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Heart rate variability by Poincaré plot and spectral analysis in young healthy subjects and patients with type 1 diabetes Przemysław Guzik, MD, PhD, Bartosz Bychowiec, MD, Jarosław Piskorski*, PhD, Adam Węgrzynowski**, MD, Tomasz Krauze, MSc, Raphael Schneider*** Ing., Piotr Liszkowski**, MD, Andrzej Wykrętowicz, MD, PhD, Bogna Wierusz-Wysocka***, MD, PhD and Henryk Wysocki, MD, PhD Department of Cardiology-Intensive Therapy, University of Medical Sciences in Poznań, Przybyszewskiego 49, 60-355 Poznań, Poland; *Institute of Physics, University of Zielona Góra, Zielona Góra, Poland; **Department of Diabetology, University of Medical Sciences in Poznań, Poland ***Klinikum rechts der Isar, TUM, Munich, Germany; e-mail: [email protected] Abstract: An abnormal autonomic modulation of the heart rate is common in young patients with type 1 diabetes (IDDM). Both spectral heart rate variability (HRV) and the Poincaré plot (PP) analysis of RR intervals has been employed in the evaluation of autonomic control of the heart rate. However, spectral HRV and not the PP HRV has been used in IDDM patients. We aimed to describe HRV with the use of spectral and PP analysis in young IDDM patients and healthy subjects. Resting 5 minutes ECG was recorded in 70 healthy young volunteers (19 – 28 years old, 32 female) and 39 young IDDM patients (18-34 years, 17 female). Compared with healthy volunteers, IDDM patients presented significantly reduced values of SD1 (p<0.0001), SD2 (p<0.0001), the area of imaginary ellipse of PP (p<0.0001), HF (p=0.0116) and LF/HF (p=0.0013) and not quite significantly decreased ratio of SD2/SD1 (p=0.0765). The values of TP and LF did not differ significantly between IDDM patients and healthy volunteers. In conclusion, similarly to the spectral approach to HRV, the Poincaré plot analysis reveals that patients with IDDM have reduced HRV, which may be secondary to some autonomic dysfunction. Both spectral HRV and PP analysis showed that short term HRV is abnormal in IDDM patients. Conversely, the PP analysis but not spectral HRV demonstrated that the total and long-term HRV is also impaired in IDDM patients. INTRODUCTION Poor glycemic control plays an important role in the development and progression of autonomic dysfunction in patients with type 1 diabetes mellitus (IDDM).1,2 It has been demonstrated on several occasions that reduced cardiovascular autonomic function may be measured by heart rate variability (HRV).3-7 The Poincaré plot (PP) analysis of RR intervals (RRI) is a nonlinear HRV method and it has been shown to reflect autonomic control of the heart rate.8-21 To the best of our knowledge it seems that PP analysis has not been used as a measure of HRV in IDDM patients. In this study we used both spectral and PP-derived analysis of HRV to evaluate the autonomic control of the heart rate in young IDDM patients and healthy people. SUBJECTS & METHODS Patients with type 1 diabetes. Thirty nine young IDDM patients (18-34 years, 17 female) with at least 5 years history of the disease and the presence of sinus rhythm were recruited in the study. Healthy subjects Seventy young healthy volunteers (19 – 28 years old, 32 female) agreed to participate in the study. Protocol & methods. The study was performed in a warm and quiet room with all individuals resting for 15 minutes in supine position and breathing spontaneously. Afterward, 3-channel chest ECG was recorded by an A/D converter with sampling frequency of 1600 Hz (Porti 5, TMSI, The Netherlands) for 5 minutes. The recorded signals were evaluated with special software - RASCHlab from the libRASCH project (v. 0.6.1; www.librasch.org, Germany).22 After an automatic evaluation of ECG, the visual inspection and all necessary corrections were done. The values of RRIs were retrieved from the stored recordings and used in further analysis. Measurement of heart rate and its variability 64 RESULTS Compared with healthy volunteers, IDDM patients presented significantly reduced values of SD1 (60.0+/-52.0 vs. 25.4+/-13.7 ms; p<0.0001), SD2 (115.0+/-54.0 vs. 61.5+/-24.9 ms; p<0.0001), S (29276+/-46524 vs. 5751+/-5200 ms2; p<0.0001), HF (447.6+/-384.5 vs. 268.4+/-273.7 ms2; p=0.0116) and LF/HF (2.1+/-1.2 vs. 3.3+/-2.7; p=0.0013) whereas the ratio SD2/SD1 was not quite significantly decreased (2.4+/-0.8 vs. 2.7+/0.9; p=0.0765). The values of TP (3088+/-4484 vs. 1908+/-1584 ms2; n.s.) and LF (837.5+/-803.5 vs. 631.7+/-571.5 ms2; n.s.) did not differ significantly between IDDM patients and healthy volunteers. All results are shown on Figures 2-5. 