P.Shanmuga Priya* and K. Balasubramanian Kabali

Stanley Medical College,Chennai. Tamilnadu. India.

DOI : https://dx.doi.org/10.13005/bpj/620

Abstract

Diabetes mellitus mainly type II  is due to resistance to insulin action. The hyperglycemia  casued by diabetes lead to micro and  macrovascular  complication  that endangers with life. Premenopausal women  with diabetes  had the risk similar to that of men with diabetes. Due to reduced estrogen hormone deficiency postmenopausal diabetic women had additional risk . To compare the frequency domain analysis of heart Rate Variability between premenopausal and postmenopausal  known  diabetic females. 60 Type II diabetic females around the age of 40- 5yrs (both pre and postmenopausal) from diabetic OPD were recruited from Stanley Medical College Hospital. Institutional Ethical committee approval  was obtained. After obtaining  written and informed consent from the subjects. ECG(LEADII)was recorded for five mintues in supine position using RMS Digital Polyrite.HRV analysis was done using Frequency  domain methods using  RMS Digital Polyrite software version 2.1. Our study  indicates that there is a lower  HRV in postmenopausal known diabetic  females when   compared  to that  of premenopausal  known diabetics. Further, decline in estrogen level  and   diabetes   gives a  additional risk of increased sympathovagal balance in postmenopausal diabetic  women. Type II postmenopausal  diabetic females have   increased level of autonomic  dysfunction .Hence  they  require  hormonal replacement therapy, regular periodic  evaluation  of  cardiac  autonomic   status in order to prevent  future cardiovascular  morbidity  and  mortality.

Keywords

Diabetes Mellitus; Heart  Rate Variability; Premenopausal and postmenopausal ageing; ostrogen

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Copy the following to cite this article: Priya P.S, Kabali K. B. Heart Rate Variability Analysis Between Premenopausal and Postmenopausal Known Diabetics: A Comparative Study. Biomed Pharmacol J 2015;8(1)

Copy the following to cite this URL: Priya P.S, Kabali K. B. Heart Rate Variability Analysis Between Premenopausal and Postmenopausal Known Diabetics: A Comparative Study. Biomed Pharmacol J 2015;8(1). Available from: http://biomedpharmajournal.org/?p=1749

INTRODUCTION

Diabetes Mellitus  is a group of common metabolic disorders that share the phenotype of hyperglycemia.The metabolic dysregulation associated with diabetes  mellitus causes secondary pathophysiological changes in multiple organ system that impose a tremendous burden on the individual  with diabetes and on the health care system¹.With evolving trend across worldwide, Diabetes Mellitus will be a leading cause of mortality and morbidity. The worldwide prevalence of Diabetes Mellitus has risen drastically over past two decades, from an estimated  30 million cases in 1985 to 285 million in 2010.In individuals aged more than 65 years ,the prevalence was 26.9%. Worldwide estimates project that in 2030 shows that the greatest number of individuals with Diabetes will be aged 45-64 years¹. Diabetic Autonomic Neuropathy (DAN) is among the most recognized and silent complications of diabetes, in the face of its significant harmful impact on survival and quality of life in people with diabetes² DAN may be either clinically evident or subclinical³ Reduced heart rate variability is the earliest indicator of CAN⁴.

MATERIALS AND  METHODS

60 Type II Diabetic females   around the age of 40-65yrs(both pre and postmenopausal) from diabetic OPD  with duration of diabetes of  3-10 yrs with Random Blood Sugar  ≥ 200 mg/dl or Fasting Blood Sugar  ≥ 126 mg/dl were recruited from Stanley Medical College Hospital. Institutional Ethical committee approval  was obtained. After obtaining written and informed consent from the subjects ECG(LEADII)was recorded for five mintues in supine position using RMS Digital Polyrite. HRV analysis was done using Frequency  Domain methods using RMS Digital Polyrite software version 2.1.

Exclusion Criteria

Subjects with a history of asthma, hypertension , cardiovascular disease and  those on chronic  medication .

