Literature DB >> 34307208

Application of a Diagnostic Methodology of Cardiac Systems Based on the Proportions of Entropy in Normal Patients and with Different Pathologies.

Javier Rodríguez1,2, Signed Prieto1,2, Elveny Laguado3, Frank Pernett4, Magda Villamizar3, Edinson Olivella5, Fredy Angarita6, Giovanni de la Cruz4, Carlos Morales4, Mónica Castro2.   

Abstract

INTRODUCTION: Dynamical systems theory, probability, and entropy were the substrate for the development of the diagnostic and predictive methodology of adult heart dynamics.
OBJECTIVE: To apply a previously developed methodology from dynamical systems, probability, and entropy in both normal and pathological subjects.
METHODS: Electrocardiographic records were selected from 30 healthy subjects and 200 with different pathologies, with a length of least 18 h. Numerical attractors from dynamical attractors and the probability of occurrence of ordered pairs of consecutive heart rates were built. A calculation of entropy and its proportions was performed and statistical analysis was conducted.
RESULTS: The normal patients' heart dynamics were evaluated according to the methodology of entropy proportions, highlighting that there are differences in normal patients with different pathologies. There was maximal level of sensitivity, specificity, and diagnostic agreement.
CONCLUSION: Proportional entropy constitutes a diagnostic and predictive method of heart systems, and may be useful as a tool to objectively diagnose and perform the follow-up of normal and pathological cases.
Copyright © 2021 by S. Karger AG, Basel.

Entities:  

Keywords:  Entropy; Heart dynamics; Heart rate; Holter; Nonlinear dynamics

Year:  2021        PMID: 34307208      PMCID: PMC8280414          DOI: 10.1159/000515699

Source DB:  PubMed          Journal:  Pulse (Basel)        ISSN: 2235-8668


  9 in total

1.  Fractal dynamics in physiology: alterations with disease and aging.

Authors:  Ary L Goldberger; Luis A N Amaral; Jeffrey M Hausdorff; Plamen Ch Ivanov; C-K Peng; H Eugene Stanley
Journal:  Proc Natl Acad Sci U S A       Date:  2002-02-19       Impact factor: 11.205

Review 2.  Fractal and complexity measures of heart rate variability.

Authors:  Juha S Perkiömäki; Timo H Mäkikallio; Heikki V Huikuri
Journal:  Clin Exp Hypertens       Date:  2005 Feb-Apr       Impact factor: 1.749

Review 3.  Methods derived from nonlinear dynamics for analysing heart rate variability.

Authors:  Andreas Voss; Steffen Schulz; Rico Schroeder; Mathias Baumert; Pere Caminal
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2009-01-28       Impact factor: 4.226

4.  Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction.

Authors:  H V Huikuri; T H Mäkikallio; C K Peng; A L Goldberger; U Hintze; M Møller
Journal:  Circulation       Date:  2000 Jan 4-11       Impact factor: 29.690

5.  Spectral analysis of heart rate variability predicts mortality and instability from vascular injury.

Authors:  Kiavash R Koko; Brian D McCauley; John P Gaughan; Marc W Fromer; Ryan S Nolan; Ashleigh L Hagaman; Spencer A Brown; Joshua P Hazelton
Journal:  J Surg Res       Date:  2017-12-22       Impact factor: 2.192

6.  Theoretical generalization of normal and sick coronary arteries with fractal dimensions and the arterial intrinsic mathematical harmony.

Authors:  Javier O Rodríguez; Signed E Prieto; Catalina Correa; Pedro A Bernal; Germán E Puerta; Sarith Vitery; Yolanda Soracipa; Diana Muñoz
Journal:  BMC Med Phys       Date:  2010-09-17

7.  Memory-induced nonlinear dynamics of excitation in cardiac diseases.

Authors:  Julian Landaw; Zhilin Qu
Journal:  Phys Rev E       Date:  2018-04       Impact factor: 2.529

Review 8.  The fractal heart - embracing mathematics in the cardiology clinic.

Authors:  Gabriella Captur; Audrey L Karperien; Alun D Hughes; Darrel P Francis; James C Moon
Journal:  Nat Rev Cardiol       Date:  2016-10-06       Impact factor: 32.419

9.  Heart rate variability as predictor of mortality in sepsis: A prospective cohort study.

Authors:  Fábio M de Castilho; Antonio Luiz P Ribeiro; José Luiz P da Silva; Vandack Nobre; Marcos R de Sousa
Journal:  PLoS One       Date:  2017-06-27       Impact factor: 3.240

  9 in total

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