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Table of Contents
Year : 2014  |  Volume : 8  |  Issue : 1  |  Page : 4-7

Short term heart rate variability for early assessment of autonomic neuropathy in patients with type 2 diabetes mellitus: A comparative cross-sectional study

1 Department of Physiology, SDM Medical College, Dharwad, Karnataka, India
2 Department of Medicine, SDM Medical College, Dharwad, Karnataka, India

Date of Web Publication18-Sep-2014

Correspondence Address:
Anupama Deepak
Department of Physiology, SDM College of Medical Sciences and Hospital, Manjushree Nagar, Sattur, Dharwad, Karnataka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0331-3131.141021

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Background: Cardiovascular autonomic diabetic neuropathy (CADN) is an important diabetes-associated complication. Reduced heart rate variation is the earliest indicator of CADN.
Aims: The aim was to study the prospect of using short term heart rate variability (HRV) analysis for early diagnosis of CADN.
Settings and Design: The type of this study was hospital-based comparative cross-sectional study.
Materials and Methods: A total of 30 asymptomatic, type 2 diabetic male patients with duration of diabetes of 1-5 years with random blood sugar ≥200 mg/dl (11.1 mmol/L) or fasting blood sugar ≥126 mg/dl (7 mmol/L) in the age group of 30-65 years were selected as subjects. Thirty age and sex matched healthy nondiabetics were selected as controls. HRV analysis was performed using electrocardiogram recorded in lead II, at rest, in the supine position for 5 min.
Results: Total power, low frequency power, high frequency power, standard deviation of all R-R intervals, root mean square of successive RR-interval differences, number of intervals differing by >50 ms from adjacent interval (NN50), and percentage of NN50 (pNN50) were significantly less in diabetics when compared to nondiabetics (P < 0.05).
Conclusion: Data from the study demonstrated that asymptomatic diabetics with <5 years history had already developed autonomic neuropathy. Short term analysis of HRV can be used as a valuable tool for early diagnosis of autonomic neuropathy.

Keywords: Cardiovascular autonomic diabetic neuropathy, short term heart rate variability, type 2 diabetics

How to cite this article:
Deepak A, Aithal K, Khode VH, Nallulwar SC. Short term heart rate variability for early assessment of autonomic neuropathy in patients with type 2 diabetes mellitus: A comparative cross-sectional study. Ann Nigerian Med 2014;8:4-7

How to cite this URL:
Deepak A, Aithal K, Khode VH, Nallulwar SC. Short term heart rate variability for early assessment of autonomic neuropathy in patients with type 2 diabetes mellitus: A comparative cross-sectional study. Ann Nigerian Med [serial online] 2014 [cited 2021 Apr 18];8:4-7. Available from: https://www.anmjournal.com/text.asp?2014/8/1/4/141021

   Introduction Top

Diabetic autonomic neuropathy (DAN) is among the least recognized and understood complications of diabetes, despite its significant negative impact on survival and quality of life in people with diabetes. [1] DAN may be either clinically evident or subclinical. [2] Clinical symptoms of autonomic neuropathy generally do not occur until long after the onset of diabetes. Subclinical autonomic dysfunction can however, occur within a year of diagnosis in type 2 diabetes patients and within 2 years in type 1 diabetes patients. Due to its association with a variety of adverse outcomes including sudden death, cardiovascular autonomic diabetic neuropathy (CADN) is the most clinically important and well-studied form of DAN. [3] An important prerequisite for therapeutic intervention to CADN is to identify it as early as possible, since cardiac denervation seems to be reversible at the beginning of the disease. [4]

Reduced heart rate variability (HRV) is the earliest indicator of CADN. [5] Though, cardiovascular reflex tests of HRV standardized by Ewing et al. are noninvasive, they require patient co-operation to a greater extent. [6] They may not be sensitive enough to reveal subtle effects of interventions on autonomic nerve function. [7]

Frequency-domain and time-domain analysis of HRV have been shown to be sensitive to quantify both sympathetic and parasympathetic components of autonomic nervous system (ANS). [6] Analysis of HRV by these methods have been done in diabetics using 24 h Holter recording of electrocardiogram (ECG); however, there have been very few studies [8],[9],[10] where a short term ECG recording of 5 min has been used for analysis. Our aim was to study the prospect of using short term HRV analysis for early diagnosis of CADN.