Experimental   Protocol

The short term  Heart rate variability recording is usually performed for research , clinical investigations  and followed the procedure given in the Task-Force report on Heart Rate Variability subjects  were instructed to avoid heavy physical activity and also instructed to retrain from all caffeinated beverages for 12 hours prior to research activity. All the study subjects and controls have a prestructed proforma completed .Subjects were  screened after measuring height,weight,blood pressure.The basal recording of blood pressure was done using sphygmomanometer by standard   Riva Rocci method. Ask the  subjects to lie down  comfortably in the supine position in the Neuro physiology lab ,Department of Physiology,Stanley Medical Collage.(5 mints rest). Placed the ECG electrodes on the limbs of the subjects and connect the leads to the machine for lead II ECG recording. Transfer the data from RMS Polyrite to window based PC loaded with software for Heart rate variability.Removed ectopics and artifacts from the recorded ECG.Extracted  the R-R tachogram from the edited 256 –second ECG using  the R wave  detector  in the  Acq Knowledge software and saved it in the ASCII format which is later used offline for short –term  HRV analysis. Performed  HRV analysis  using  the  HRVanalysis  software version 2.1(Biosignal Analysis  group,Finland). Mean R-R is measured in second(s).Variance, defined as power in a portion of the total spectrum of frequencies, is measured n milliseconds squared(ms2).Mean R-R  is measured in seconds .

Parameters studied

Spectral indices (LF ms2,HF ms 2 ,  LF/HF ratio) are calculated.

Statistics

Data are expressed as mean ± SD .Data between the study groups were compared using unpaired Student  t-test. Differences were considered statistically significant at (P<0.05). The collected data was analysed with SPSS 16.0 version.Data were normally distributed based on the Kolmogorov-Smirnov Z test for normality.To describe about the data mean and S.D was used. To find the significant difference between the Patients and controls Independent t-test was used.

 RESULTS AND DISCUSSION

Diabetes Mellitus is characterized by hyperglycemia  mainly in Type II diabetes due to reduced action of insulin (Insulin resistance)1. It is the major cause for cardiovascular morbidity and mortality.  The main advantage of using frequency domain analysis of Heart rate variability is that one can study the signal’s frequency-specific oscillations.Thus  both the amount of  variability and the oscillation frequency(number of heart rate fluctuations per second) can be obtained. Spectral analysis involves decomposing the series of sequential R-R intervals into a sum of sinusoidal functions of different amplitudies and frequencies by the FFT algorithm. . The LF fluctuations are predominantly under sympathetic control with vagal modulation, whereas the HF fluctuations are under parasympathetic control⁵. Three main spectral components are distinguished in a spectrum calculated from short-term recordings of 2 to 5 minutes^6,7,8,9,10 : VLF, LF, and HF components. Frequency domain analyses contributed to the understanding of autonomic background of RR interval fluctuations in the heart rate record.^11,12Silent ischemic heart disease or cardiac arrhythmias have both been invoked as contributors to sudden death.  In Asymptomatic Diabetics (DIAD) study of 1123 patients with type 2 diabetes, cardiac autonomic dysfunction was a strong predictor of ischemia. Results from the European Diabetes Insulin-Dependent Diabetes Mellitus (IDDM) Complications Study showed that patients with impaired HRV had a higher corrected QT prolongation than without this complication Cardiac autonomic neuropathy (CAN), which can be documented by abnormal heart rate variability (HRV), occurs commonly in patients with diabetes and is associated with silent myocardial ischemia⁶ and increased mortality^7, In a recent large meta-analysis, Maser et al.  reported that the presence of  cardiac autonomic neuropathy was associated with a greater than threefold increase in mortality and sudden death⁷.. Autonomic imbalance between the sympathetic and parasympathetic nervous systems regulation of cardiovascular function contributes to metabolic abnormalities and significant morbidity and mortality for individuals with diabetes.^8-10The  presence of CAN was associated with a greater than threefold increase in mortality and sudden death. Silent ischemic heart disease or cardiac arrhythmias have both been invoked as contributors to sudden death. Meta-analyses of published data demonstrate that reduced cardiovascular autonomic function as measured by heart rate variability (HRV) is strongly associated with an increased risk of silent myocardial ischemia.s^9,15 Regular HRV testing provides early detection and thereby promotes timely diagnostic and therapeutic interventions. HRV was found to be an independent predictor of all-cause mortality during a period of 9 years, in a population-based study using Cox proportional hazard models. Moreover, the Hoorn study by Gerritsen et  al demonstrated that impaired autonomic function is associated with increased all-cause and cardiovascular mortality and that CAN in patientsalready at risk (diabetes, hypertension, or history of CVD) may be especially hazardous Clinical manifestations of cardiovascular autonomic dysfunction (e.g., exercise intolerance, intraoperative cardiovascular liability, orthostatic tachycardia and bradycardia syndromes, silent myocardial ischemia) can result in life-threatening outcomes^10-14

Table  1: Subjects Characteristics, Anthropometric Measures

Parameter		Mean	SD	t value	p value
BMI	Pre	31.6	39	1.01	0.317
	Post	24.4	1.6
SBP (mmHg)	Pre	120.2	6.8	7.11	0.00
	Post	131.3	5.2
DBP (mmHg	Pre	74	5.0	7.649	0.00
	Post	82.3	3.3

No significant difference between pre and postmenopausal study subjects compared to premenopausal diabetics,postmenopausal diabetics had  lower estrogen level,lower HF,Higher LFand high LF/HF ratio.

