Recurrence Quantification Analysis of Heart Rate Variability in Early Diagnosis of Diabetic Autonomic Neuropathy


Authors: T. Nedělka 1,2;  J. Schlenker 1;  L. Riedlbauchová 3;  R. Mazanec 1
Authors‘ workplace: Neurologická klinika dospělých 2. LF UK a FN v Motole, Praha 1;  Fakulta biomedicínského inženýrství ČVUT v Praze 2;  Kardiologická klinika 2. LF UK a FN v Motole, Praha 3
Published in: Cesk Slov Neurol N 2012; 75/108(6): 721-728
Category: Original Paper

Overview

Introduction:
Detection of autonomic dysfunction in subclinical stages of diabetic cardiovascular autonomic neuropathy is highly important and helps in therapeutic management. Evaluation of cardiovascular function is usually based on heart rate variability (HRV) linear data analysis in time and frequency domains. However, autonomic control of heart rate is complex and could be described by non-linear analysis. In our study, non-linear recurrence quantification analysis (RQA) was used.

Methods:
We analyzed RQA during orthostatic test in 20 patients with type 2 diabetes (mean age 54 years). Results were compared to sex and age-matched group of 20 healthy controls (mean age 53 years). Cross-comparison between RQA, time- and frequency-domains analysis during the supine rest phase of orthostatic test was also performed.

Results:
There was significant increase in percentage of recurrences in diabetic patients compared to controls in the following variables: determinism (p <0.0001), laminarity (p <0.0002), length of the longest diagonal line Lmax (p = 0.026) and mean length of vertical lines trapping time (p = 0.0214) in both phases of the orthostatic test. We found significant increase in determinism, laminarity and trapping time in the supine rest phase. However, the Lmax parameter remained insignificant compared to the control group and results were similar to previous studies.

Conclusion:
Reduction of complexity in cardiovascular regulation was found in diabetic patients compared to age-matched controls. In comparison to standard methods, RQA appears to be more sensitive in diagnostics of subclinical cardiovascular autonomic neuropathy. RQA may be useful as an additional approach to time and frequency domain analysis of HRV.

Key words:
diabetic autonomic neuropathy – cardiac autonomic neuropathy –

diabetes mellitus – heart rate variability – spectral analysis –

recurrence analysis


Sources

1. Ziegler D, Dannehl K, Mühlen H, Spüler M, Gries FA. Prevalence of cardiovascular autonomic dysfunction assessed by spectral analysis, vector analysis, and standard tests of heart rate variation and blood pressure responses at various stages of diabetic neuropathy. Diabet Med 1992; 9(9): 806–814.

2. The effect of intensive diabetes therapy on measures of autonomic nervous system function in the Diabetes Control and complications Trial (DCCT). Diabetologia 1998; 41(4): 416–423.

3. Kennedy WR, Navarro X, Sutherland DE. Neuropathy profile of diabetic patients in a pancreas transplantation program. Neurology 1995; 45(4): 773–780.

4. Fox CS, Coady S, Sorlie PD, D’Agostino RB sr, Pencina MJ, Vasan RS et al. Increasing cardiovascular disease burden due to diabetes mellitus: the Framingham Heart Study. Circulation 2007; 115(12): 1544–1550.

5. Rathmann W, Ziegler D, Jahnke M, Haastert B, Gries FA. Mortality in diabetic patients with cardiovascular autonomic neuropathy. Diabet Med 1993; 10(9): 820–824.

6. Schroeder EB, Chambless LE, Liao D, Prineas RJ, Evans GW, Rosamond WD et al. Diabetes, glucose, insulin, and heart rate variability: the Atherosclerosis Risk in Communities (ARIC) study. Diabetes Care 2005; 28(3): 668–674.

7. Takase B, Kitamura H, Noritake M, Nagase T, Kurita A, Ohsuzu F et al. 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(2): 127–135.

8. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiologic interpretation, and clinical use. Circulation 1996; 93(5): 1043–1065.

9. Opavský J. Autonomní nervový systém a diabetická autonomní neuropatie. Klinické aspekty a diagnostika. Praha: Galén 2002.

10. Vlčková E, Bednařík J, Buršová Š, Šajgalíková K, Mlčáková L. Spektrální analýza variability srdeční frekvence – normativní data. Cesk Slov Neurol N 2010; 73/106(6): 663–672.

11. Silipo R, Deco G, Vergassola R, Bartsch H. Dynamics extraction in multivariate biomedical time series. Biol Cybern 1998; 79(1): 15–27.

12. Javorka M, Trunkvalterova Z, Tonhajzerova I, Lazarova Z, Javorkova J, Javorka K. Recurrences in heart rate dynamics are changed in patients with diabetes mellitus. Clin Physiol Funct Imaging 2008; 28(5): 326–331.

13. Naschitz JE, Rosner I, Shaviv N, Khorshidi I, Sundick S, Isseroff H et al. Assessment of cardiovascular reactivity by fractal and recurrence quantification analysis of heart rate and pulse transit time. J Hum Hypertens 2003; 17(2): 111–118.

14. Marwan N. A historical review of recurrence plots. Eur Phys J Special Topics 2008; 164: 3–12.

15. Sharma V. Deterministic chaos and fractal complexity in the dynamics of cardiovascular behavior: perspectives on a new frontier. Open Cardiovasc Med J 2009; 3: 110–123.

16. Mohebbi M, Ghassemian H. Prediction of paroxysmal atrial fibrillation using recurrence plot-based features of the RR-interval signal. Physiol Meas 2011; 32(8): 1147–1162.

