Startseite Medizin Correlation among Poincare plot and traditional heart rate variability indices in adults with different risk levels of metabolic syndrome: a cross-sectional approach from Southern India
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Correlation among Poincare plot and traditional heart rate variability indices in adults with different risk levels of metabolic syndrome: a cross-sectional approach from Southern India

  • Chiranjeevi Kumar Endukuru , Girwar Singh Gaur , Dhanalakshmi Yerrabelli EMAIL logo , Jayaprakash Sahoo , Balasubramaniyan Vairappan und Alladi Charanraj Goud
Veröffentlicht/Copyright: 11. Januar 2023
Journal of Basic and Clinical Physiology and Pharmacology
Aus der Zeitschrift Journal of Basic and Clinical Physiology and Pharmacology Band 34 Heft 4

Abstract

Objectives

Heart rate variability (HRV) is an important marker of cardiac autonomic modulation. Metabolic syndrome (MetS) can alter cardiac autonomic modulation, raising the risk of cardiovascular disease (CVD). Poincaré plot analysis (PPA) is a robust scatter plot-based depiction of HRV and carries similar information to the traditional HRV measures. However, no prior studies have examined the relationship between PPA and traditional HRV measures among different risk levels of MetS. We evaluated the association between the Poincare plot and traditional heart rate variability indices among adults with different risk levels of MetS.

Methods

We measured anthropometric data and collected fasting blood samples to diagnose MetS. The MetS risk was assessed in 223 participants based on the number of MetS components and was classified as control (n=64), pre-MetS (n=49), MetS (n=56), and severe MetS (n=54). We calculated the Poincaré plot (PP) and traditional HRV measures from a 5 min HRV recording.

Results

Besides the traditional HRV measures, we found that various HRV indices of PPA showed significant differences among the groups. The severe MetS group had significantly lower S (total HRV), SD1 (short-term HRV), SD2 (long-term HRV), and higher SD2/SD1. The values of S, SD1, SD2, and SD2/SD1 were significantly correlated with most traditional HRV measures.

Conclusions

We found gradual changes in HRV patterns as lower parasympathetic and higher sympathetic activity alongside the rising number of MetS components. The HRV indices of PPA integrating the benefits of traditional HRV indices distinguish successfully between different risk levels of MetS and control subjects.

Keywords: autonomic modulation; heart rate variability; metabolic syndrome; Poincare plot analysis; risk stratification
Corresponding author: Dhanalakshmi Yerrabelli, Department of Physiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India, Phone: +919444781210, E-mail:

Funding source: Jawaharlal Institute of Postgraduate Medical Education and Research

Award Identifier / Grant number: JIP/Res/Intramural/Phs-1/2018-19/98

Acknowledgments

The authors wish to express their thanks for the financial support of the Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India. The subject’s participation in this study is also gratefully acknowledged.

  1. Research funding: Funded by Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER) in the form of an intramural Ph.D. research grant JIP/Res/Intramural/Phs-1/2018-19/98.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: The Institutional Ethical Committee approved the study protocol for human studies at JIPMER, Puducherry. The project reference no. is (JIP/IEC/2018/0301).

References

1. Kaur, J. A comprehensive review on metabolic syndrome. Cardiol Res Pract 2014;2014:943162. https://doi.org/10.1155/2014/943162.Suche in Google Scholar PubMed PubMed Central

2. Petrie, JR, Guzik, TJ, Touyz, RM. Diabetes, hypertension, and cardiovascular disease: clinical insights and vascular mechanisms. Can J Cardiol 2018;34:575–84. https://doi.org/10.1016/j.cjca.2017.12.005.Suche in Google Scholar PubMed PubMed Central

3. Alberti, KGMM, Eckel, RH, Grundy, SM, Zimmet, PZ, Cleeman, JI, Donato, KA, et al.. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study. Circulation 2009;120:1640–5. https://doi.org/10.1161/circulationaha.109.192644.Suche in Google Scholar PubMed

4. Eckel, RH, Alberti, KGMM, Grundy, SM, Zimmet, PZ. The metabolic syndrome. Lancet 2010;375:181–3. https://doi.org/10.1016/s0140-6736(09)61794-3.Suche in Google Scholar PubMed

