Clinical Application of a Cardiac Diagnostic Method Based on Dynamic Systems Theory

Background: A new methodology based on dynamical systems theory has been developed to differentiate normal cardiac dynamic from acute
illness by calculating the space occupation of chaotic geometric attractors in the phase space. Objective: The purpose of this study was to apply
this 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 the
attractors with the two grids were calculated according to the box-counting method and the differentiating parameters of normality and acute
disease were applied. Sensibility, specificity and kappa coefficient were calculated for evaluating diagnostic concordance. Fractal dimension
for normal holters was between 1,621 and 1,970 and between 1,268 and 1,784 for holters with arrhythmic electrical storm. It was not possible
to identify differences between groups with mathematical values of fractal dimension. Results: However, space occupation of normal dynamic
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 clinical
applicability of the methodology. It detects when a cardiac dynamic exhibits a progressive diminution of spatial occupation, which is useful to
distinguish the cases with arrhythmic electrical storm from cases with chronic arrhythmias or normal dynamic. These findings could be useful to
predict appearance of arrhythmic electrical storms