17. Hitara Y, Horai S, Aihara K. Reproduction of distance matrices and original time series from recurrence plots and their applications. Eur Phys J Spec Top 2008; 164(1):13–22.

18. Mestivier D, Dabiré H, Jarnet J, Safar ME, Chau NP. Quantification of sympathetic and parasympathetic tones by nonlinear indexes in normotensive rats. Am J Physiol 1998; 275 (4 Pt 2): H1290–H1297.

19. Mestivier D, Dabiré H, Chau NP. Effects of autonomic blockers on linear and non-linear indexes of blood pressure and heart rate in SHR. Am J Physiol Heart Circ Physiol 2001; 281(3): 1113–1121.

20. Hoyer D, Schmidt K, Zwiener U, Bauer R. Characterization of complex heart rate dynamics and their pharmacological disorders by non-linear prediction and special data transformations. Cardiovasc Res 1996; 31(3): 434–440.

21. Hagerman I, Berglund M, Lorin M, Nowak J, Sylvén C. Chaos related deterministic regulation of heart rate variability in time and frequency domains: effects of autonomic blockade and exercise. Cardiovascular Res 1996; 31(3): 410–418.

22. Sun R, Wang Y. Predicting termination of atrial fibrillation based on the structure and quantification of the recurrence plot. Med Eng Phys 2008; 30(9): 1105–1111.

23. Mohebbi M, Ghassemian H. Prediction of paroxysmal atrial fibrillation using recurrence plot-based features of the RR-interval signal. Physiol Meas 2011; 32(8): 1147–1162.

24. Acharya UR, Sree SV, Chattopadhyay S, Yu W, Ang PC. Application of recurrence quantification analysis for the automated identification of epileptic EEG signals. Int J Neural Syst 2011; 21(3): 199–211.

25. Priano L, Saccomandi F, Mauro A, Guiot C. Non-linear recurrence analysis of NREM human sleep microstructure discloses deterministic oscillation patterns related to sleep stage transitions and sleep maintenance. Conf Proc IEEE Eng Med Biol Soc 2010; 2010: 4934–49347.

26. Acharya UR, Faust O, Kannathal N, Chua T, Laxminarayan S. Non-linear analysis of EEG signals at various sleep stages. Comput Methods Programs Biomed 2005; 80(1): 37–45.

27. Trunkvalterova Z, Javorka M, Tonhajzerova I, Javorkova J, Lazarova Z, Javorka K et al. Reduced short--term complexity of heart rate and blood pressure dynamics in patients with diabetes mellitus type 1: multiscale entropy analysis. Physiol Meas 2008; 29(7): 817–828.

28. González JJ, Cordero JJ, Feria M, Pereda E. Detection and sources of nonlinearity in the variability of cardiac R-R intervals and blood pressure in rats. Am J Physiol Heart Circ Physiol 2000; 279(6): H3040–H3046.

29. Kennel MB, Brown R, Abarbanel HD. Determining embedding dimension for phase-space reconstruction using a geometrical construction. Phys Rev A 1992; 45(6): 3403–3411.

30. Fraser AM, Swinney HL. Independent coordinates for strange attractors from mutual information. Phys Rev A 1986; 33(2): 1134–1140.

31. Ding H, Crozier S, Wilson SJ. Optimization of Euclidean distance threshold in the application of recurrence quantification analysis to heart rate va­riability studies. Chaos Solitons Fractals 2008; 38(5): 1457–1467.

32. Schinkel S, Dimigen O, Marwan N. Selection of recurrence threshold for signal detection. Eur Phys J Spec Top 2008; 164: 45–53.

33. Chattipakorn N, Incharoen T, Kanlop N, Chattipakorn S. Heart rate variability in myocardial infarction and heart failure. Int J Cardiol 2007; 120(3): 289–296.

34. Anderson JL, Horne BD. Nonlinear heart rate va­riability: a better ECG predictor of cardiovascular risk? J Cardiovasc Electrophysiol 2005; 16(1): 21–23.

35. Feldman EL, Stevens MJ, Thomas PK, Brown MB, Canal N, Greene DA. A practical two-step quantitative clinical and electrophysiological assessment for the diagnosis and staging of diabetic neuropathy. Dia­betes Care 1994; 17(11): 1281–1289.

36. Marwan N. Encounters with neighbours: current developments of concepts based on recurrence plots and their applications. Postdam: University Potsdam 2003.

37. Traut M. MATLAB® Recipes for Earth Sciences. Potsdam: Springer 2007.

38. Sun R, Wang Y. Predicting termination of atrial fibrillation based on the structure and quantification of the recurrence plot. Med Eng Phys 2008; 30(9): 1105–1111.

39. Cellucci CJ, Albano AM, Rapp PE. Statistical validation of mutual information calculations: comparison of alternative numerical algorithms. Phys Rev E Stat Nonlin Soft Matter Phys 2005; 71 (6 Pt 2): 066208.

40. Schlenker J. Hodnocení variability srdečního rytmu pomocí rekurentní analýzy. Diplomová práce. Kladno: ČVUT – FBMI 2010.

Labels
Paediatric neurology Neurosurgery Neurology

Article was published in

Czech and Slovak Neurology and Neurosurgery

Issue 6

2012 Issue 6

Most read in this issue

This topic is also in:


Login
Forgotten password

Don‘t have an account?  Create new account

Forgotten password

Enter the email address that you registered with. We will send you instructions on how to set a new password.

Login

Don‘t have an account?  Create new account