5. Moreira, GC, Cipullo, JP, Ciorlia, LAS, Cesarino, CB, Vilela-Martin, JF. Prevalence of metabolic syndrome: association with risk factors and cardiovascular complications in an urban population. PLoS One 2014;9:e105056. https://doi.org/10.1371/journal.pone.0105056.Suche in Google Scholar PubMed PubMed Central

6. Saklayen, MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep 2018;20:12. https://doi.org/10.1007/s11906-018-0812-z.Suche in Google Scholar PubMed PubMed Central

7. Deepa, M, Farooq, S, Deepa, R, Manjula, D, Mohan, V. Prevalence and significance of generalized and central body obesity in an urban Asian Indian population in Chennai, India (CURES: 47). Eur J Clin Nutr 2009;63:259–67. https://doi.org/10.1038/sj.ejcn.1602920.Suche in Google Scholar PubMed

8. Prasad, DS, Kabir, Z, Dash, AK, Das, BC. Prevalence and risk factors for metabolic syndrome in Asian Indians: a community study from urban Eastern India. J Cardiovasc Dis Res 2012;3:204–11. https://doi.org/10.4103/0975-3583.98895.Suche in Google Scholar PubMed PubMed Central

9. Venugopal, V, Dongre, AR, Saravanan, S. Prevalence and determinants of metabolic syndrome among the rural adult population of Puducherry. Indian J Community Med 2019;44:21–5.10.4103/ijcm.IJCM_132_18Suche in Google Scholar

10. Stagnaro, S. Epidemiological evidence for the non-random clustering of the components of the metabolic syndrome: multicentre study of the mediterranean group for the study of diabetes. Eur J Clin Nutr 2007;61:1143–4. https://doi.org/10.1038/sj.ejcn.1602668.Suche in Google Scholar PubMed

11. Thayer, JF, Yamamoto, SS, Brosschot, JF. The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors. Int J Cardiol 2010;141:122–31. https://doi.org/10.1016/j.ijcard.2009.09.543.Suche in Google Scholar PubMed

12. Stuckey, MI, Tulppo, MP, Kiviniemi, AM, Petrella, RJ. Heart rate variability and the metabolic syndrome: a systematic review of the literature. Diabetes Metab Res Rev 2014;30:784–93. https://doi.org/10.1002/dmrr.2555.Suche in Google Scholar PubMed

13. Kleiger, RE, Stein, PK, Bigger, JT. Heart rate variability: measurement and clinical utility. Ann Noninvasive Electrocardiol 2005;10:88–101. https://doi.org/10.1111/j.1542-474x.2005.10101.x.Suche in Google Scholar PubMed PubMed Central

14. Wulsin, LR, Horn, PS, Perry, JL, Massaro, JM, DʼAgostino, RBS. The contribution of autonomic imbalance to the development of metabolic syndrome. Psychosom Med 2016;78:474–80. https://doi.org/10.1097/psy.0000000000000290.Suche in Google Scholar PubMed

15. Koskinen, T, Kähönen, M, Jula, A, Mattsson, N, Laitinen, T, Keltikangas-Järvinen, L, et al.. Metabolic syndrome and short-term heart rate variability in young adults. The cardiovascular risk in young Finns study. Diabet Med 2009;26:354–61. https://doi.org/10.1111/j.1464-5491.2009.02686.x.Suche in Google Scholar PubMed

16. Liao, D, Sloan, RP, Cascio, WE, Folsom, AR, Liese, AD, Evans, GW, et al.. Multiple metabolic syndrome is associated with lower heart rate variability. The atherosclerosis risk in communities study. Diabetes Care 1998;21:2116–22. https://doi.org/10.2337/diacare.21.12.2116.Suche in Google Scholar PubMed

17. Raimundo, RD, Godleski, JJ. Heart rate variability in metabolic syndrome. J Hum Growth Dev 2015;25:7–10. https://doi.org/10.7322/jhgd.96757.Suche in Google Scholar

18. Malik, M, John Camm, A, Thomas Bigger, J, Breithardt, G, Cerutti, S, Cohen, RJ, et al.. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 1996;93:1043–65. https://doi.org/10.1161/01.cir.93.5.1043.Suche in Google Scholar

19. Karmakar, CK, Gubbi, J, Khandoker, AH, Palaniswami, M. Analyzing temporal variability of standard descriptors of Poincaré plots. J Electrocardiol 2010;43:719–24. https://doi.org/10.1016/j.jelectrocard.2010.09.001.Suche in Google Scholar PubMed

