Low prevalence of cardiac autonomic neuropathy in Type 1 diabetic patients without nephropathy

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1 Low prevalence of cardiac autonomic neuropathy in Type 1 diabetic patients without J. A. Meinhold, E. Maslowska-Wessel, R. Bender and P. T. Sawicki Abstract Department of Metabolic Diseases and Nutrition, WHO Collaborating Centre for Diabetes, Heinrich-Heine-University DuÈ sseldorf, Germany Accepted 12 December 2000 Aim To assess the prevalence of cardiac autonomic neuropathy (CAN) in Type 1 diabetic patients with and without. Methods Sixty-six consecutive patients without, with incipient or overt and a diabetes duration between 21 and 31 years were examined. Heart rate variability (HRV) as measure for CAN was investigated with short-term spectral analysis in the low-frequency (LF) band (0.06±0.15 Hz), re ecting sympathetic and vagal activity, and high-frequency (HF) band (0.15±0.50 Hz), re ecting vagal activity. HRV was expressed as spectral power (ms 2, log-transformed). Normal, age-corresponding reference values were established in 184 controls. QTc intervals and dispersion were measured. Results After adjustment for age, there was no signi cant difference between healthy controls and patients without. After further adjustment for diabetes duration, HbA 1c, hypertension and treatment with b-blockers, HRV in both frequency bands decreased with evidence of. LF band (supine): patients without 5.56 (4.89±6.21) (least squares means and 95% con dence interval (CI)), incipient 5.72 (5.15± 6.29) and overt 4.11 (3.27±4.96). HF band (supine): without 5.93 (5.26±6.60), incipient 5.99 (5.41±6.57) and overt 4.84 (4.00±5.68). Signi cant differences were found for patients without and with incipient compared with those with overt in the LF band and between patients with incipient compared with those with overt in the HF band. QTc intervals and QTc dispersion increased signi cantly with increasing. Conclusions Long-term Type 1 diabetes without was not associated with impaired cardiac autonomic function in our study. However, in those with, a loss of both vagal and sympathetic activity was present, and the severity of CAN correlated positively with more advanced. Diabet. Med. 18, 607±613 (2001) Keywords cardiac autonomic neuropathy, Type 1 diabetes, diabetic Correspondence to: Jutta Meinhold MD, Department of Metabolic Diseases and Nutrition, Heinrich-Heine-University of DuÈ sseldorf, PO Box , DuÈ sseldorf, Germany. meinhold@uni-duesseldorf.de 607

2 608 CAN in Type 1 diabetes with and without J. A. Meinhold et al. Table 1 Clinical characteristics and laboratory values of Type 1 diabetic patients without, patients with incipient and overt without with incipient with overt Women / men 6/18 12/14 9/7 Age (years) (21±62) (24±58) (30±52) Diabetes duration (years) (10±36) (11±50) (22±47) Hypertension (n (%)) 2 (8) 19 (73) 16 (100) (BP* > 140/90 mmhg) Diabetic retinopathy (n (%)) 10 (42) 20 (77) 15 (94) (non-prolif. + prolif.) Serum creatinine (mmol/l) (70.7±106.1) (61.9±256.4) (88.4±397.8) Creatinine clearance (90±161) (52±193) (41±114) (ml/min per 1.73 m 2 ) Proteinuria (mg/24 h) (16±57) (66±480) (576±8786) HbA 1c (%) (5.6±9.2) (5.4±9.5) (6.1±10.4) *Blood pressure. Means 6 SD (range). Introduction Cardiac autonomic neuropathy (CAN) plays an important role in the high cardiac mortality of diabetic patients with. Among other factors, it may trigger `sudden death'. Knowledge about the prevalence of CAN in Type 1 diabetic patients is incomplete. It was shown that in those with overt, CAN is common [1±3]. This association was rst shown by Zander [1] and later by Molgaard [2,3]. Incipient seems to be associated with CAN as well, but to a lesser degree [1±3]. There is a controversy whether autonomic dysfunction in longterm Type 1 diabetic patients without is common or not [1±8]. The aim of this study was to investigate the prevalence of CAN in patients with long-standing Type 1 diabetes without when compared with those with incipient and overt. Particular consideration was given to confounding factors such as age, disease duration, metabolic control and hypertension, and QTc and QTc dispersion were also measured. Patients and methods Patients and controls Sixty-six consecutive patients with Type 1 diabetes were recruited from our out-patient clinic with the following inclusion criteria: age 20±60 years, body mass index (BMI) < 29 kg/m 2, diabetes duration of > 10 years and HbA 1c < 9%. Exclusion criteria were end stage renal failure, acute angina, myocardial infarction during the last 6 months, heart failure (NYHA II±IV), valvular heart disease, atrial brillation and ventricular extrasystoles > 10/h, smoking of more than 20 cigarettes per day, regular daily alcohol consumption of more than 20 g for women and 60 g for men, heavy alcohol consumption in the past, presence