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ISSN 1561-3011 (Electronic)

2017, Number 4

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Rev Cubana Invest Bioméd 2017; 36 (4)

Mathematical diagnosis of cardiac dynamics in 16 hours and evaluation of hemodynamic variables in the Intensive Care Unit

Rodríguez VJO, Prieto BSE, Correa HSC, Soracipa MMY, Oliveros RH

Language: Spanish
References: 42
Page: 1-15
PDF size: 164.47 Kb.


ABSTRACT

Introduction: from dynamic systems, diagnosis of cardiac dynamics applicable to clinic in 16 hours was developed, useful for patient's intensive care unit.
Objectives: to confirm the diagnostic ability of the new assessment methodology of cardiac dynamics in 16 hours and determine the evolution of the arterial and venous pressure of oxygen and carbon dioxide.
Methods: 50 dynamic were taken, 10 normal and 40 with acute pathologies, taking the minimum and maximum heart rate, and number of beats per minute. Attractors were constructed and areas of occupation and the fractal dimension in 21 and 16 hours were evaluated, comparing both physical and mathematical diagnosis each other. Subsequently a confirmation of the diagnosis made in 16 hours by a blinded study compared to conventional diagnosis. Additionally, values of the arterial and venous pressure of oxygen and carbon dioxide from 7 Intensive Care Unit patients were taken and chaotic attractors were constructed to evaluate the minimum and maximum values of the attractor on the delay map.
Results: the diagnostic capability of the methodology in 16 hours for cardiac dynamic was confirmed, with sensitivity and specificity of 100% and kappa coefficient 1 over conventional diagnosis; the minimum and maximum values of the arterial and venous pressure of oxygen and carbon dioxide were found between 29.60 and 194.40; 24.20 and 56.10; 16,40 and 65,60 and 21,40 and 97,90 respectively.
Conclusions: diagnostic predictions were confirmed in 16 hours differentiating normal, chronic and acute disease useful for clinical monitoring in Intensive Care Unit patients. The variables behaved chaotically; these results may inform clinical applications and predictions of mortality.


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