20. Fishman, M, Jacono, FJ, Park, S, Jamasebi, R, Thungtong, A, Loparo, KA, et al.. A method for analyzing temporal patterns of variability of a time series from Poincare plots. J Appl Physiol (1985) 2012;113:297–306. https://doi.org/10.1152/japplphysiol.01377.2010.Suche in Google Scholar PubMed PubMed Central

21. 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. https://doi.org/10.1109/10.959330.Suche in Google Scholar PubMed

22. Hoshi, RA, Pastre, CM, Vanderlei, LCM, Godoy, MF. Poincaré plot indexes of heart rate variability: relationships with other nonlinear variables. Auton Neurosci 2013;177:271–4. https://doi.org/10.1016/j.autneu.2013.05.004.Suche in Google Scholar PubMed

23. Carrasco, S, Gaitán, MJ, González, R, Yánez, O. Correlation among Poincaré plot indexes and time and frequency domain measures of heart rate variability. J Med Eng Technol 2001;25:240–8. https://doi.org/10.1080/03091900110086651.Suche in Google Scholar PubMed

24. Guzik, P, Piskorski, J, Krauze, T, Schneider, R, Wesseling, KH, Wykretowicz, A, et al.. Correlations between the Poincaré plot and conventional heart rate variability parameters assessed during paced breathing. J Physiol Sci 2007;57:63–71. https://doi.org/10.2170/physiolsci.rp005506.Suche in Google Scholar

25. Hsu, CH, Tsai, MY, Huang, GS, Lin, TC, Chen, KP, Ho, ST, et al.. Poincaré plot indexes of heart rate variability detect dynamic autonomic modulation during general anesthesia induction. Acta Anaesthesiol Taiwanica 2012;50:12–8. https://doi.org/10.1016/j.aat.2012.03.002.Suche in Google Scholar PubMed

26. Tulppo, MP, Mäkikallio, TH, Takala, TES, Seppänen, T, Huikuri, HV. Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am J Physiol 1996;271:1–2.10.1152/ajpheart.1996.271.1.H244Suche in Google Scholar PubMed

27. Stein, PK, Domitrovich, PP, Huikuri, HV, Kleiger, RE. Traditional and nonlinear heart rate variability are each independently associated with mortality after myocardial infarction. J Cardiovasc Electrophysiol 2005;16:13–20. https://doi.org/10.1046/j.1540-8167.2005.04358.x.Suche in Google Scholar PubMed

28. Kubičková, A, Kozumplík, J, Nováková, Z, Plachý, M, Jurák, P, Lipoldová, J. Heart rate variability analysed by Poincaré plot in patients with metabolic syndrome. J Electrocardiol 2016;49:23–8. https://doi.org/10.1016/j.jelectrocard.2015.11.004.Suche in Google Scholar PubMed

29. Ma, Y, Tseng, P-H, Ahn, A, Wu, M-S, Ho, Y-L, Chen, M-F, et al.. Cardiac autonomic alteration and metabolic syndrome: an ambulatory ECG-based study in a general population. Sci Rep 2017;7:44363. https://doi.org/10.1038/srep44363.Suche in Google Scholar PubMed PubMed Central

30. Silva-E-Oliveira, J, Amélio, PM, Abranches, ILL, Damasceno, DD, Furtado, F. Heart rate variability based on risk stratification for type 2 diabetes mellitus. Einstein 2017;15:141. https://doi.org/10.1590/s1679-45082017ao3888.Suche in Google Scholar PubMed PubMed Central

31. Sellen, D. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. Geneva: WHO Technical Report Series No. 854; 1995:452 p.Suche in Google Scholar

32. Garrow, JS, Webster, J. Quetelet’s index (W/H2) as a measure of fatness. Int J Obes 1985;9:147–53.Suche in Google Scholar

33. Fukuyama, N, Homma, K, Wakana, N, Kudo, K, Suyama, A, Ohazama, H, et al.. Validation of the Friedewald equation for evaluation of plasma LDL-cholesterol. J Clin Biochem Nutr 2008;43:1–5. https://doi.org/10.3164/jcbn.2008036.Suche in Google Scholar PubMed PubMed Central