   Materials and Methods Top

Using a comparative cross-sectional design, this pilot study on a small number of subjects was carried out to demonstrate that this approach of assessing autonomic neuropathy is scientifically and economically practicable. A total of 30 male patients with type 2 diabetes with duration of diabetes of 1-5 years with random blood glucose concentration random blood sugar ≥200 mg/dl (11.1 mmol/L) or fasting blood sugar ≥126 mg/dl (7 mmol/L) in the age group of 30-65 years were chosen, from the medicine outpatient clinic. Patients did not have any symptoms of autonomic neuropathy like orthostatic hypotension, exercise intolerance, etc. The 30 controls chosen from medical college campus were healthy nondiabetics who were matched with the study group for age and sex. Institutional Ethical Committee Clearance was taken. Athletes, those who practice yoga or exercises, those with history of cardiovascular, respiratory, psychiatric diseases and consumption of alcohol and tobacco or any medications that affect the autonomic nervous activity were excluded.

Subjects were asked to abstain from caffeine for at least 12 h as it would stimulate sympathetic nerves. They reported to study after refraining from food for 2 h to avoid confronting effect on parasympathetic nerves. [11] All subjects were informed about the noninvasive procedure of recording, aim of the study and consent was obtained from them. Height was measured to the nearest 0.1 cm without footwear using vertically movable scale. Weight was measured to the nearest 100 g using a digital scale and body mass index (BMI) was calculated. HbA1c in cases and controls was measured by high-performance liquid chromatography to know the glycemic control over a prolonged period. Heart rate and blood pressure were recorded.

Heart rate variability analysis was done using ECG recorded at rest in a supine position for 5 min. ECG was recorded using disposable Ag/AgCl electrodes. ECG data in standard lead II configuration was acquired using portable ECG data acquisition equipment (Niviqure Meditech Systems, Bangalore, India). The data gathered was edited manually for artefacts. Frequency and time-domain analysis was performed using Kubios HRV analysis software. Kubios HRV is advanced and easy to use software for HRV analysis. The software supports several input data formats for ECG data and beat-to-beat RR interval data. It includes an adaptive QRS detection algorithm and tools for artefact correction, trend removal and analysis sample selection. The software computes all the commonly used time-domain and frequency-domain HRV parameters. The ECG derived respiratory frequency is also computed, which is important for reliable interpretation of the analysis results. [12]

The power was calculated in two bands: The 0.15-0.4 Hz band of RR power considered as high frequency (HF) reflects parasympathetic nerve activity to the heart, whereas 0.04-0.15 Hz considered as low frequency (LF) band was believed to reflect at least in part, sympathetic nervous activity to the heart. The ratio of LF:HF represents a measure of the balance of sympathetic and parasympathetic function. [13] Parameters recorded by time-domain analysis were the mean heart rate, standard deviation of all R-R intervals (SDNN), root mean square of successive RR-interval differences (RMSSD), number of intervals differing by >50 ms from adjacent interval (NN50), and percentage of NN50 (pNN50). [14]

Statistical analysis was done using IBM SPSS Statistics for Windows, Version 20.0. (IBM Corp., Armonk, NY, USA) Comparison of the data between type 2 diabetics and nondiabetic groups was done by independent t-test. Correlation of HR, systolic blood pressure (SBP), diastolic blood pressure (DBP), LF power and HF power with HbA1c was done by Pearson's correlation. P < 0.05 was considered as statistically significant.

   Results Top

A comparison of anthropometric indices between diabetics and nondiabetics is shown in [Table 1]. Age, height (Ht.), and weight (Wt.) did not differ significantly between diabetics and nondiabetics. BMI (P = 0.048) and HbA1c (P = 0.032) were significantly higher in diabetics.
Table 1: Comparison of anthropometric indices in type 2 diabetics and nondiabetics

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Regarding short term HRV, it was observed that all time-domain measures - SDNN (P = 0.007), RMSSD (P = 0.002), NN50 (P < 0.001) and pNN50 (P < 0.001) were significantly lower in the diabetes patients when compared to the nondiabetic subjects. In frequency-domain analysis total power (TP) (P = 0.003), LF (P = 0.008) and HF powers (0.003) were decreased in diabetes patients. However, LF and HF power in normalized units remained comparable in diabetics and nondiabetics. Furthermore, LF/HF ratio remained comparable in the two groups. HR, SBP and DBP also did not differ in both groups [Table 2].
Table 2: Comparison of HR, SBP, DBP and parameters of HRV between type 2 diabetics and nondiabetics

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Diastolic blood pressure increased significantly with increased HbA1c levels (r = 0.486, P = 0.006). There was a negative, but insignificant correlation between LF power (r = −0.053, P = 0.783), HF power (r = −0.241, P = 0.199) and HbA1c levels.

