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Clinical correlates of non-linear indices of heart rate variability in chronic heart failure patients

  • Roberto Maestri , Gian Domenico Pinna , Rita Balocchi , Gianni D'Addio , Manuela Ferrario , Alberto Porta , Roberto Sassi , Maria Gabriella Signorini and Maria Teresa La Rovere
Published/Copyright: October 25, 2006
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Biomedical Engineering / Biomedizinische Technik
From the journal Volume 51 Issue 4

Abstract

We assessed the clinical correlates of a comprehensive set of non-linear heart rate variability (HRV) indices computed from 24-h Holter recordings for 200 stable chronic heart failure (CHF) patients [median age (lower quartile, upper quartile) 54 (47, 58) years, LVEF 23% (19%, 28%)]. A total of 19 non-linear indices belonging to six major families, namely symbolic dynamics, entropy, empirical mode decomposition, fractality-multifractality, unpredictability and Poincaré plots, were considered. Most indices showed a significant association with ejection fraction and with the severity of symptoms, while only two (one each from the fractality and Poincaré plot families) showed an association with aetiology. Only one symbolic dynamics variable was associated with the presence of non-sustained ventricular tachycardia and two symbolic dynamics variables were associated with the rate of ventricular ectopic events. Our results demonstrate the existence of selective links between non-linear indexes of HRV and the clinical status and functional impairment of CHF patients. This indicates that further studies should be designed to investigate the physiopathological mechanisms involved in such links.


Corresponding author: Roberto Maestri, Servizio di Bioingegneria, Fondazione S. Maugeri, IRCCS, Istituto Scientifico di Montescano, 27040 Montescano (PV), Italy Phone: +39-0385-247277 Fax: +39-0385-61386

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Published Online: 2006-10-25
Published in Print: 2006-10-01

©2006 by Walter de Gruyter Berlin New York

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  26. Frequency modulation between low- and high-frequency components of the heart rate variability spectrum
  27. Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability series
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