of neuropathy other than diabetic origin, acute infection and acute psychological stress. Heart failure was excluded clinically and if necessary veri ed with an echocardiogram. Patients were classi ed according to their urinary protein excretion into no (proteinuria < 61 mg/24 h), incipient (proteinuria 61±500 mg/24 h) and overt (proteinuria > 500 mg/24 h) [9]. Percentage of hypertension (blood pressure > 140/90 mmhg) corresponds to the proportion of patients treated with antihypertensives (Table 1). All hypertensive patients without were treated with b-blockers, 50% of them additionally with calcium channel blockers. Hypertensive patients with incipient (overt) were treated in 73% (81%) with b-blockers, in 46% (81%) with diuretics, in 23% (25%) with ACE inhibitors, in 15% (19%) with a-blockers, in 12% (25%) with calcium channel blockers and in 4% (19%) with centrally acting sympatholytic agents. All 184 healthy subjects were within the age of 20±60 years. They had no symptoms or clinical history of cardiopulmonary disease and did not take any medication. BMI was < 29 kg/m 2. The study design was approved by the local ethical committee; patients and controls gave their informed consent to participate in the study. Methods Assessment of CAN CAN was assessed by investigation of heart rate variability (HRV) with spectral analysis. This method enables the assessment of HRV in two different frequency bands (low frequency 0.06±0.15 Hz and high frequency 0.15±0.50 Hz). The lowfrequency band (LF) is attributed to vagal and sympathetic activity, the high-frequency band (HF) to vagal activity alone. Spectral analysis measures HRV as spectral power (ms 2 ).

3 Original article 609 We used the VariaPulse TF3 device (Sima Media Olomouc Ltd., Olomouc, Czech Republic). It transfers the recorded heart rate into infrared light signals which are transferred to a receiver connected to a computer. The window for spectrum calculation was 256 signals. For calculation of spectral power, it uses coarse-graining spectral analysis [10] and Fast Fourier Transformation. The heart rate was recorded over 15 min, with the rst and third 5-min phases in the supine position and the second 5-min phase standing. Normal, age-corresponding values for spectral power were established under the same study conditions as described below. Controls were divided into four groups from 20 to 29 years (group 2), 30±39 years (group 3), 40±49 years (group 4) and 50±60 years (group 5). Mean age in years was 25 in group 2, 34 in group 3, 44 in group 4 and 54 in group 5. Results of spectral power calculations were logtransformed. Mean values from the two supine phases were calculated. Quantiles were then computed for the HF and LF band for each age group. CAN was de ned to be present if the patients result in either the low or high-frequency band was below the 2.5% quantile of the age-corresponding control group. We used only values measured in the supine position, as reproducibility of the intraclass correlation coef cient indicated good reproducibility for the supine position (data not published). Calculation of QTc intervals and QTc dispersion In addition to measurement of HRV, we also measured QT intervals and calculated both QTc intervals and dispersion. QT intervals were measured from the beginning of the QRS complex to the end of the T wave; in case of an existing U wave, the QT interval was measured until the nadir between the T and the U wave. Three QT intervals were measured in each of the 12 leads of an electrocardiogram (50 mm/s speed), mean values calculated for each lead. QT intervals were corrected for heart rate with Bazett's formula. A mean value was calculated from the 12 QTc intervals for each patient. For calculation of QTc dispersion, the difference between the longest and the shortest QT interval of each lead was calculated; differences were corrected for heart rate and a mean value for QTc dispersion from the results of the 12 leads was calculated. Study protocol The following conditions were established on the study day: no severe hypoglycaemic or ketoacidotic episodes during the week before and no acute illness during the 48 h prior to assessment of CAN. All participants were asked to avoid heavy physical activity during the 24 h before the investigation. The patients were asked to avoid any hypoglycaemic blood glucose values (< 3.4 mmol/l) and were also instructed to avoid any consumption of alcohol during the last 12 h. They were asked not to smoke and not to drink caffeine-containing beverages on the study day. Insulin dosage and any other medication was left unchanged. Subjects were all examined in the same room between 2 p.m. and 6 p.m., without acoustical disturbance or uorescent light. Measurement of blood glucose and urine was performed always directly before the investigation. After a resting period of 10 min, supine