Nonlinear indices of heart rate variability in chronic heart failure patients: Redundancy and comparative clinical value (662 views)
J Cardiovasc Electrophysiol (ISSN: 1045-3873), 2007; 18(4): 425-433.
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Paper type: Journal Article,
Impact factor: 3.475, 5-year impact factor: 3.246
Url: http://www.scopus.com/inward/record.url?eid=2-s2.0-33947200734&partnerID=40&md5=261747e80bef289c3a2acc224887b028
Keywords: Chronic Heart Failure, Heart Rate Variability, Nonlinear Dynamics, Prognosis, Amiodarone, Beta Adrenergic Receptor Blocking Agent, Digoxin, Dipeptidyl Carboxypeptidase Inhibitor, Diuretic Agent, Nitrate, Adult, Article, Cardiovascular Risk, Cluster Analysis, Diagnostic Value, Disease Classification, Entropy, Female, Heart Death, Heart Transplantation, Holter Monitoring, Human, Major Clinical Study, Medical Assessment, Prediction, Priority Journal, Proportional Hazards Model, Risk Assessment, Risk Factor, Sample Size, Sinus Rhythm, Survival Rate, Survival Time, Area Under Curve, Arrhythmia, Chronic Disease, Electrocardiography, Ambulatory, Congestive, Middle Aged, Theoretical, Multivariate Analysis, Predictive Value Of Tests,
Affiliations:
*** IBB - CNR ***
Dipartimento di Bioingegneria, Fondazione S. Maugeri, IRCCS, Montescano, Italy
Dipartimento di Elettronica e Informatica, Università di Trieste, Italy
Dipartimento di Fisica, Università di Pisa, Italy
Istituto di Fisiologia Clinica, CNR, Pisa, Italy
Dipartimento Scienze Precliniche, LITA Vialba, Università degli Studi di Milano, Italy
Dipartimento di Tecnologie dell'Informazione, Università degli Studi di Milano, Italy
Dipartimento di Cardiologia, Fondazione S. Maugeri, IRCCS, Montescano, Italy
Servizio di Bioingegneria, Fondazione S. Maugeri, IRCCS Istituto Scientifico di Montescano, 27040 Montescano (PV), Italy
References:
Not available.
J Cardiovasc Electrophysiol (ISSN: 1045-3873), 2007; 18(4): 425-433.
Export to BibTeX Export to EndNote
Paper type: Journal Article,
Impact factor: 3.475, 5-year impact factor: 3.246
Url: http://www.scopus.com/inward/record.url?eid=2-s2.0-33947200734&partnerID=40&md5=261747e80bef289c3a2acc224887b028
Keywords: Chronic Heart Failure, Heart Rate Variability, Nonlinear Dynamics, Prognosis, Amiodarone, Beta Adrenergic Receptor Blocking Agent, Digoxin, Dipeptidyl Carboxypeptidase Inhibitor, Diuretic Agent, Nitrate, Adult, Article, Cardiovascular Risk, Cluster Analysis, Diagnostic Value, Disease Classification, Entropy, Female, Heart Death, Heart Transplantation, Holter Monitoring, Human, Major Clinical Study, Medical Assessment, Prediction, Priority Journal, Proportional Hazards Model, Risk Assessment, Risk Factor, Sample Size, Sinus Rhythm, Survival Rate, Survival Time, Area Under Curve, Arrhythmia, Chronic Disease, Electrocardiography, Ambulatory, Congestive, Middle Aged, Theoretical, Multivariate Analysis, Predictive Value Of Tests,
Affiliations:
*** IBB - CNR ***
Dipartimento di Bioingegneria, Fondazione S. Maugeri, IRCCS, Montescano, Italy
Dipartimento di Elettronica e Informatica, Università di Trieste, Italy
Dipartimento di Fisica, Università di Pisa, Italy
Istituto di Fisiologia Clinica, CNR, Pisa, Italy
Dipartimento Scienze Precliniche, LITA Vialba, Università degli Studi di Milano, Italy
Dipartimento di Tecnologie dell'Informazione, Università degli Studi di Milano, Italy
Dipartimento di Cardiologia, Fondazione S. Maugeri, IRCCS, Montescano, Italy
Servizio di Bioingegneria, Fondazione S. Maugeri, IRCCS Istituto Scientifico di Montescano, 27040 Montescano (PV), Italy
References:
Not available.
