Document Detail


Compression entropy contributes to risk stratification in patients with cardiomyopathy.
MedLine Citation:
PMID:  16915769     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Sudden cardiac death (SCD) is a leading cause of mortality with an incidence of 3 million cases per year worldwide. Therapies for patients who have survived an SCD episode or have a high risk of developing lethal ventricular arrhythmia are well established and depend mainly on risk stratification. In this study we investigated the suitability of the non-linear measure compression entropy (Hc) for improved risk prediction in cardiac patients. We recorded 24-h Holter ECG for 300 patients with congestive heart failure (CHF). During a mean follow-up period of 12 months, 32 patients died due to a cardiac event. Hc depends on the compression parameters window length w and buffer length b, which were optimised by analysing a subgroup of patients. Compression entropies based on the beat-to-beat interval (BBI) were subsequently calculated and compared with standard heartrate variability parameters. Statistical analysis revealed significant differences between high- and low-risk CHF patients in standard HRV measures, as well as compression entropy based on the BBI (cardiac death, p = 0.005; SCD, p = 0.02). In conclusion, the implementation of non-linear compression entropy analysis in multivariate analysis seems to be useful for enhanced risk stratification of cardiac death, especially SCD, in ischaemic cardiomyopathy patients.
Authors:
Sandra Truebner; Iwona Cygankiewicz; Rico Schroeder; Mathias Baumert; Montserrat Vallverdú; Pere Caminal; Rafael Vazquez; Antoni Bayés de Luna; Andreas Voss
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Biomedizinische Technik. Biomedical engineering     Volume:  51     ISSN:  0013-5585     ISO Abbreviation:  Biomed Tech (Berl)     Publication Date:  2006 Jul 
Date Detail:
Created Date:  2006-08-18     Completed Date:  2006-09-12     Revised Date:  2010-11-05    
Medline Journal Info:
Nlm Unique ID:  1262533     Medline TA:  Biomed Tech (Berl)     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  77-82     Citation Subset:  IM    
Affiliation:
Department of Medical Engineering, University of Applied Sciences Jena, Jena, Germany.
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MeSH Terms
Descriptor/Qualifier:
Aged
Algorithms
Arrhythmias, Cardiac / diagnosis*,  mortality*
Cardiomyopathies / diagnosis*,  mortality*
Comorbidity
Death, Sudden, Cardiac / epidemiology
Diagnosis, Computer-Assisted / methods*
Electrocardiography, Ambulatory / statistics & numerical data*
Entropy
Heart Rate
Humans
Incidence
Middle Aged
Multivariate Analysis
Nonlinear Dynamics
Reproducibility of Results
Risk Assessment / methods*
Risk Factors
Sensitivity and Specificity
Spain / epidemiology

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


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