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Address for correspondence:

Yasin Turker, MD, Uzunmustafa M. 827. S. No:5 D:2, 81010 Düzce, Turkey. E-mail: dryasinturker@hotmail.com

Received 22 August 2012; revision accepted for publication 31 October 2012.

INTRODUCTION

Patients with diabetes mellitus (DM) are at an increased risk of sudden cardiac death (SCD) partly explained by cardiac autonomic neuropathy (CAN)1-3.

Heart rate variability and heart rate recovery in patients with type 1 diabetes mellitus

Yasin TURKER1, MD; Yusuf ASLANTAS1, MD; Yusuf AYDİN2, MD; Hilmi DEMİRİN3, PhD; Ali KUTLUCAN4, MD; Hakan TİBİLLİ1, MD; Yasemin TURKER5, MD; Hakan OZHAN1, MD.1Dept. of Cardiology, Faculty of Medicine, Duzce University, Duzce, Turkey; 2Dept. of Internal Medicine and Endocrinology and Metabolism, Faculty of Medicine, Duzce University, Duzce, Turkey; 3Dept. of Biochemistry and Clinical Biochemistry, Faculty of Medicine, Duzce University, Duzce, Turkey; 4Dept. of Internal Medicine, Faculty of Medicine, Duzce University, Duzce, Turkey; 5Family Medicine Centre, Duzce, Turkey.

Objective Patients with diabetes mellitus (DM) are at an increased risk of sudden cardiac death (SCD) partly explained by cardiac autonomic neuropathy (CAN). There have been fewer studies to evaluate CAN using heart rate variability (HRV) and heart rate recovery (HRR) in patients with type 2 DM. To our knowledge, there has been no study to investigate the association between HRR, HRV and type 1 DM. The purpose of this study was to exam-ine the changes in HRR and HRV measurements in type 1 diabetic patients.

Methods The study population consisted of 35 consecutive patients with type 1 diabetes and 35 sex- and age-matched non-diabetic controls. We performed electrocardiography, echocardiography, Holter analysis, exercise stress test, routine biochemical tests including haemoglobin A1c, high-sensitivity C-reactive protein and evaluated the clinical characteristics. HRR was calculated by subtracting the heart rate values at the fi rst minute of the recovery phase from the peak heart rate. Abnormal HRR was defi ned as HRR ≤ 18 beats. The HRV analysis was performed in both time domain and frequency domain.

Results In HRV analysis, type 1 diabetic patients had signifi cantly lower time domain [SDNN (P = 0.041), SDANN (P = 0.016), r-MSSD (P < 0.001), pNN50 (P < 0.001)] and frequency domain [total power (P = 0.002), VLF (P < 0.001), LF (P < 0.001), HF (P = 0.001), LF/HF (P = 0.034)] HRV parameters as compared to controls. In logistic regression analysis, the HRR (OR 0.927, 95% CI 0.872 to 0.985, P = 0.014), METs (OR 0.562, 95% CI 0.355 to 0.890, P = 0.014), pNN50 (OR 0.729, 95% CI 0.566 to 0.941, P = 0.015) and HF (OR 0.952, 95% CI 0.911 to 0.994, P = 0.027) were independently associated with type 1 DM.

Conclusion The results of this study showed that HRV parameters and HRR were signifi cantly reduced in patients with type 1 versus healthy controls. We found that HRV parameters correlated with HRR in type 1 diabetic patients. There is a relationship between CAN and infl ammation and also, there may be a relationship between CAN and intensive glycaemic control according to this study.

Keywords Heart rate recovery – heart rate variability – type 1 diabetes mellitus.

CAN results from damage to the autonomic nerve fibres that innervate heart and blood vessels, and results in abnormalities in heart rate control and vascular dynamics4. Reduced heart rate variability is the earliest indicator of CAN5. Attenuated heart rate recovery (HRR) following maximal exercise test is a predictor of mortal-ity in healthy adults and in those referred for diagnostic testing6. There have been few studies to evaluate CAN using heart rate variability (HRV) and HRR in patients with type 2 DM7,8. To our knowledge, there has been no study to investigate association among HRR, HRV and type 1 DM. The purpose of this study was to examine the changes in HRR and HRV measurements in type 1 diabetic patients.

