Literature DB >> 17670859

Fractal scale-invariant and nonlinear properties of cardiac dynamics remain stable with advanced age: a new mechanistic picture of cardiac control in healthy elderly.

Daniel T Schmitt1, Plamen Ch Ivanov.   

Abstract

Heart beat fluctuations exhibit temporal structure with robust long-range correlations, fractal and nonlinear features, which have been found to break down with pathologic conditions, reflecting changes in the mechanism of neuroautonomic control. It has been hypothesized that these features change and even break down also with advanced age, suggesting fundamental alterations in cardiac control with aging. Here we test this hypothesis. We analyze heart beat interval recordings from the following two independent databases: 1) 19 healthy young (average age 25.7 yr) and 16 healthy elderly subjects (average age 73.8 yr) during 2 h under resting conditions from the Fantasia database; and 2) 29 healthy elderly subjects (average age 75.9 yr) during approximately 8 h of sleep from the sleep heart health study (SHHS) database, and the same subjects recorded 5 yr later. We quantify: 1) the average heart rate (<R-R>); 2) the SD sigma(R-R) and sigma(DeltaR-R) of the heart beat intervals R-R and their increments DeltaR-R; 3) the long-range correlations in R-R as measured by the scaling exponent alpha(R-R) using the Detrended Fluctuation Analysis; 4) fractal linear and nonlinear properties as represented by the scaling exponents alpha(sgn) and alpha(mag) for the time series of the sign and magnitude of DeltaR-R; and 5) the nonlinear fractal dimension D(k) of R-R using the fractal dimension analysis. We find: 1) No significant difference in (P > 0.05); 2) a significant difference in sigma(R-R) and sigma(DeltaR-R) for the Fantasia groups (P < 10(-4)) but no significant change with age between the elderly SHHS groups (P > 0.5); and 3) no significant change in the fractal measures alpha(R-R) (P > 0.15), alpha(sgn) (P > 0.2), alpha(mag) (P > 0.3), and D(k) with age. Our findings do not support the hypothesis that fractal linear and nonlinear characteristics of heart beat dynamics break down with advanced age in healthy subjects. Although our results indeed show a reduced SD of heart beat fluctuations with advanced age, the inherent temporal fractal and nonlinear organization of these fluctuations remains stable. This indicates that the coupled cascade of nonlinear feedback loops, which are believed to underlie cardiac neuroautonomic regulation, remains intact with advanced age.

Mesh:

Year:  2007        PMID: 17670859     DOI: 10.1152/ajpregu.00372.2007

Source DB:  PubMed          Journal:  Am J Physiol Regul Integr Comp Physiol        ISSN: 0363-6119            Impact factor:   3.619


  29 in total

1.  Phase transitions in physiologic coupling.

Authors:  Ronny P Bartsch; Aicko Y Schumann; Jan W Kantelhardt; Thomas Penzel; Plamen Ch Ivanov
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-12       Impact factor: 11.205

2.  Effect of extreme data loss on long-range correlated and anticorrelated signals quantified by detrended fluctuation analysis.

Authors:  Qianli D Y Ma; Ronny P Bartsch; Pedro Bernaola-Galván; Mitsuru Yoneyama; Plamen Ch Ivanov
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2010-03-02

3.  Development of the National Healthy Sleep Awareness Project Sleep Health Surveillance Questions.

Authors:  Timothy I Morgenthaler; Janet B Croft; Leslie C Dort; Lauren D Loeding; Janet M Mullington; Sherene M Thomas
Journal:  J Clin Sleep Med       Date:  2015-09-15       Impact factor: 4.062

4.  Applying fractal analysis to short sets of heart rate variability data.

Authors:  M A Peña; J C Echeverría; M T García; R González-Camarena
Journal:  Med Biol Eng Comput       Date:  2009-01-29       Impact factor: 2.602

5.  Entropy measures, entropy estimators, and their performance in quantifying complex dynamics: Effects of artifacts, nonstationarity, and long-range correlations.

Authors:  Wanting Xiong; Luca Faes; Plamen Ch Ivanov
Journal:  Phys Rev E       Date:  2017-06-12       Impact factor: 2.529

6.  Assessing the complexity of short-term heartbeat interval series by distribution entropy.

Authors:  Peng Li; Chengyu Liu; Ke Li; Dingchang Zheng; Changchun Liu; Yinglong Hou
Journal:  Med Biol Eng Comput       Date:  2014-10-29       Impact factor: 2.602

7.  Heart rate dynamics during acute pain in newborns.

Authors:  Amir Weissman; Etan Z Zimmer; Michal Aranovitch; Shraga Blazer
Journal:  Pflugers Arch       Date:  2012-10-09       Impact factor: 3.657

8.  Aging effects on cardiac and respiratory dynamics in healthy subjects across sleep stages.

Authors:  Aicko Y Schumann; Ronny P Bartsch; Thomas Penzel; Plamen Ch Ivanov; Jan W Kantelhardt
Journal:  Sleep       Date:  2010-07       Impact factor: 5.849

9.  Stratification pattern of static and scale-invariant dynamic measures of heartbeat fluctuations across sleep stages in young and elderly.

Authors:  Daniel T Schmitt; Phyllis K Stein; Plamen Ch Ivanov
Journal:  IEEE Trans Biomed Eng       Date:  2009-02-06       Impact factor: 4.538

10.  Cardiovascular assessment of supportive doctor-patient communication using multi-scale and multi-lag analysis of heartbeat dynamics.

Authors:  M Nardelli; A Greco; O P Danzi; C Perlini; F Tedeschi; E P Scilingo; L Del Piccolo; G Valenza
Journal:  Med Biol Eng Comput       Date:  2018-07-14       Impact factor: 2.602

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