We computed 3 linear and 20 nonlinear HRV indexes on 24-h Holter recordings from 200 stable CHF patients (age 52 +/- 9 yrs, NYHA II-III, LVEF 24 +/- 6%) with the aim to assess i) the mutual interrelationships between these indexes and ii) their prognostic value towards cardiac death. We found high correlations between variables, with potential bias in fitting survival models. To overcome this problem a clustering procedure was used, obtaining 11 clusters. Cox analysis showed that seven clusters were significantly associated with the study outcome (p < 0.05) but, after adjustment for major clinical prognostic parameters, significance persisted only in 2 of them (both composed by nonlinear variables). Our results indicate that composite scores derived from nonlinear indices contain significant prognostic information independent of classical clinical predictors, highlighting the importance of non linear HRV parameters in prognostic stratification of CHF patients.
Linear and non-linear indices of heart rate variability in chronic heart failure: mutual interrelationships and prognostic value / R. Maestri, G.D. Pinna, P. Allegrini, R. Balocchi, A. Casaleggio, G. D'Addio, M. Ferrario, D. Menicucci, A. Porta, R. Sassi, M.G. Signorini, M.T. La Rovere, S. Cerutti - In: Computers in Cardiology, 2005[s.l] : IEEE, 2005. - ISBN 0780393376. - pp. 981-984 (( Intervento presentato al 32. convegno Annual Conference on Computers in Cardiology tenutosi a Lyon nel 2005 [10.1109/CIC.2005.1588273].
Linear and non-linear indices of heart rate variability in chronic heart failure: mutual interrelationships and prognostic value
A. Porta;R. Sassi;
2005
Abstract
We computed 3 linear and 20 nonlinear HRV indexes on 24-h Holter recordings from 200 stable CHF patients (age 52 +/- 9 yrs, NYHA II-III, LVEF 24 +/- 6%) with the aim to assess i) the mutual interrelationships between these indexes and ii) their prognostic value towards cardiac death. We found high correlations between variables, with potential bias in fitting survival models. To overcome this problem a clustering procedure was used, obtaining 11 clusters. Cox analysis showed that seven clusters were significantly associated with the study outcome (p < 0.05) but, after adjustment for major clinical prognostic parameters, significance persisted only in 2 of them (both composed by nonlinear variables). Our results indicate that composite scores derived from nonlinear indices contain significant prognostic information independent of classical clinical predictors, highlighting the importance of non linear HRV parameters in prognostic stratification of CHF patients.File | Dimensione | Formato | |
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