Acta Cardiol 2013; 68(2): 145-150 doi: 10.2143/AC.68.2.2967271

Y. Turker et al.146

cardiologists. Recordings were analysed for arrhythmias and HRV. The HRV analysis was performed in both time domain and frequency domain. The HRV analysis was performed in time and frequency domains accord-ing to the Task Force of the European Society of Car-diology and North American Society of Pacing and Electrophysiology12. The following time domain param-eters: mean R–R intervals; standard deviations of all N–N intervals (SDNN); standard deviations of the aver-ages of N–N intervals (SDANN), the root mean square of the difference in successive R–R intervals (r-MSSD), proportion derived by dividing the number of interval differences of successive N–N intervals greater than 50 ms by the total number of N–N intervals (pNN50) and frequency domain parameters: variance of all NN inter-vals approximately (total power); power in the very low frequency range (VLF); power in the low frequency range (LF); power in the high frequency range (HF); LF/HF were calculated. Ventricular arrhythmia was defined as occurrence of any of the following: ventricular premature contractions (VPCs), VPC cou-plets, and ventricular tachycardia documented by Holter analysis, or by electrocardiography. Atrial arrhythmia was defined as occurrence of any of the following: atrial premature contractions (APCs), atrial couplets, supraventricular tachycardia, atrial flutter or fibrillation documented by Holter analysis or by elec-trocardiography.

Echocardiography

In all participants, transthoracic M-mode, two-dimensional, pulsed-wave, continuous wave and colour Doppler echocardiographic examinations were per-formed using a General Electric Vingmed Vivid 7 (GE Ultrasound), using 2.5–3.5 MHz transducers. Left ven-tricular end-diastolic and end-systolic diameters and left atrial diameters were determined from two-dimen-sional images, according to published criteria. Left ven-tricular EF was calculated using the modified Simpson’s method. Diastolic dysfunction was defined according to the guidelines of the American Society of Echocar-diography and taking into consideration the mean age of our population13.

Blood sampling

Blood samples were drawn at initial presentation from the antecubital vein. Whole blood count and rou-tine biochemical tests including haemoglobin A1c (HbA1c) were performed. High-sensitivity C-reactive protein (hs-CRP) was measured with chemiluminescent immunometric assay using an IMMULITE® 1000 Auto-analyzer (Siemens, Germany).

METHODS

Study population

The study population consisted of 35 consecutive patients (17 women; mean age 29.8 ± 7.7 years) with type 1 diabetes and 35 sex- and age-matched non-diabetic controls (19 women; mean age 27.9 ± 5.6 years). Type 1 DM patients were diagnosed according to the American Diabetes Association criteria9. Exclusion criteria were acute coronary syndrome, congestive heart failure, coex-isting occlusive CAD, valvular heart disease, pacemaker implantation, persistent atrial fibrillation, frequent atrial or ventricular premature beats, conduction defects, Wolff- Parkinson-White syndrome, peripheral vascular diseases, contraindications to exercise stress testing, orthopedic or neurological limitations, pericarditis, peripheral neuropathy, congenital heart disease, use of beta-adrenergic blocking agents and digoxin, alcohol abuse, and renal, hepatic, or thyroid disease. The study protocol was approved by the Ethics Committee of the Duzce University, and every subject signed a consent form. We performed electrocardiography, echocardio-graphy, Holter analysis, exercise stress test, and routine biochemical tests, and evaluated their clinical charac-teristics.

Exercise testing

Patients underwent ‘symptom-limited’ exercise tread-mill testing (model 425-AC; Nihon Kohden; Tokyo, Japan) using the standard and modified Bruce proto-cols10. During each exercise stage and recovery stage, symptoms, blood pressure, heart rate, cardiac rhythm, and exercise workload in metabolic equivalents (METs) were recorded. Chronotropic response was assessed on the basis of the proportion of heart rate (HR) reserve used as peak exercise, or (peak HR-resting HR)/(220-age-resting HR); a value of ≤ 0.80 was considered as chronotropic incompetence. Heart rate recovery was calculated by subtracting the heart rate values at the first minute of the recovery phase from the peak heart rate. Abnormal HRR was defined as HRR ≤ 18 beats. Func-tional capacity was measured in metabolic equivalents, and abnormal exercise capacity was defined by the fol-lowing formula: METs = 18.0 − 0.15 X age, consistent with previous studies7,11.

Holter analysis

The 24-h digital Holter recording was performed once for each sample on a Rozinn RZ 153 (Rozinn Electronics, Inc., Glendale, NY, USA) with H4W® com-puting software and independently analysed by two

Heart rate variability and heart rate recovery with type 1 DM 147

0.911 to 0.994, P = 0.027) were independently associated with type 1 DM. HRR was significantly correlated with total cholesterol (r: 0.584, P < 0.001), SDNN (r: 0.444, P = 0.008), pNN50 (r: 0.454, P = 0.006), hs-CRP (r: –0.341, P = 0.004), fasting plasma glucose (r: –0.485, P = 0.013) and HbA1c (r: –420, P = 0.013) in the type 1 DM patients group. Hs-CRP was correlated with SDANN (r: –0.324, P = 0.006), LF (r: –0.414, P < 0.001), HF (r: –0.389, P < 0.001) and HRR (r: –0.341, P = 0.004) in the type 1 DM patients group. Fasting plasma glucose was correlated with HRR (r: –0.485, P = 0.013), VLF (r: –409, P = 0.016), SDANN (r: –0.375, P = 0.026) and HbA1c was correlated with HRR (r: –420, P = 0.013), VLF (r: –0.507, P = 0.002), SDANN (r: –370, P = 0.021) in the type 1 diabetic group.

