A novel heart rate attractor for the prediction of cardiovascular disease

Abstract

Abstract Rationale The cardiac dynamic has been studied with a new methodology based on probability and proportions of entropy of frequencies of appearance, by means of heart rate (HR) in a new kind of attractor. This methodology has established numerical predictions of cardiac dynamics, including for patients from the coronary care unit. Objective To validate a novel method with heart rate attractor in the prediction of cardiovascular disease, applied at the coronary care unit. Methods and results An application of this methodology in a blind study with 800 Holter registries was done. With the maximum and minimum values of HR, and the number of heartbeats for each hour, a numerical attractor was built for each Holter monitor. Occurrence probabilities of HR ordered pairs were calculated as well as the Boltzmann Gibb's entropy. The S/k value and entropy proportions were found, quantifying the dynamic state. Finally, the mathematical evaluation was compared with the gold standard by means of sensitivity, specificity and Kappa coefficient. The proportion's values were within the expected ranges, both normal and pathological Holter registries, and the diagnostic concordance measurements showed the maximum possible values; the sensitivity and specificity were 100% and the Kappa coefficient was 1. Conclusions The diagnostic capacity of the methodology was confirmed with 800 Holter registries, showing that this methodology quantitatively differentiates normality, illness and evolution between both states, which enables quicker assessments to be made.