical University of Catalonia, Barcelona, Spain.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Autonomic Nervous System / physiology
Cardiomyopathy, Hypertrophic / physiopathology*
Electrocardiography
Energy Metabolism
Entropy
Fourier Analysis
Heart Rate / physiology*
Humans
Linear Models
Nonlinear Dynamics
Prognosis

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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