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Revista Colombiana de Cardiología
versão impressa ISSN 0120-5633
Resumo
RODRIGUEZ, Javier et al. Dynamic systems and probability theory applied to the diagnosis of cardiac dynamics in 16 hours. Rev. Colomb. Cardiol. [online]. 2020, vol.27, n.1, pp.29-35. ISSN 0120-5633. https://doi.org/10.1016/j.rccar.2019.04.008.
Introduction:
Quantitative diagnostics of cardiac systems have been established using theories such as, dynamic systems, fractal geometry, and probability theory.
Objective:
To evaluate cardiac dynamics using a methodology based on probability theory and dynamic systems in sixteen hours.
Methods:
Using a total of 80 cardiac dynamic electrocardiograph traces (10 normal and 70 with disease), a record was made of the maximum and minimum heart rate values, as well as the number of heart beats/hour during each hour. These values were used to construct the attractor. The fractal dimension was then calculated using the “box counting” method, the spatial occupation, and the probability of spatial occupation by the attractor. The mathematic diagnosis was determined, and a statistical validation was made as regards the conventional diagnosis, which was taken as the reference standard.
Results:
It was shown that the probability of spatial occupation of the pathological attractor dynamics was between 0.29 and 0.144, and for dynamics in the normal state it was between 0.164 and 0.329. The sensitivity, specificity, positive and negative predictive values were 100%, and the kappa coefficient was 1.
Conclusions:
The diagnostic and predictive capacity of the methodology to differentiate normal from disease states at clinical level was demonstrated.
Palavras-chave : Heart rate; Dynamic systems; Fractals; Probability; Diagnosis; Cardiac dynamics.