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

Abstract

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.

Nonlinear additive autoregressive model-based analysis of short-term heart rate variability

“…HRV measurements have proven to be independent predictors of sudden cardiac death after acute myocardial infarction, chronic heart failure or dilated cardiomyopathy [17,21,27,33,34,38]. Moreover, it has been shown that shortterm HRV analysis already has an independent prognostic value in risk stratification apart from that of clinical and functional variables [23].…”

Ventricular arrhythmias and changes in heart rate preceding ventricular tachycardia in patients with an implantable cardioverter defibrillator

“…In addition to their primary clinical role to reduce the incidence of sudden cardiac death, data that were recorded in ICDs and subsequently downloaded have also been used to analyze the conditions that precede the onset of VT and VF [5, 8-11, 20, 25, 28, 30, 31, 34, 37, 39, 43, 46]. The data derived from ICDs complement data from other sources that have analyzed heart rate variability (HRV) [8,17,19,28,36,48,49,51], premature ventricular complexes (PVCs) [1,4,7,15,26,40,41,44], and T-wave alternans [18,23,35,38] in assessment of factors that lead to the initiation of ventricular tachycardia and confer an increased risk for sudden cardiac death. Many factors including increased heart rate [16,19,20,24,27,31,34], reduced HRV [11,17,19,22,28,30,31,36,43,45,48,49], increased incidence of PVCs [4,7,16,40,44], and T-wave alterna...…”

A Research on Maximum Symbolic Entropy from Intrinsic Mode Function and Its Application in Fault Diagnosis

“…Considering the later one takes account of the relationship between neighboring points, hence it is more conducive to find property of signals. In the symbolizing process, the range between the maximum and minimum values was divided into 2 or 4 intervals [23][24][25].…”