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Evaluation of renormalised entropy for risk stratification using heart rate variability data

  • Standard time and frequency parameters of heart rate variability (HRV) describe only linear and periodic behaviour, whereas more complex relationships cannot be recognised. A method that may be capable of assessing more complex properties is the non-linear measure of 'renormalised entropy.' A new concept of the method, RE(AR), has been developed, based on a non-linear renormalisation of autoregressive spectral distributions. To test the hypothesis that renormalised entropy may improve the result of high-risk stratification after myocardial infarction, it is applied to a clinical pilot study (41 subjects) and to prospective data of the St George's Hospital post- infarction database (572 patients). The study shows that the new RE(AR) method is more reproducible and more stable in time than a previously introduced method (p<0.001). Moreover, the results of the study confirm the hypothesis that on average, the survivors have negative values of RE(AR) (-0.11+/-0.18), whereas the non-survivors have positive values (0.03+/-0.22, p<0.01).Standard time and frequency parameters of heart rate variability (HRV) describe only linear and periodic behaviour, whereas more complex relationships cannot be recognised. A method that may be capable of assessing more complex properties is the non-linear measure of 'renormalised entropy.' A new concept of the method, RE(AR), has been developed, based on a non-linear renormalisation of autoregressive spectral distributions. To test the hypothesis that renormalised entropy may improve the result of high-risk stratification after myocardial infarction, it is applied to a clinical pilot study (41 subjects) and to prospective data of the St George's Hospital post- infarction database (572 patients). The study shows that the new RE(AR) method is more reproducible and more stable in time than a previously introduced method (p<0.001). Moreover, the results of the study confirm the hypothesis that on average, the survivors have negative values of RE(AR) (-0.11+/-0.18), whereas the non-survivors have positive values (0.03+/-0.22, p<0.01). Further, the study shows that the combination of an HRV triangular index and RE(AR) leads to a better prediction of sudden arrhythmic death than standard measurements of HRV. In summary, the new RE(AR) method is an independent measure in HRV analysis that may be suitable for risk stratification in patients after myocardial infarction.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Niels WesselORCiDGND, Andreas Voss, Jürgen KurthsORCiDGND, Alexander Schirdewan, Katarina Hnatkova, Marek Malik
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Erstveröffentlichung:2000
Erscheinungsjahr:2000
Datum der Freischaltung:24.03.2017
Quelle:Medical & Biological Engeneering & Computing. - 38 (2000), 6, S. 680 - 685
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
Name der Einrichtung zum Zeitpunkt der Publikation:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik
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