DISCUSSION

The main findings of this study were that HRR values and time domain and frequency domain HRV param-eters were reduced in type 1 diabetic patients.

Diabetic autonomic neuropathy is one of the least recognized and understood complications of diabetes mellitus (DM) due to its association with a variety of adverse sequela including fatal and nonfatal cardiovas-cular events and overall mortality14-16. CAN is the most clinically important form of diabetic autonomic neu-ropathy17. Early detection of subclinical autonomic dysfunction in diabetic patients is therefore of vital importance for risk stratification and subsequent man-agement for prevention of serious adverse conse-quences18. In the study by O’Brien et al., individuals with CAN experienced a 3.3-fold higher mortality rate versus those without over the 5-year follow-up interval19. Samp-son et al. compared the mortality experience of those with and without abnormal heart rate variability and observed a 2.6-fold higher mortality rate for those with the abnormality CAN versus the without abnormality CAN group20. Dysfunction of the autonomic nervous system appears to be associated with an increased risk of mortality and morbidity in diabetic patients4. Cardiac autonomic neuropathy is a common complication of type 1 diabetes.

There are several techniques available for assessing CAN21. A battery of cardiovascular reflex tests, spectral analysis of heart rate and blood pressure variability and baroreceptor cardiac reflex sensitivity have been used to assess autonomic function in diabetic patients22. Exer-cise HRR is a useful, straightforward method and a highly reproducible tool in assessing parasympathetic tone. Moreover, its feasibility has been validated in several studies23,24. Among the different available non-invasive techniques for quantifying the autonomic

Statistical analysis

Statistical analysis was performed by means of SPSS software, version 11.0 (SPSS Inc., Chicago, Illinois, USA). Continuous variables are expressed as mean ± SD, categorical variables are presented as percentages and frequencies. The student t-test was used to compare the continuous variables, and the chi-square test for cate-gorical variables between two groups. Logistic regression analysis was performed to identify the predictors of type 1 DM. The confounders, which had a significance at P < 0.10 in univariate tests, were included as covariate in regression analysis. The Spearman correlation test was used to identify correlation between continuous vari-ables. A P value of less than 0.05 was considered statis-tically significant.

RESULTS

A total of 35 consecutive patients (17 women; mean age 29.8 ± 7.7 years) with type 1 diabetes, and sex- and age-matched 35 non-diabetic controls (19 women; mean age 27.9 ± 5.6 years) were included in the study. Baseline demographic, clinical and laboratory characteristics of the study population are listed in table 1. Type 1 diabetic patients showed significantly higher levels of fasting plasma glucose (P < 0.001), HbA1c (P < 0.001) and hs-CRP (P = 0.012) than healthy controls. The mitral E max/A max ratio was significantly lower in type 1 dia-betic patients compared to controls (P = 0.005). The percentage of diastolic dysfunction in type 1 diabetics was significantly higher than in healthy controls (23% vs. 3%, P = 0.013). Table 2 shows exercise stress testing and HRV parameters. Exercise duration (P < 0.001), METs (P = 0.001), resting HR (P = 0.006), peak HR (P = 0.032), HRR (P = 0.002), and the percentage of impaired HRR (P = 0.023) were significantly different between type 1 diabetic patients and controls. In HRV analysis, type 1 diabetic patients had significantly lower time domain [SDNN (P = 0.041), SDANN (P = 0.016), r-MSSD (P < 0.001), pNN50 (P < 0.001)] and frequency domain [total power (P = 0.002), VLF (P < 0.001), LF (P < 0.001), HF (P = 0.001), LF/HF (P = 0.034)] HRV parameters as compared to controls. The incidence of arrhythmia, was higher in patients with type 1 diabetes (40% vs.17.1%, P = 0.063). Eleven patients had VPCs, 2 patients had APCs and 1 patient had VPCs and APCs in type 1 diabetic patients. Five patients had VPCs, 1 patient had VPCs and APCs in the control group.