Chart: Comparison Of Heart Rate Variability Parameters Between Premenopausal and Postmenopausal Women Click her to view full Chart

Table 2: Frequency Domain Analysis oh heart rate variability

		Mean	SD	t value	p value
Pm2LF	Pre	1083.9	153.8	3.417	0.002
	Post	3245.5	555.2
Pm2HF	Pre	474.2	211.5	11.884	0.00
	Post	189.5	179.7
LF/HF	Pre	3.2	1.1	19.307	0.00
	Post	22.0	5.2

CONCLUSION

The postmenopausal women had a significantly reduced overall fluctuation in autonomic input demonstrated by lower HF, increased LF ,HF ratio in postmenopausal diabetic suggests that more sympathetic dominance.Therfore my study suggests that decline in levels of estrogen from pre to postmenopausal makes shift of autonomic balance towards the sympathetic dominence. Type II postmenopasual  diabetic  females have   increased level of autonomic  dysfunction .Hence  they  require  hormonal  replacement therapy, regular periodic  evaluation  of  cardiac  autonomic   status in order to prevent  future cardiovascular  morbidity  and  mortality.

REFERENCES

1. Harrison’s   Principles   Of   Internal Medicine-18th Edition (page2868-3003).
2. Vinik AI, Erbas T. Recognizing and treating diabetic autonomic neuropathy. Cleve Clin J Med.2001; 68: 928- 944.
3. American    Diabetes    Association   and   American Academy of Neurology. Report and recommendations of San   Antonio   Conference    on diabetic  neuropathy (Consensus Statement). D iabetes   . 1988; 37: 1000- 1004.
4. Maser R, Lenhard M,  De Cherney G. Cardiovascular autonomic neuropathy: the clinical significance of its determination. Endocrinologist. 2000; 10: 27-33.
5. Rodica Pop-Busui, MD, PHD,1 Gregory W. Evans, MA,2 Hertzel C. Gerstein, MD, MSC,3 Vivian Fonseca, MD,4 Jerome L. Fleg, MD,5 Byron J. Hoogwerf, MD,6 Saul Genuth, MD,7 Richard H. Grimm, MD, PHD,8 Marshall A. Corson, MD,9 Ronald Prineas, MD,2,* and the ACCORD Study Group Diabetes Care. 2010 July; 33(7): 1578–1584. 6. Sayers BM. Analysis of heart rate variability. Ergonomics. 1973;16:17-32
6. Hirsh JA, Bishop B. Respiratory sinus arrhythmia in humans: how breathing pattern modulates heart rate. Am J Physiol. 1981;241:H620-H629. Akselrod S, Gordon D, Ubel FA, Shannon DC, Barger AC, Cohen RJ.
7. 8..Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat to beat cardiovascular control. Science. 1981;213:220-222.
8. Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R, Pizzinelli P, Sandrone G, Malfatto G, Dell’Orto S, Piccaluga E, Turiel M, Baselli G, Cerutti S, Malliani A. Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympathovagal interaction in man and conscious dog. Circ Res. 1986;59:178-193.
9. Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991;84:1482. predictor of mortality after an acute myocardial infarction.
10. Pomeranz M, Macaulay RJB, Caudill MA, Kutz I, Adam D, Gordon D, Kilborn KM, Barger AC, Shannon DC, Cohen RJ, Benson M. Assessment of autonomic function in humans by heart rate spectral analysis. Am J Physiol. 1985;248:H151-H153.
11. Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R, Pizzinelli P, Sandrone G, Malfatto G, Dell’Orto S, Piccaluga E, Turiel M, Baselli G, Cerutti S, Malliani A. Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympathovagal interaction in man and conscious dog. Circ Res. 1986;59:178-193.
12. Ziegler D, Zentai CP, Perz S, Rathmann W, Haastert B, Doring A, Meisinger C.: Prediction of mortality using measures of cardiac autonomic dysfunction in the diabetic and nondiabetic population: the MONICA/KORA Augsburg Cohort Study. Diabetes Care 2008; 31: 556–561.
13. Ferrani AU, Radaelli, Centola M. Ageing and the cardiovascular system. J Appl Physiol 2003;95: 2591–2597.
14. Bannister R. Autonomic failure. A textbook ofclinical disorder of autonomic neuropathy. OxfordUniversity

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