title: Nonlinear indices of heart rate variability in chronic heart failure patients: redundancy and comparative clinical value.
abstract: OBJECTIVE
  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.
  
  
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Dipartimento di Bioingegneria, Fondazione S. Maugeri, IRCCS, Montescano and Telese, Italy. rmaestri@fsm.it
authors.forename: Roberto
authors.initials: R
authors.lastname: Maestri
authors.forename: Gian Domenico
authors.initials: GD
authors.lastname: Pinna
authors.forename: Agostino
authors.initials: A
authors.lastname: Accardo
authors.forename: Paolo
authors.initials: P
authors.lastname: Allegrini
authors.forename: Rita
authors.initials: R
authors.lastname: Balocchi
authors.forename: Gianni
authors.initials: G
authors.lastname: D'Addio
authors.forename: Manuela
authors.initials: M
authors.lastname: Ferrario
authors.forename: Danilo
authors.initials: D
authors.lastname: Menicucci
authors.forename: Alberto
authors.initials: A
authors.lastname: Porta
authors.forename: Roberto
authors.initials: R
authors.lastname: Sassi
authors.forename: Maria Gabriella
authors.initials: MG
authors.lastname: Signorini
authors.forename: Maria Teresa
authors.initials: MT
authors.lastname: La Rovere
authors.forename: Sergio
authors.initials: S
authors.lastname: Cerutti
mesh_terms: D019540:Area Under Curve; D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000209:etiology*; D002908:Chronic Disease; D016000:Cluster Analysis; D015716:Electrocardiography, Ambulatory; D005260:Female; D006333:Heart Failure / Q000150:complications* / Q000175:diagnosis*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models