Nonlinear indices of heart rate variability in chronic heart failure patients: Redundancy and comparative clinical value
Nonlinear Heart Rate Variability in Heart Failure. Aims: We aimed to assess the mutual interrelationships and to compare the prognostic value of a comprehensive set of nonlinear indices of heart rate variability (HRV) in a population of chronic heart failure (CHF) patients. Methods and Results: Twenty nonlinear HRV indices, representative of symbolic dynamics, entropy, fractality-multifractality, predictability, empirical mode decomposition, and Poincaré plot families, were computed from 24-hour Holter recordings in 200 stable CHF patients in sinus rhythm (median age [interquartile range]: 54 [47-58] years, LVEF: 23 [19-28] %, NYHA class II-III: 88%). End point for survival analysis (Cox model) was cardiac death or urgent transplantation. Homogeneous variables were grouped by cluster analysis, and in each cluster redundant variables were discarded. A prognostic model including only known clinical and functional risk factors was built and the ability of each selected HRV variable to add prognostic information to this model assessed. Bootstrap resampling was used to test the models stability. Four nonlinear variables showed a correlation >0.90 with classical linear ones and were discarded. Correlations >0.80 were found between several nonlinear variables. Twelve clusters were obtained and from each cluster a candidate predictor was selected. Only two variables (from empirical mode decomposition and symbolic dynamics families) added prognostic information to the clinical model. Conclusion: This exploratory study provides evidence that, despite some redundancies in the informative content of nonlinear indices and strong differences in their prognostic power, quantification of nonlinear properties of HRV provides independent information in risk stratification of CHF patients. © 2007 by Futura Publishing Company, Inc.
Nonlinear Heart Rate Variability in Heart Failure. Aims: We aimed to assess the mutual interrelationships and to compare the prognostic value of a comprehensive set of nonlinear indices of heart rate variability (HRV) in a population of chronic heart failure (CHF) patients. Methods and Results: Twenty nonlinear HRV indices, representative of symbolic dynamics, entropy, fractality-multifractality, predictability, empirical mode decomposition, and Poincaré plot families, were computed from 24-hour Holter recordings in 200 stable CHF patients in sinus rhythm (median age [interquartile range]: 54 [47-58] years, LVEF: 23 [19-28] %, NYHA class II-III: 88%). End point for survival analysis (Cox model) was cardiac death or urgent transplantation. Homogeneous variables were grouped by cluster analysis, and in each cluster redundant variables were discarded. A prognostic model including only known clinical and functional risk factors was built and the ability of each selected HRV variable to add prognostic information to this model assessed. Bootstrap resampling was used to test the models stability. Four nonlinear variables showed a correlation >0.90 with classical linear ones and were discarded. Correlations >0.80 were found between several nonlinear variables. Twelve clusters were obtained and from each cluster a candidate predictor was selected. Only two variables (from empirical mode decomposition and symbolic dynamics families) added prognostic information to the clinical model. Conclusion: This exploratory study provides evidence that, despite some redundancies in the informative content of nonlinear indices and strong differences in their prognostic power, quantification of nonlinear properties of HRV provides independent information in risk stratification of CHF patients. © 2007 by Futura Publishing Company, Inc.
Nonlinear indices of heart rate variability in chronic heart failure patients: Redundancy and comparative clinical value
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Nonlinear indices of heart rate variability in chronic heart failure patients: Redundancy and comparative clinical value
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Impact Factor: 0.023
View Export to BibTeX Export to EndNote
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Impact Factor: 4.575
View Export to BibTeX Export to EndNote
Marotta T, Ferrara LA, Di Marino L, Mancini M, Annuzzi G, Russo O, D'Orta G, Lucarelli C, Rossi F
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Impact Factor: 1.681
View Export to BibTeX Export to EndNote
Morisco C, Nappi A, Argenziano L, Sarno D, Fonatana D, Imbriaco M, Nicolai E, Romano M, Rosiello G, Cuocolo A
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Impact Factor: 2
View Export to BibTeX Export to EndNote
16 Records (15 excluding Abstracts).
Total impact factor: 58.119 (56.119 excluding Abstracts).
Total 5 year impact factor: 73.354 (62.808 excluding Abstracts).
Total impact factor: 58.119 (56.119 excluding Abstracts).
Total 5 year impact factor: 73.354 (62.808 excluding Abstracts).
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