In logistic regression analysis, the HRR (OR 0.927, 95% CI 0.872 to 0.985, P = 0.014), METs (OR 0.562, 95% CI 0.355 to 0.890, P = 0.014), pNN50 (OR 0.729, 95% CI 0.566 to 0.941, P = 0.015) and HF (OR 0.952, 95% CI

Y. Turker et al.148

controls. Additionally, we found that HRV parameters were correlated with HRR in type 1 diabetic patients. Similar to our study, Javorka et al., reported that short-term HRV is reduced in patients with type 1 diabetes mellitus28. Additionally, it is shown that patients with type 1 DM have a lower HRV on 24-hour ambulatory recordings than both healthy subjects and patients with chronic stable angina pectoris29.

Madsen et al.,30 found that C-reactive protein and heart rate variability are independently associated. This may support a link between low-grade inflammation and autonomic dysfunction and Araujo et al.31 reported that the lower heart rate variability correlated with a higher concentration of hs-CRP. In this study, type 1 diabetic patients showed significantly higher levels of

modulation of cardiovascular function, HRV has emerged as a simple, non-invasive and powerful tool to evaluate the sympathovagal balance at the sinoatrial level25,26. HRV is arising as a simple and non-invasive measure of the autonomic impulses, representing one of the most promising quantitative markers of the auto-nomic balance. The widest possible use, the cost-effec-tiveness in the application of the technique and ease of data acquisition makes the HRV an interesting option for interpretation of the functioning of the CAN and a promising clinical tool to assess and identify impair-ments on health27. In this study, we investigated CAN in type 1 diabetic patients with both HRR and HRV. We showed that HRV parameters and HRR were signifi-cantly reduced in patients with type 1 versus healthy

Table 1 Demographic, clinical, and laboratory characteristics of the study patients.

Characteristics Type 1 diabetic patients (n = 35) Controls (n = 35) P value

Mean age, years 29.7 ± 7.6 27.8 ± 5.6 0.244

Female/male, (n/n) 17/18 19/16 0.811

Hypertension, n (%) 2 (5.7) 1 (2.9) 0.555

Current smoker; n (%) 14 (40) 10 (28.6) 0.450

Hypercholesterolaemia, n (%) 4 (11.4) 2 (5.7) 0.673

BMI (kg/m2) 24.7 ± 3.0 24.5 ± 3.8 0.668

BMI ≥ 30 kg/m2, n (%) 3 (8.6) 4 (11.4) 0.690

Haemoglobin (g/dl) 13.4 ± 1.2 13.2 ± 1.7 0.566

BUN (mg/dl) 13.3 ± 3.3 12.0 ± 2.5 0.700

Serum creatinine (mg/dl) 0.74 ± 0.11 0.73 ± 0.17 0.777

Fasting plasma glucose (mg/dl) 186.1 ± 102.9 93.8 ± 5.25 < 0.001

HbA1c (%) 9.26 ± 2.71 5.25 ± 0.37 < 0.001

FT3 (pg/ml) 3.0 ± 0.5 2.81 ± 1.0 0.849

FT4 (ng/dl) 1.15 ± 0.16 1.24 ± 0.48 0.515

TSH (μIU/ml) 1.87 ± 1.3 1.34 ± 0.5 0.293

Total cholesterol (mg/dl) 180.0 ± 40.2 161.2 ± 29.9 0.340

HDL (mg/dl) 54.7 ± 14.2 54.1 ± 24.6 0.598

LDL (mg/dl) 98.4 ± 30.1 84.11 ± 23.1 0.330

Triglycerides (mg/dl) 145.4 ± 78.8 116.9 ± 64.1 0.093

Magnesium (mmol/l) 2.0 ± 0.28 1.97 ± 0.14 0.590

Calcium (mmol/l) 9.6 ± 0.48 9.8 ± 0.43 0.900

Potassium (mmol/l) 4.48 ± 0.42 4.35 ± 0.23 0.121

Sodium (mmol/l) 138.2 ± 1.97 139.2 ± 2.0 0.960

Hs-CRP (mg/l) 1.49 ± 1.21 0.88 ± 0.84 0.012

LVEDD (mm) 42.4 ± 4.6 44.2 ± 4.7 0.113

LVESD (mm) 27.0 ± 3.5 28.1 ± 2.3 0.108

LA (mm) 29.7 ± 2.8 30.4 ± 2.5 0.261

Ejection fraction (%) 65.3 ± 5.1 63.9 ± 3.7 0.186

Mitral E max/A max (cm/s) 1.19 ± 0.35 1.39 ± 0.24 0.005

Diastolic dysfunction, n(%) 8 (23) 1 (3) 0.013

BMI: body mass index, FT3: free triiodothyronine, FT4: free thyroxine, Hs-CRP: high-sensitivity C-reactive protein, HbA1c: haemoglobin, A1c: LA, left atrial diameter, LVEDD: left ventricular end-diastolic diameter, LVESD: left ventricular end-systolic diameter, TSH: thyroid-stimulating hormone. Values are mean ± SD (range) or n (%).

