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

Standard time and frequency parameters of heart rate variability (HRV) desc ribe only linear and periodic behaviour, whereas more complex relationships cannot be recognised. A method that may be capable of assessing more compl ex properties is the non-linear measure of 'renormalised entropy.' A new co ncept of the method, REAR, has been developed, based on a non-linear renorm alisation of autoregressive spectral distributions. To test the hypothesis that renormalised entropy may improve the result of high-risk stratificatio n after myocardial infarction, it is applied to a clinical pilot study (41 subjects) and to prospective data of the St George's Hospital post-infarcti on database (572 patients). The study shows that the new REAR method is mor e 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 REAR (-0.11 +/- 0.18), w hereas the non-survivors have positive values (0.03 +/- 0.22, p < 0.01). Fu rther, the study shows that the combination of an HRV triangular index and REAR leads to a better prediction of sudden arrhythmic death than standard measurements of HRV. In summary, the new REAR method is an independent meas ure in HRV analysis that may be suitable for risk stratification in patient s after myocardial infarction.