   Discussion Top

Short term HRV analysis by both frequency and time-domain analysis showed that HRV was reduced in type 2 diabetics. SDNN, which is considered a global variability indicator was low in asymptomatic type 2 diabetic patients when compared to nondiabetic subjects. RMSSD, NN50 and pNN50, which are indicative of parasympathetic activity were less in diabetics. TP, LF power and HF power were also reduced in them. However, LF/HF ratio was comparable between the two groups. This indicates that diabetics have impaired autonomic modulation of heart rate, which heralds the development of cardiac autonomic neuropathy in them.

Studies using HRV in diabetics have demonstrated reduced HRV measures, similar to the results in the present study. However, most of these studies have been done using long term ECG recordings. A study by Kudat et al. showed that all time and frequency-domain parameters are reduced in diabetics. [6] Hsiao et al. had also reported that frequency-domain parameters are reduced in diabetics with or without symptoms of autonomic neuropathy, but reduction was more pronounced in those with symptoms and those with micro vascular complications. [15] Al-Hazimi et al. have demonstrated that all time-domain parameters were reduced in diabetics. [16] All these studies used 24 h ECG recording for analysis; however, we could record similar results in our study using a 5 min recording of ECG, which seems to be easier and more feasible.

Mudassir and Laxmi had also carried out HRV analysis in diabetics using 5 min. Recording. [8] However, they had studied only frequency-domain parameters (TP, LF power, HF power and LF/HF ratio), whereas we recorded both time and frequency-domain parameters. Short term recordings of ECG are preferably analyzed by frequency-domain analysis. [9] However, SDNN, RMSSD, NN50 and pNN50 have also been measured reliably from short term recordings of 5 min. [10] Furthermore, together these parameters help us to determine the branch of the ANS affected.

In our study, HF power as well as RMSSD, NN50 and pNN50, which are all indicative of parasympathetic activity are reduced. LF power is also reduced in diabetics in our study. Some studies suggest that LF, when expressed in normalized units, is a quantitative marker of sympathetic modulations; while, other studies view LF as reflecting both sympathetic activity and vagal activity. [9] LF/HF was comparable between the groups. Thus, the results of our study indicate involvement of both branches of ANS, but predominantly the parasympathetic branch of ANS, which is in accordance with the view that early in the natural history of type 2 diabetes there is impairment of parasympathetic function, but later with the progression of disease, sympathetic function also gets impaired. [17],[18]

A weak association has been shown to exist between HRV and HbA1c in our study. Though HbA1c is referred to as a chronic glycemic indicator, it gives an idea of glycemia control of 2-3 months only. However, our patients have been having a history of diabetes mellitus for a period of 1-5 years, and a single value of HbA1c cannot convey information about their blood sugar levels in all these years.

Heart rate variability is a noninvasive electrocardiographic marker reflecting the activity of the sympathetic and vagal components of the ANS on the sinus node of the heart. It expresses the total amount of variations of both instantaneous HR and RR intervals (intervals between QRS complexes of normal sinus depolarizations). Thus, HRV analyses the tonic baseline autonomic function. In a normal heart with an intact ANS, there will be continuous physiological variations of the sinus cycles reflecting a balanced sympthovagal state and normal HRV. Changes in activity in the afferent and efferent fibers of the ANS, and in local neural regulation contribute to sympathovagal imbalance that is reflected by a diminished HRV. [19] In CADN, there may be a functional abnormality or organic structural damage to the different components of the ANS, resulting in reduced HRV. [20]

Disorders of polyol metabolism, fatty acid metabolism, accumulation of glycated proteins, decrease of endoneural circulation, oxidative stress, destruction of nerve growth factors and autoimmune mechanisms are the various proposed pathological mechanisms of diabetic neuropathy. [21]

   Conclusion Top

This study shows that there is an impairment of cardiac autonomic nerves, both sympathetic and parasympathetic in asymptomatic type 2 diabetic patients. Short term analysis of HRV is a simple and easy method for early detection of this impairment. It is our view that short term HRV analysis should be incorporated as early as possible in the routine screening process of a diabetic patient, and should be performed periodically. A larger predictive study is justified based on the findings of this study.