34. Endukuru, CK, Gaur, GS, Yerrabelli, D, Sahoo, J, Vairappan, B. Impaired baroreflex sensitivity and cardiac autonomic functions are associated with cardiovascular disease risk factors among patients with metabolic syndrome in a tertiary care teaching hospital of South-India. Diabetes Metabol Syndr 2020;14:2043–51. https://doi.org/10.1016/j.dsx.2020.10.018.Suche in Google Scholar PubMed

35. Magagnin, V, Bassani, T, Bari, V, Turiel, M, Maestri, R, Pinna, GD, et al.. Non-stationaries significantly distort short-term spectral, symbolic and entropy heart rate variability indices. Physiol Meas 2011;32:1775–86. https://doi.org/10.1088/0967-3334/32/11/s05.Suche in Google Scholar

36. Toichi, M, Sugiura, T, Murai, T, Sengoku, A. A new method of assessing cardiac autonomic function and its comparison with spectral analysis and coefficient of variation of R–R interval. J Auton Nerv Syst 1997;62:79–84. https://doi.org/10.1016/s0165-1838(96)00112-9.Suche in Google Scholar PubMed

37. Laude, D, Elghozi, JL, Girard, A, Bellard, E, Bouhaddi, M, Castiglioni, P, et al.. Comparison of various techniques used to estimate spontaneous baroreflex sensitivity (the EuroBaVar study). Am J Physiol Regul Integr Comp Physiol 2004;286:R226–31. https://doi.org/10.1152/ajpregu.00709.2002.Suche in Google Scholar PubMed

38. Chen, G, Chung, E, Meng, L, Alexander, B, Vu, T, Rinehart, J, et al.. Impact of non invasive and beat-to-beat arterial pressure monitoring on intraoperative hemodynamic management. J Clin Monit Comput 2012;26:133–40. https://doi.org/10.1007/s10877-012-9344-2.Suche in Google Scholar PubMed

39. Imholz, BP, Wieling, W, van Montfrans, GA, Wesseling, KH. Fifteen years experience with finger arterial pressure monitoring: assessment of the technology. Cardiovasc Res 1998;38:605–16. https://doi.org/10.1016/s0008-6363(98)00067-4.Suche in Google Scholar PubMed

40. White, WB. Heart rate and the rate-pressure product as determinants of cardiovascular risk in patients with hypertension. Am J Hypertens 1999;12:2.10.1016/S0895-7061(98)00280-5Suche in Google Scholar PubMed

41. Wulsin, LR, Horn, PS, Perry, JL, Massaro, JM, D’Agostino, RB. Autonomic imbalance as a predictor of metabolic risks, cardiovascular disease, diabetes, and mortality. J Clin Endocrinol Metab 2015;100:2443–8. https://doi.org/10.1210/jc.2015-1748.Suche in Google Scholar PubMed

42. La Rovere, MT, Bigger, JT, Marcus, FI, Mortara, A, Schwartz, PJ. Baroreflex sensitivity and heart-rate variability in prediction of total cardiac mortality after myocardial infarction. Lancet 1998;351:478–84. https://doi.org/10.1016/s0140-6736(97)11144-8.Suche in Google Scholar PubMed

43. Soares-Miranda, L, Sandercock, G, Vale, S, Santos, R, Abreu, S, Moreira, C, et al.. Metabolic syndrome, physical activity and cardiac autonomic function. Diabetes Metab Res Rev 2012;28:363–9. https://doi.org/10.1002/dmrr.2281.Suche in Google Scholar PubMed

44. Korhonen, I, Mainardi, LT, Yppärilä, H, Musialowicz, T. Comparison of linear and non-linear analysis of heart rate variability in sedated cardiac surgery patients. Annu Rep Res Reactor Inst Kyoto Univ 2001;1:496–9.10.1109/IEMBS.2001.1018976Suche in Google Scholar

45. Ashwell, M, Gunn, P, Gibson, S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev 2012;13:275–86. https://doi.org/10.1111/j.1467-789x.2011.00952.x.Suche in Google Scholar PubMed

46. Carnagarin, R, Matthews, VB, Herat, LY, Ho, JK, Schlaich, MP. Autonomic regulation of glucose homeostasis: a specific role for sympathetic nervous system activation. Curr Diabetes Rep 2018;18:107. https://doi.org/10.1007/s11892-018-1069-2.Suche in Google Scholar PubMed