10000 80000 8000 n.s. p<0.0001 60000 S [m s2] T P [m s 2 ] Heart rate, expressed in terms of RRI, and HRV were measured in all recordings. For HRV analysis 2 approaches were used: - frequency domain HRV with assessment of total power (TP), low frequency power (LF) and high frequency power (HF), and LF to HF ratio (LF/HF) according to published references;7 - PP analysis with the use of home-made scripts written in Matlab (The MathWorks Inc, USA) according to published references.8,9 There are 2 standard descriptors of PP (see Fig. 1 below), namely SD2 (measuring the dispersion of points along the line of identity) and SD1 (assessing the dispersion of points across the identity line).8,9 SD1 is a measure of short term HRV whereas SD2 a measure of long and short term HRV.8-11 6000 4000 40000 20000 2000 0 0 Healthy IDDM Healthy IDDM Figure 2. Total HRV by spectral (left part) and Poincaré plot (right part) analyses in healthy people and IDDM patients. 900 125 p=0.0116 450 300 75 50 25 150 0 0 Healthy IDDM Healthy IDDM Figure 3. Short-term HRV by spectral (left part) and Poincaré plot (right part) analyses in healthy people and IDDM patients. 2000 200 n.s. 1500 p<0.0001 150 S D 2 [m s] LF [m s 2 ] Additionally, we have combined SD1 and SD2 to form two additional descriptors of PPs: - S corresponding to the area of the imaginary ellipse on the Poincaré plot and is expressed by the formula S= π x SD1 x SD2; - the ratio of SD2 to SD1 (SD2/SD1) by analogy to LF/HF from spectral HRV analysis. We have reasons to believe that S illustrates the total HRV and SD2/SD1 describes sympathovagal balance.12 Statistical analysis All continuous data were presented as means +/standard deviations (SD). Student t-test was applied in statistical comparison of HRV parameters between IDDM patients and healthy subjects. Only p < 0.05 was considered statistically significant. All graphs and analyses were performed in Prism 4.02 for Windows (GraphPad, USA). p<0.0001 100 600 S D 1 [m s] Figure 1. A sample of Poincaré plot with its descriptors H F [m s 2 ] 750 1000 500 100 50 0 0 Healthy IDDM Healthy IDDM Figure 4. Short-term and long-term HRV by spectral (left part) and Poincaré plot (right part) analyses in healthy people and IDDM patients. 65 7 6 4 p=0.0013 3 S D 2/S D 1 5 LF /H F p=0.0765 4 3 2 2 1 1 0 0 Healthy IDDM Healthy IDDM Figure 5. Sympathetic-parasympathetic balance by spectral (left part) and Poincaré plot (right part) analyses in healthy people and IDDM patients. DISCUSSION In this study we have found that young IDDM patients, compared to healthy people, have reduced HRV. This is a known phenomenon but the new message is that the reduced HRV in IDDM patients can also be found with the use of PP analysis. Moreover, it appears that PP analysis was more sensitive than spectral HRV to present attenuated autonomic modulation of the heart rate in diabetic patients. Diabetic patients are at risk of the premature atherosclerosis leading to increased cardiovascular morbidity. The ischemic heart disease with acute coronary syndromes, heart failure, diabetic cardiomyopathy, myocardial infarction, various arrhythmias and sudden cardiac death are more common and happen earlier than in non-diabetic people. Additionally, abnormal glucose metabolism with insulin deficiency, chronic inflammation and endothelial dysfunction lead to repetitive tissue ischemia and may produce autonomic neuropathy.1,2,3,6 Therefore, there are many reasons for HRV reduction in the course of diabetes. It may be secondary to the impaired function of cardiovascular system, to the presence of diabetic autonomic neuropathy and to the occurrence of both complications of the disease. In fact, the reduced HRV in IDDM individuals was better reflected with PP analysis than with spectral method in our study. The spectral HRV showed that only HF presenting short-term RRI variability was significantly decreased in diabetics. As a results, the balance between sympathetic and parasympathetic influences on the heart rate was increased in IDDM patients compared with healthy persons. As it was shown, there was no significant difference in TP (total HRV) and LF (short- and long-term HRV) between IDDM and healthy subjects. Conversely, PP analysis of HRV showed that S, being a measure of total HRV (and also of short- term HRV), and SD2, expressing both short- and long term HRV, are diminished in IDDM patients. Similarly, SD1 reflecting short-term HRV was significantly reduced in the diabetic patients as well. The sympathetic-parasympathetic balance described by PP analysis (SD2/SD1) was also increased in diabetic individuals although not quite significantly (p=0.0765). Quite a lot of studies have proven that the PP analysis of HRV is a reliable tool for describing autonomic modulation of cardiovascular system. These studies have been performed both in physiological and in clinical settings.8-21 