Dynamical Landscape of Heart Rhythm in Discerning Erratic Rhythm in Elderly People

We hypothesize that increase with age of short-term measures of heart rhythm [a way in which accelerations and decelerations appear], especially dynamical pattern indices [Transition Rates (ST) or self-Transfer Entropy (sTE)], provide indicates for unhealthy autonomic activity or cardiac tissue remodeling in elderly people. Hence they can help in early recognition of arrhythmogenesis processes. Based on properties of heart rhythm of 190 healthy persons, grouped into their age decade, we have found that both ST and sTE are efficient separators for discerning elderly people with erratic rhythm. The values in minimum in ST = 2.4 and minimum in sTE = 0.27, obtained by square function approximation, have been used to divide subjects of 70s and 80s into two groups. For all entropic measures these groups are different (p < 0.001, in t-test or Man-Whitney in case normality test failed). The fragmentation metrics [based on statistics of signs of heart rate changes] PPP and PAS also distingushed these groups though at greater p- value, and PSS yielded that the groups are identical. The minima of these function did not give satisfactory division of elderly into groups. Concluding, frequent changes in heart rate acceleration sign and size are the best signature for anomalous levels of short-term heart rate variability in elderly people.

[1]  S. Cerutti,et al.  Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society. , 2015, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[2]  Zbigniew R. Struzik,et al.  Entropic Measures of Complexity of Short-Term Dynamics of Nocturnal Heartbeats in an Aging Population , 2015, Entropy.

[3]  M Malik,et al.  Changes in Heart Rate Variability with Age , 1996, Pacing and clinical electrophysiology : PACE.

[4]  F. Magrini,et al.  The Prognostic Value of Heart Rate Variability in the Elderly, Changing the Perspective: From Sympathovagal Balance to Chaos Theory , 2012, Pacing and clinical electrophysiology : PACE.

[5]  Thomas Penzel,et al.  Aging effects on cardiac and respiratory dynamics in healthy subjects across sleep stages. , 2010, Sleep.

[6]  Phyllis K Stein,et al.  Heart rate variability and its changes over 5 years in older adults. , 2008, Age and ageing.

[7]  C. Peng,et al.  Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory. , 1999, Circulation.

[8]  Ary L. Goldberger,et al.  Heart Rate Fragmentation: A New Approach to the Analysis of Cardiac Interbeat Interval Dynamics , 2017, Front. Physiol..

[9]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[10]  Phyllis K. Stein,et al.  Development of more erratic heart rate patterns is associated with mortality post-myocardial infarction. , 2008, Journal of electrocardiology.

[11]  D H Singer,et al.  Twenty-four hour time domain heart rate variability and heart rate: relations to age and gender over nine decades. , 1998, Journal of the American College of Cardiology.

[12]  P.K. Stein,et al.  Heart rate variability is confounded by the presence of erratic sinus rhythm , 2002, Computers in Cardiology.

[13]  Zbigniew R. Struzik,et al.  Dynamical Landscape of Heart Rhythm in Long-Term Heart Transplant Recipients: A Way to Discern Erratic Rhythms , 2018, Front. Physiol..

[14]  Garry Egger,et al.  Castaways , 2009 .