47. Wade, KH, Carslake, D, Nilsen, TI, Timpson, NJ, Davey Smith, G, Romundstad, P. Blood pressure and mortality: using offspring blood pressure as an instrument for own blood pressure in the HUNT study. Sci Rep 2015;5:12399. https://doi.org/10.1038/srep12399.Suche in Google Scholar PubMed PubMed Central

48. Kudaiberdieva, G, Görenek, B, Timuralp, B. Heart rate variability as a predictor of sudden cardiac death. Anadolu Kardiyol Derg 2007;7:68–70.Suche in Google Scholar

49. Navarro-Lomas, G, De-La-O, A, Jurado-Fasoli, L, Castillo, MJ, Femia, P, Amaro-Gahete, FJ. Assessment of autonomous nerve system through non-linear heart rate variability outcomes in sedentary healthy adults. PeerJ 2020;8:e10178. https://doi.org/10.7717/peerj.10178.Suche in Google Scholar PubMed PubMed Central

50. Orellana, JN, De La Cruz Torres, B, Cachadiña, ES, De Hoyo, M, Domínguez Cobo, S. Two new indexes for the assessment of autonomic balance in elite soccer players. Int J Sports Physiol Perform 2015;10:452–7. https://doi.org/10.1123/ijspp.2014-0235.Suche in Google Scholar PubMed

51. De Vito, G, Galloway, SDR, Nimmo, MA, Maas, P, McMurray, JJV. Effects of central sympathetic inhibition on heart rate variability during steady-state exercise in healthy humans. Clin Physiol Funct Imag 2002;22:32–8. https://doi.org/10.1046/j.1475-097x.2002.00395.x.Suche in Google Scholar PubMed

52. Ma, Y, Tseng, PH, Ahn, A, Wu, MS, Ho, YL, Chen, MF, et al.. Cardiac autonomic alteration and metabolic syndrome: an ambulatory ECG-based study in a general population. Sci Rep 2017;7:44363. https://doi.org/10.1038/srep44363.Suche in Google Scholar PubMed PubMed Central

53. Li, Z, Tang, ZH, Zeng, F, Zhou, L. Associations between the severity of metabolic syndrome and cardiovascular autonomic function in a Chinese population. J Endocrinol Invest 2013;36:993–9.Suche in Google Scholar
Received: 2022-08-04
Accepted: 2022-12-24
Published Online: 2023-01-11

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/jbcpp-2022-0208
Schlagwörter für diesen Artikel
autonomic modulation; heart rate variability; metabolic syndrome; Poincare plot analysis; risk stratification

Artikel in diesem Heft

  1. Frontmatter
  2. Minireview
  3. Impact of mental toughness on athlete’s performance and interventions to improve
  4. Reviews
  5. A review of the mechanisms of anti-cancer activities of some medicinal plants–biochemical perspectives
  6. Antimicrobials in COVID-19: strategies for treating a COVID-19 pandemic
  7. Anxiolytic effects of vestibular stimulation: an update
  8. Original Articles
  9. Intermittent exposure to green and white light-at-night activates hepatic glycogenolytic and gluconeogenetic activities in male Wistar rats
  10. Study of pre-operative neutrophil–lymphocyte ratio in urothelial carcinoma
  11. The effects of Berberis vulgaris L. root extract on the opiate withdrawal syndrome and psychological factors: a randomized double-blind clinical trial
  12. Evidence of alterations in the learning and memory in offspring of stress-induced male rats
  13. The impact of vestibular symptoms and electronystagmography results on recovery from sudden sensorineural hearing loss
  14. Complementary mechanisms of modulation of spontaneous phasic contractions by the gaseous signalling molecules NO, H2S, HNO and the polysulfide Na2S3 in the rat colon
  15. Pharmacist-directed Sputnik V (GAM-COVID-VAC) surveillance program: a prospective observational study in Southern India
  16. Correlation among Poincare plot and traditional heart rate variability indices in adults with different risk levels of metabolic syndrome: a cross-sectional approach from Southern India
  17. Does etodolac affect TRPA1 functionality in vivo in human?
  18. Dynamic of irisin secretion change after moderate-intensity chronic physical exercise on obese female
  19. Letter to the Editor
  20. The prospective record-breaking obesity drug tirzepatide raises concerns about affordability
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