blood pressure was measured and an electrocardiogram under resting conditions recorded. A 15-min spectral analysis was performed if blood glucose values were between > 4.5 and < 10 mmol/l and blood pressure < 160/ 90 mmhg. Laboratory measurements HbA 1c was determined with a high performance liquid chromatography (HPLC) method (reference range 4.2±6.1%). For estimation of proteinuria, a protein precipitation method with trichloroacetic acid (5%) and laserphotometric measurement was used. The upper normal value of this method is 60 mg/ 24 h. Values of proteinuria < 61 mg/24 h correspond to the cutoff level of 30 mg albuminuria in 24 h [9]. Before patients were included in the study, proteinuria was measured in a random urine sample and additionally in two 24-h urine samples without signs of urinary tract infection. Measurements of proteinuria were done within 3 months prior to inclusion in the study. Determination of creatinine in serum and urine was performed with the Jaffe method. For measurement of creatinine clearance corrected for body surface, patients collected urine over 24 h. Blood glucose measurements before examination were done with the glucose oxidase method (Glucose Analyzer II; Beckman Instruments, Munich, Germany). Statistical analysis For analysis of differences between patient groups and the control group, analysis of covariance (ANCOVA) was used. To control for the effect of confounding variables, we adjusted the difference between the groups for age, diabetes duration, hypertension and HbA 1c. If the overall statistical analysis of group differences was signi cant, pair-wise comparisons between the groups were done. As there are only three patient groups, this procedure controls the experiment-wise error rate in the strong sense for the multiple comparisons [11]. P-values < 0.05 were regarded as signi cant. For computations the SAS procedure GLM was used [12]. Results The clinical characteristics and laboratory values of the investigated 66 patients are given in Table 1. Values for spectral power of controls and patients adjusted only for age are given in Table 2. It shows that there is no signi cant difference between healthy controls and patients without. However, there is a signi cant difference between the controls and patients without compared with those patients with. Table 3 demonstrates spectral power values of patients after adjustment for age, diabetes duration, HbA 1c, hypertension and treatment with b-blockers: HRV decreased signi cantly in both frequency bands with progression of. Pair-wise comparisons between the groups showed the following results: in the LF band (supine position), patients with overt had signi cantly different values from those without and with incipient. In the LF band (standing position) and the HF band (supine position), patients with

4 610 CAN in Type 1 diabetes with and without J. A. Meinhold et al. Table 2 Heart rate variability in the low and high-frequency band (log spectral power, ms 2 ) of healthy controls and Type 1 diabetic patients without, with incipient and overt Log spectral power (ms 2 ) Healthy controls (n = 184) without with incipient with overt Low frequencyðsupine (3.5; 9.9) a (4.8; 8.2) a (1.9; 9.4) b (0.5; 6.4) c Low frequencyðstanding (1.7; 9.1) a (3.5; 7.8) a (1.6; 7.8) b (0.2; 6.0) c High frequencyðsupine (3.7; 10.2) a (4.1; 9.0) a (2.7; 9.5) b (2.4; 6.7) c High frequencyðstanding (1.1; 8.5) a (3.6; 7.6) a (1.8; 7.3) b (1.6; 6.0) c Log spectral power values of healthy controls and patients are adjusted for age. Data are means 6 SD (minimum; maximum). Means in the same line with a different letter (a, b, c) are signi cantly different. Signi cant differences are all P = Table 3 Heart rate variability in the low and high-frequency band (log spectral power, ms 2 ) in Type 1 diabetic patients without, with incipient and overt Log spectral power (ms 2 ) without with incipient with overt Low frequencyðsupine (4.89±6.21) (5.15±6.29) , 2 (3.27±4.96) Low frequencyðstanding 4.98 (4.27±6.68) (4.66±5.87) (2.94±4.71) High frequencyðsupine 5.93 (5.26±6.60) (5.41±6.57) (4.00±5.68) High frequencyðstanding 5.29 (4.60±5.97) 6.18 (4.59±6.77) 4.29 (3.43±6.15) Log spectral power values are adjusted for age, diabetes duration, HbA 1c, existence of hypertension and treatment with b-blockers. Least squares means from ANCOVA model with 95% con dence intervals. 1 Signi cant difference after pair-wise comparison of log spectral power (ms 2 ) between patients without vs. patients with overt for low frequency supine (P = ). 