Nevertheless, it seems that it is the first time that the Poincaré plot analysis has been used in young people with type 1 diabetes to describe autonomic control of the hear rate. The diabetic neuropathy is the most probable but not the sole cause of the observed HRV reduction in IDDM patients. Additionally, the prospect of using the PP analysis of HRV as a tool for the diagnosis of diabetic neuropathy is very promising, but we have not investigated this possibility, as our objectives in the present study have been different. This problem calls for more research and shall be addressed in future studies. CONCLUSION. Both the Poincaré plot analysis and the spectral method reveal that patients with IDDM have reduced HRV. It looks like not only the spectral HRV but the Poincaré plot analysis of RRI is also able to show impaired autonomic control of the heart rate in young IDDM patients. References: 1. Larsen JR, Sjoholm H, Berg TJ et al. Eighteen years of fair glycemic control preserves cardiac autonomic function in type 1 diabetes. Diabetes Care. 2004;27:963-6. 2. The effect of intensive diabetes therapy on measures of autonomic nervous system function in the Diabetes Control and Complications Trial (DCCT). Diabetologia. 1998;41:416-23. 3. Ziegler D, Laux G, Dannehl K et al. Assessment of cardiovascular autonomic function: age-related normal ranges and reproducibility of spectral analysis, vector analysis, and standard tests of heart rate variation and blood pressure responses. Diabet Med 1992; 9:166–175 66 4. Howorka K, Pumprla J, Schabmann A Optimal parameters for short-term heart rate spectrogram for routine evaluation of diabetic cardiovascular autonomic neuropathy. J Auton Nerv Syst 1998; 69:164–172 5. Gerritsen J, TenVoorde BJ, Dekker JM et al. Measures of cardiovascular autonomic nervous function: agreement, reproducibility, and reference values in middle age and elderly subjects. Diabetologia. 2003;46:330-8 6. Vinik AI, Maser RE, Mitchell BD, Freeman R. Diabetic autonomic neuropathy. Diabetes Care. 2003; 26:1553-79 7. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation. 1996;93:1043–65 8. Brennan M, Palaniswami M, Kamen P. Poincaré plot interpretation using a physiological model of HRV based on a network of oscillators, Am J Physiol Heart Circ Physiol 2002; 283: H1873–H1886 9. Brennan M, Palaniswami M, Kamen P. Do existing measures of Poincaré plot geometry reflect nonlinear features of heart rate variability? IEEE Trans Biomed Eng 2001;48:1342-7. 10. Tulppo MP, Makikallio TH, Takala TE et al. Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am. J. Physiol. 1996; 271: H244–H252. 11. Tulppo MP, Makikallio TH, Seppanen T et al. Vagal modulation of heart rate during exercise: effects of age and physical fitness. Am J Physiol. 1998;274:H424-9. 12. Guzik P, Piskorski J, Krauze T et al. The autonomic modulating effects of changing respiratory rate on HRV are portrayed by novel descriptors of Poincaré plot analysis. Proceedings from the Joint ISE and ISHNE Congress. Folia Cardiologica, 2005;12 suppl: in press. 13. Tulppo MP,Makikallio TH, Seppanen T et al. Effects of pharmacological adrenergic and vagal modulation on fractal heart rate dynamics. Clin Physiol 2001;21:515-523 14. Tulppo MP,Makikallio TH, Seppanen T et al. Heart rate dynamics during accentuated sympathovagal interaction. Am J Physiol 1998;274 (Heart Circ Physiol):H810-H816. 15. Woo, MA, Stevenson WG, Moser DK et al. Complex heart rate variability and serum norepinephrine levels in patients with advanced heart failure. J Am Coll Cardiol 1994; 23: 565-591 16. Woo MA, Stevenson WG, Moser DK et al. Patterns of beat-to-beat heart rate variability in advanced heart failure. Am Heart J. 1992;123:704-10. 17. Hnatkova K, Copie X, Staunton A et al. Traditional and nonlinear heart rate variability are each independently associated with mortality after myocardial infarction. J Electrocardiol. 1995;28 Suppl:74-80 18. Otzenberger H, Gronfier C, Simon C et al. Dynamic heart rate variability: a tool for exploring sympathovagal balance continuously during sleep in men. Am J Physiol. 1998;275:H946-50. 19. Copie X, Leheuzey JY, Iliou MC, et al. Correlation between time-domain measures of heart rate variability and scatterplots in postinfarction patients. Pacing Clin Electrophysiol. 1996; 19:342–7. 20. Bergfeldt L, Haga Y. Power spectral and Poincare plot characteristics in sinus node dysfunction. J Appl Physiol. 2003;94:2217-24 21. Woo MA, Stevenson WG, Moser DK et al. Patterns of beat-to-beat heart rate variability in advanced heart failure. Am Heart J. 1992;123:704-10. 22. Schneider R, Barthel P, Bauer A et al. libRASCH - A Programming Framework for Signal Handling. Proceedings Computer in Cardiology 2004;31:53-56 67