Heart rate variability and heart rate recovery with type 1 DM 149

our study. Intensive treatment can prevent the develop-ment of CAN in patients with type 1 diabetes.

CONCLUSIONS

The results of this study showed that HRV parameters and HRR were significantly reduced in patients with type 1 DM versus healthy controls. We found that HRV parameters correlated with HRR in type 1 diabetic patients. There is a relationship between CAN and inflammation, and also, there may be a relationship between CAN and intensive glycaemic control according to this study.

CONFLICT OF INTEREST: none.

hs-CRP than healthy controls. Similarly as in the previ-ous studies30,31 we found a significant negative correla-tion between hs-CRP and SDANN, LF, HF in the type 1 DM patients group.

Shishehbor et al. reported that HRR is associated with triglyceride-to-HDL cholesterol ratio and identifies patients with insulin resistance who are at increased risk of death32. In the present study, HRR was significantly negatively correlated with only serum total cholesterol level in the lipid panel.

In a recent study it has been shown that fasting plasma glucose remained significantly associated with HRR in patients with coronary heart disease33. Capillary glucose and HbA1c correlated negatively with SDNN/NN at recovery, after age and sex adjustment in another recent study8. Similarly, in type 1 diabetic patients sig-nificant correlations were observed between HRR, VLF, SDANN and both fasting plasma glucose and HbA1c in

Table 2 Exercise stress testing parameters, and time and frequency-domain measures.

Characteristics Type 1 diabetic patients (n = 35) Controls (n = 35) P value

Exercise duration (min) 7.01 ± 1.43 8.35 ± 1.36 < 0.001

METs 9.44 ± 1.5 10.71 ± 1.52 0.001

Resting HR (bpm) 91.2 ± 15.3 82.3 ± 8.9 0.006

Resting SBP (mm Hg) 118.7 ± 8.2 121.1 ± 12.9 0.355

Resting DBP (mm Hg 75.5 ± 5.9 78.0 ± 9.5 0.187

Peak HR (bpm) 173.1 ± 13.3 179.7 ± 12.1 0.032

Peak SBP (mm Hg) 164.5 ± 12.1 169.5 ± 17.9 0.186

CI ≤ 0.80, n (%) 3 (8.6) 1 (2.9) 0.614

HRR 24.8 ± 10.8 32.6 ± 9.4 0.002

HRR < 18, n (%) 10 (28.6) 2 (5.7) 0.023

Holter fi ndings

Maximum HR (bpm) 137.4 ± 15.2 139.1 ± 22.6 0.711

Average HR (bpm) 79.1 ± 8.8 78.4 ± 7.5 0.716

Minimum HR (bpm) 52.4 ± 6.4 51.1 ± 8.2 0.458

SDNN (ms) 148.6 ± 42.0 168.7 ± 38.5 0.041

SDANN (ms) 91.5 ± 34.0 108.7 ± 23.0 0.016

r-MSSD (ms) 38.6 ± 16.2 55.7 ± 16.9 < 0.001

pNN50 (%) 9.17 ± 5.7 17.6 ± 5.7 < 0.001

Total power (103) (ms2) 2.46 ± 1.1 3.27 ± 1.0 0.002

VLF (103) (ms2) 1.27 ± 0.48 2.34 ± 0.97 < 0.001

LF (ms2) 474.1 ± 179.6 788.4 ± 268.4 < 0.001

HF (ms2) 165.4 ± 72.4 233.0 ± 90.2 0.001

LF/HF 3.11 ± 0.94 3.63 ± 1.08 0.034

Arrhythmias 14 (40.0) 6 (14.1) 0.063

CI: chronotropic incompetence, DBP: diastolic blood pressure, HF: power in the high frequency range, HR: heart rate, HRR: heart rate recovery index, LF: power in the low frequency range, METs: metabolic equivalents, pNN50: proportion derived by dividing the number of interval differences of successive N–N intervals greater than 50 ms by the total number of N–N intervals, r-MSSD: the root mean square of the difference in successive R–R intervals, SBP: systolic blood pressure, SDANN: standard deviations of the averages of N–N intervals, SDNN: standard deviations of all N–N intervals, VLF: power in the very low frequency range. Values are mean ± SD (range) or n (%).

Y. Turker et al.150

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