Heart rate variability as a predictive factor for coronary artery disease

Document Type : Research Paper

Authors

1 Department of Physiology, School of Medicine, Babol University of Medical Sciences, Babol, Iran

2 Department of Physiology, Shaheed Beheshti University of Medical Sciences, Tehran, Iran

3 Department of Physiology, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran

Abstract

Background and Objective: Heart rate variability (HRV) is the amount of heart rate fluctuations around the mean heart rate and can be used as a mirror of the cardiorespiratory control system. It is a valuable tool to investigate the sympathetic and parasympathetic functions of the autonomic nervous system. This variation during respiration is called respiratory sinus arrhythmia (RSA). RSA reflects heart rate control system, especially a cardiac parasympathetic activity which can be evaluated by some proper tests such as standing test. Researches show HRV alters among patients with coronary artery diseases (CAD).
Materials and Methods: In this study, we intended to calculate amount of HRV in patients with chest pain before diagnostic exercise stress test (EST) and to compare the obtained results with EST results. 66 (19 women and 47 men) with chest pain. Volunteers and unknown CAD referred for EST with a mean age of 50 years were participated in this study. Each volunteer underwent deep breathing (6 breaths/minute) and standing up tests prior to EST for HRV measurements.
Results: There was less variation in heart rate during both deep breathing and standing up tests in patients with positive result of EST than in patients with negative result of EST.
Conclusion: Our study suggests that HRV is depressed in individuals who have unknown coronary artery disease with an immediate positive EST result.

Keywords

References

1.      Acharya UR, Joseph KP, Kannathal N, Lim CM, Suri JS. Heart rate variability: a review. Medical and Biological Engineering and Computing 2006; 44(12):1031-51. doi: 10.1007/s11517-006-0119-0.
2.      Li H-R, Lu T-M, Cheng H-M, Lu D-Y, Chiou C-W, Chuang S-Y, et al. Additive value of heart rate variability in predicting obstructive coronary artery disease beyond Framingham risk. Circulation Journal 2016; 80(2):494-501. doi: 10.1253/circj.CJ-15-0588.
3.      Katona PG, Jih F. Respiratory sinus arrhythmia: noninvasive measure of parasympathetic cardiac control. Journal of Applied Physiology 1975; 39(5):801-5. doi: 10.1152/jappl.1975.39.5.801.
4.      Stålberg EV, Nogués MA. Automatic analysis of heart rate variation: I. Method and reference values in healthy controls. Muscle & Nerve 1989; 12(12):993-1000. doi: 10.1002/mus.880121207.
5.      Airaksinen K, Ikäheimo M, Linnaluoto M, Niemelä M, Takkunen J. Impaired vagal heart rate control in coronary artery disease. Heart. 1987; 58(6):592-7. doi: 10.1136/hrt.58.6.592.
6.      Tristani FE, Kamper DG, McDermott DJ, Peters BJ, Smith JJ. Alterations of postural and Valsalva responses in coronary heart disease. American Journal of Physiology-Heart and Circulatory Physiology. 1977; 233(6):H694-9. doi: 10.1152/ajpheart.1977.233.6.H694.
7.      Brown KA, Maloney JD, Smith C, Haritzler G, Ilstrup DM. Carotid sinus reflex in patients undergoing coronary angiography: relationship of degree and location of coronary artery disease to response to carotid sinus massage. Circulation 1980; 62(4):697-703. doi: 10.1161/01.cir.62.4.697.
8.      Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explored in the frequency domain. Circulation 1991; 84(2):482-92. doi: 10.1161/01.cir.84.2.482.
9.      Hayano J, Yuda E. Pitfalls of assessment of autonomic function by heart rate variability. Journal of physiological Anthropology 2019;38(1):3. https://doi.org/10.1186/s40101-019-0193-2.
10.    Shields RW. Heart rate variability with deep breathing as a clinical test of cardiovagal function. Cleveland Clinic Journal of Medicine 2009; 76 Suppl 2:S37-40. doi: 10.3949/ccjm.76.s2.08.
11.    Huikuri HV, Mäkikallio TH. Heart rate variability in ischemic heart disease. Autonomic Neuroscience 2001; 90(1-2):95-101. doi: 10.1016/S1566-0702(01)00273-9.
12.    Hayano J, Sakakibara Y, Yamada M, Ohte N, Fujinami T, Yokoyama K, et al. Decreased magnitude of heart rate spectral components in coronary artery disease. Its relation to angiographic severity. Circulation 1990; 81(4):1217-24. doi: 10.1161/01.cir.81.4.1217.
13.    Minisi AJ, Thames MD. Effect of chronic myocardial infarction on vagal cardiopulmonary baroreflex. Circulation Research 1989; 65(2):396-405. doi: 10.1161/01.res.65.2.396.
14.    Huikuri HV, Jokinen V, Syvänne M, Nieminen MS, Airaksinen KJ, Ikäheimo MJ, et al. Heart rate variability and progression of coronary atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology. 2015;35(1):1. doi: 10.1161/ATV.0000000000000016.
15.    La Rovere MT, Bigger Jr JT, Marcus FI, Mortara A, Schwartz PJ, Investigators A. Baroreflex sensitivity and heart-rate variability in prediction of total cardiac mortality after myocardial infarction. The Lancet 1998; 351(9101):478-84. doi: 10.1016/s0140-6736(97)11144-8.
16.    Pfeifer MA, Cook D, Brodsky J, Tice D, Reenan A, Swedine S, et al. Quantitative evaluation of cardiac parasympathetic activity in normal and diabetic man. Diabetes 1982; 31(4 Pt 1):339-45. doi: 10.2337/diab.31.4.339.
17.    Villareal RP, Liu BC, Massumi A. Heart rate variability and cardiovascular mortality. Current atherosclerosis Reports 2002; 4(2):120-7. doi: 10.1007/s11883-002-0035-1.
18.    Singh JP, Larson MG, O’Donnell CJ, Wilson PF, Tsuji H, Lloyd-Jones DM, et al. Association of hyperglycemia with reduced heart rate variability (The Framingham Heart Study). The American Journal of Cardiology 2000; 86(3):309-12. doi: 10.1016/s0002-9149(00)00920-6.
19.    Goldenberg I, Goldkorn R, Shlomo N, Einhorn M, Levitan J, Kuperstein R, et al. Heart rate variability for risk assessment of myocardial ischemia in patients without known coronary artery disease: The HRV‐DETECT (heart rate variability for the detection of myocardial ischemia) study. Journal of the American Heart Association 2019; 8(24):e014540. doi: 10.1161/JAHA.119.014540.
20.    Ge D, Srinivasan N, Krishnan SM. Cardiac arrhythmia classification using autoregressive modeling. Biomedical Engineering Online 2002; 1:5. doi: 10.1186/1475-925x-1-5.
Journal of Basic and Clinical Pathophysiology
Volume 9, Issue 1
May 2021
Pages 16-22

Files

Share

How to cite

Statistics