   References Top

1.Vinik AI, Erbas T. Recognizing and treating diabetic autonomic neuropathy. Cleve Clin J Med 2001;68:928-30, 932, 934.  Back to cited text no. 1
2.American Diabetes Association and American Academy of Neurology: Report and recommendations of San Antonio Conference on diabetic neuropathy (Consensus Statement). Diabetes 1988;37:1000-4.  Back to cited text no. 2
3.Pfeifer MA, Weinberg CR, Cook DL, Reenan A, Halter JB, Ensinck JW, et al. Autonomic neural dysfunction in recently diagnosed diabetic subjects. Diabetes Care 1984;7:447-53.  Back to cited text no. 3
4.Howorka K, Pumprla J, Haber P, Koller-Strametz J, Mondrzyk J, Schabmann A. Effects of physical training on heart rate variability in diabetic patients with various degrees of cardiovascular autonomic neuropathy. Cardiovasc Res 1997;34:206-14.  Back to cited text no. 4
5.Maser R, Lenhard M, DeCherney G. Cardiovascular autonomic neuropathy: the clinical significance of its determination. Endocrinologist 2000;10:27-33.  Back to cited text no. 5
6.Kudat H, Akkaya V, Sozen AB, Salman S, Demirel S, Ozcan M, et al. Heart rate variability in diabetes patients. J Int Med Res 2006;34:291-6.  Back to cited text no. 6
7.Lafitte MJ, Fevre-Genoulaz, Srikanta SS, Punitha L, Vidyanand S. 500 heart beats for assessing diabetic autonomic neuropathy. Int J Diabetes Dev Ctries 2005;25:113-7.  Back to cited text no. 7
8.Mudassir M, Laxmi AN. A comparative study of heart rate variability in diabetic subjects and normal subjects. Int J Biomed Adv Res 2012;3:640-4.  Back to cited text no. 8
9.Task Force of European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996. Heart rate variability, standards of measurement, physiological interpretation, and clinical use. Circulation 1996;93:1043-65.  Back to cited text no. 9
10.Nunan D, Sandercock GR, Brodie DA. A quantitative systematic review of normal values for short-term heart rate variability in healthy adults. Pacing Clin Electrophysiol 2010;33:1407-17.  Back to cited text no. 10
11.Yadav RK, Gupta R, Deepak KK. A pilot study on short term heart rate variability & its correlation with disease activity in Indian patients with rheumatoid arthritis. Indian J Med Res 2012;136:593-8.  Back to cited text no. 11
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12.Tarvainen MP, Niskanen JP, Lipponen JA, Ranta-Aho PO, Karjalainen PA. Kubios HRV - Heart rate variability analysis software. Comput Methods Programs Biomed 2014;113:210-20.  Back to cited text no. 12
13.Shenoy JP, Shivakumar J, Kanmani TL, Shailaja M, Mirajkar A, Pai PG. Mental stress induced changes in autonomic nervous activity in normotensive offsprings of hypertensive parents. J Clin Diagn Res 2011;5:1537-41.  Back to cited text no. 13
14.Evrengül H, Tanriverdi H, Dursunoglu D, Kaftan A, Kuru O, Unlu U, et al. Time and frequency domain analyses of heart rate variability in patients with epilepsy. Epilepsy Res 2005;63:131-9.  Back to cited text no. 14
15.Hsiao JY, Tien KJ, Hsiao CT, Weng HH, Chung TC, Hsieh MC. The relationship between diabetic autonomic neuropathy and diabetic risk factors in a Taiwanese population. J Int Med Res 2011;39:1155-62.  Back to cited text no. 15
16.Al-Hazimi A, Al-Ama N, Syiamic A, Qosti R, Abdel-Galil K. Time-domain analysis of heart rate variability in diabetic patients with and without autonomic neuropathy. Ann Saudi Med 2002;22:400-3.  Back to cited text no. 16
17.Vinik AI, Maser RE, Ziegler D. Autonomic imbalance: Prophet of doom or scope for hope? Diabet Med 2011;28:643-51.  Back to cited text no. 17
18.Freccero C, Svensson H, Bornmyr S, Wollmer P, Sundkvist G. Sympathetic and parasympathetic neuropathy are frequent in both type 1 and type 2 diabetic patients. Diabetes Care 2004;27:2936-41.  Back to cited text no. 18
19.Sztajzel J. Heart rate variability: A noninvasive electrocardiographic method to measure the autonomic nervous system. Swiss Med Wkly 2004;134:514-22.  Back to cited text no. 19
20.Vinik AI, Ziegler D. Diabetic cardiovascular autonomic neuropathy. Circulation 2007;115:387-97.  Back to cited text no. 20
21.Schönauer M, Thomas A, Morbach S, Niebauer J, Schönauer U, Thiele H. Cardiac autonomic diabetic neuropathy. Diab Vasc Dis Res 2008;5:336-44.  Back to cited text no. 21


  [Table 1], [Table 2]


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