Recurrences in heart rate dynamics are changed in patients with diabetes mellitus

Clinical Physiology and Functional Imaging

Volumn 28, Issue 5, 2008, Pages 326-331

  Javorka, Michal ^a   Trunkvalterova, Zuzana ^a   Tonhajzerova, Ingrid ^a   Lazarova, Zuzana ^a   Javorkova, Jana ^b   Javorka, Kamil ^a  

^a University Teaching Hospital in Martin   (Slovakia)

^b Martinska Fakultna Nemocnica   (Slovakia)

Author keywords

Complexity; Diabetes mellitus; Heart rate variability; Non linear dynamics; Recurrence plot

Indexed keywords

ADOLESCENT; ADULT; ARTICLE; AUTONOMIC DYSFUNCTION; CLINICAL ARTICLE; CONTROLLED STUDY; DIABETIC NEUROPATHY; FEMALE; HEART INNERVATION; HEART RATE VARIABILITY; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; MALE; NONLINEAR SYSTEM; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; SCHOOL CHILD;

ADOLESCENT; ADULT; AUTONOMIC NERVOUS SYSTEM DISEASES; CHILD; DIABETES MELLITUS, TYPE 1; DIABETIC NEUROPATHIES; FEMALE; HEART; HEART RATE; HUMANS; MALE; MODELS, CARDIOVASCULAR; NONLINEAR DYNAMICS; PERIODICITY; PILOT PROJECTS; SENSITIVITY AND SPECIFICITY;

EID: 49849085393     PISSN: 14750961     EISSN: 1475097X     Source Type: Journal    
DOI: 10.1111/j.1475-097X.2008.00813.x     Document Type: Article

References (26)

1. Baumert M, Baier V, Haueisen J, Wessel N, Meyerfeldt U, Schirdewan A, Voss A. Forecasting of life threating arrhythmias using the compression entropy of heart rate. Methods Inf Med (2004); 43: 202-206.
2. Baumert M, Baier V, Schirdewan A, Truebner S, Voss A. Short- and long-term joint symbolic dynamics of heart rate and blood pressure in dilated cardiomyopathy. IEEE Trans Biomed Eng (2005); 52: 2112-2115.
3. Burger AJ, D'Elia JA, Weinrauch LA, Lerman I, Gaur A. Marked abnormalities in heart rate variability are associated with progressive deterioration of renal function in type 1 diabetic patients with overt nephropathy. Int J Cardiol (2002); 86: 281-287.
4. Cao L. Practical method for determining the minimum embedding dimension of a scalar time series. Physica D (1997); 110: 43-50.
5. Costa MD, Peng C-K, Goldberger AL Multiscale analysis of heart rate dynamics: Entropy and time irreversibility measures. Cardiovasc Eng (2008); (in press).
6. Dabire H, Mestivier D, Jarnet J, Safar ME, Chau NP. Quantification of sympathetic and parasympathetic tones by nonlinear indexes in normotensive rats. Am J Physiol (1998); 275: H1290-H1297.
7. Fraser AM, Swinney HL. Independent coordinates for strange attractors from mutual information. Phys Rev A (1986); 33: 1134-1140.
8. Giudice PL, Careddu A, Magni G, Quagliata T, Pacifici L, Carminati P. Autonomic neuropathy in streptozotocin diabetic rats: Effect of acetyl-L-carnitine. Diabetes Res Clin Pract (2002); 56: 173-180.
9. Goldberger AL, Peng CK, Lipsitz LA. What is physiologic complexity and how does it change with aging and disease? Neurobiol Aging (2002); 23: 23-26.
10. Gonzalez JJ, Cordero JJ, Feria M, Pereda E. Detection and sources of nonlinearity in the variability of cardiac R-R and blood pressure in rats. Am J Physiol (2000); 279: H3040-H3046.
11. Hayano J, Sakakibara Y, Yamada A, Yamada M, Mukai S, Fujinami T, Yokoyama K, Watanabe Y, Takata K. Accuracy of assessment of cardiac vagal tone by heart rate variability in normal subjects. Am J Cardiol (1991); 67: 199-204.
12. Makimattila S, Schlenzka A, Mantysaari M, Bergholm R, Summanen P, Saar P, Erkkila H, Yki-Jarvinen H. Predictors of abnormal cardiovascular autonomic function measured by frequency domain analysis of heart rate variability and conventional tests in patients with type 1 diabetes. Diabetes Care (2000); 23: 1686-1693.
13. Marwan N, Wessel N, Meyerfeldt A, Schirdewan A, Kurths J. Recurrence plot based measures of complexity and its application to heart rate variability data. Phys Rev E (2002); 66: 026702.
14. Marwan N, Romano MC, Thiel M, Kurths J. Recurrence plots for the analysis of complex systems. Phys Rep (2007); 438: 237-329.
15. Mestivier D, Dabire H, Chau NP. Effects of autonomic blockers on linear and nonlinear indexes of blood pressure and heart rate in SHR. Am J Physiol (2001); 272: H1099-H1113.
16. Schreiber T. Interdisciplinary application of nonlinear time series methods. Phys Rep (1999); 308: 1-64.
17. Schroeder EB, Chambless LE, Liao D, Prineas RJ, Evans GW, Rosamond WD, Heiss G. Diabetes, glucose, insulin, and heart rate variability. Diabetes Care (2005); 28: 668-674.
18. Takase B, Kitamura H, Noritake M, Nagase T, Kurita A, Ohsuzu F, Matsuoka T. Assessment of diabetic autonomic neuropathy using twenty-four hour spectral analysis of heart rate variability. A comparison with the findings of Ewing battery. Jpn Heart J (2002); 43: 127-135.
19. Takens F. Detecting strange attractors in turbulence. In: Dynamical Systems and Turbulence Lecture Notes in Mathematics, Vol. 898 (eds Rand, DA, Young, LS) (1981), pp. 365-381. Springer, Berlin.
20. Theiler J. Spurious dimension from correlation algorithms applied to limited time series data. Phys Rev A (1986); 34: 2427-2432.
21. Thiel M, Romano MC, Kurths J, Meucci R, Allaria E, Arecchi FT. Influence of observational noise on the recurrence quantification analysis. Physica D (2002); 171: 138-152.
22. Vinik AI, Erbas T. Recognizing and treating diabetic autonomic neuropathy. Cleve Clin J Med (2001); 68: 928-944.
23. Vinik AI, Maser RE, Mitchell BD, Freeman R. Diabetic Autonomic Neuropathy. Diabetes Care (2003); 26: 1553-1579.
24. Webber CL. Introduction to Recurrence Quantification Analysis. RQA Software Ver. 11.1 (2007). Available at: http://homepages.luc.edu/ ~cwebber/ (accessed on 10 November 2007).
25. Webber CL, Zbilut JP. Dynamical assessment of physiological systems and states using recurrence plot strategies. J Appl Physiol (1994); 76: 965-973.
26. Webber CL, Zbilut JP. Recurrence Quantification Analysis of Nonlinear Dynamical Systems, Tutorials in Contemporary Nonlinear Methods for the Behavioral Science Web Book (2005). US National Science Foundation. Available at: http://www.nsf.gov/sbe/bcs/pac/nmbs/nmbs.jsp (accessed on 10 November 2007).