Clinical application of a cardiac diagnosis method based on dynamic systems theory

Abstract

Background: A new methodology based on dynamical systems theory has been developed to differentiate normal cardiac dynamic from acuteillness by calculating the space occupation of chaotic geometric attractors in the phase space. Objective: The pur pose of t his s tud y was to a pplythis methodology to confirm its clinical applicability and the relation between the measures and the appearance of arrhythmic electrical storms.Methodology: There were analyzed 200 holters. The minimum and maximal heart rate and the number of beats per hour were selected. Then,a simulation for constructing the attractor of each cardiac dynamic in the phase space was made. Fractal dimension and space occupation of theattractors with the two grids were calculated according to the box-counting method and the differentiating parameters of normality and acutedisease were applied. Sensibility, specificity and kappa coefficient were calculated for evaluating diagnostic concordance. Fractal dimension fo r n orm al hol te rs w as bet we en 1 ,6 21 a nd 1,9 70 and be tween 1,268 and 1,784 for holters with arrhythmic electrical stor m. It w as not po ssi bl eto identify differences between groups with mathematical values of fr a ct al d im e ns io n . Results: Ho we v er , s p ac e o c cu p at io n of n or ma l dy n am ic attractors was always greater than 200 with the 5 beats minG1 grid and space occupation of cases with arrhythmia was between 31 and 60,close to space occupation of cases with acute myocardial infarction, which was between 19 and 23. Conclusion: This study confirmed the clinicalapplicability of the methodology. It detects when a cardiac dynamic exhibits a progressive diminution of spatial occupation, which is useful todistinguish the cases with arrhythmic electrical storm from cases with chronic arrhythmias or normal dynamic. These findings could be useful topredict appearance of arrhythmic electrical storms.