2 Signi cant difference after pair-wise comparison of log spectral power (ms 2 ) between patients with incipient vs. patients with overt for low frequency supine (P = ), low frequency standing (P = ), high frequency supine (P = ). incipient and overt had signi cantly different values. All other comparisons did not show signi cant differences. The age-corrected, individual spectral power of all patients in relation to age-adjusted normal values is shown in Fig. 1 (values not corrected for other confounding variables). Thirty percent of patients with incipient and 81% of patients with overt had pathological results (outside the 95% reference range) in the LF band, 31% and 75%, respectively, in the HF band (Fig. 2). However, all Type 1 diabetic patients without had values within the reference range in both frequency bands. QTc intervals and QTc dispersion were signi cantly longer in patients with incipient and overt in comparison with patients without (Table 3). However, there was only a weak correlation between the length of the QTc interval/dispersion and reduced HRV. In the LF band the correlation to the QTc interval was ±0.48, to the QTc dispersion ±0.34. In the HF band the correlation to the QTc interval was ±0.48 and to the QTc dispersion ±0.36. Discussion This cross-sectional study was designed to assess the prevalence of cardiac autonomic neuropathy in patients with long-term Type 1 diabetes with and without. Our results demonstrate that the patients with longterm Type 1 diabetes without did not have impairment of cardiac autonomic function. However, in those with, especially overt, a loss of both sympathetic and vagal activity was present. The lack of association between disease durationðin our cohort 21 yearsðand the presence of CAN con rms results of other studies performed with autonomic testing in the time and frequency domain [3, >13]. In the study by Molgaard et al. with 24 h investigation of CAN, healthy controls and normoalbuminuric patients with a disease duration of 14 years were found to have signi cant differences only in few of the investigated parameters in the time domain [3]. Hoffmann et al. measured HRV over 24 h and showed that it was not signi cantly different between controls and Type 1 diabetic subjects with a mean diabetes duration of 9 years [13]. Poulsen et al. measured

5 Original article 611 Table 4 Mean QTc interval and mean QTc dispersion in Type 1 diabetic patients without, with incipient and overt without with incipient with overt QTc interval (s ) QTc dispersion (s 1/2 ) Means 6 SD. 1 P = for difference between patients without vs. patients with incipient and overt. 2 P = for difference between patients without vs. patients with incipient and overt. Figure 1 Individual values of heart rate variability in the low frequency area in 66 Type 1 diabetic patients with and without. Plotted lines are quantiles for spectral power in the low frequency area, established in 184 healthy controls (HC). All given values for spectral power are results of measurements in the supine position. h, Without ; D, with incipient ; d, with overt. Figure 2 Individual values of heart rate variability in the high frequency area in 66 Type 1 diabetic patients with and without. Plotted lines are quantiles for spectral power in the high frequency area, established in 184 healthy controls (HC). All given values for spectral power are results of measurements in the supine position. h, Without ; D, with incipient ; d, with overt. reduced HRV in normoalbuminuric Type 1 diabetic patients with a mean diabetes duration of 18 years who had an albumin excretion rate > 4.2 mg/min [14]. However, no healthy control group was investigated to de ne normal values for the device, making any interpretation with regard to presence or absence of CAN in these patients impossible. Previous studies performed with bedside tests to investigate CAN support our results as well [8,15±17]. Many other investigators found an association between disease duration and the presence of CAN [4± 6,18±20]. Differences between our results and these studies may be due to various factors. In the present study, we carefully tried to control for factors associated with an alteration of autonomic function such as metabolic control and hypertension [5,18,21,22]. In addition, differences in results may be related to the technique applied to investigate CAN. Spectral analysis which was used in the present study or investigation of CAN in the time domain are more speci c and sensitive methods to diagnose autonomic dysfunction than bedside tests [2,23]. In our study we found an association between CAN and the presence of overt diabetic : patients with this condition had signi cantly lower values for heart rate variability. This could be shown for both sympathetic and vagal activity. Patients with incipient did not show signi cantly different results from patients without. This became evident only after adjustment of results with confounding variables. That result is in

6 612 CAN in Type 1 diabetes with and without J. A. Meinhold et al. contrast to the results of Molgaard. In his study, the prevalence of CAN in incipient was calculated to be > 50%, based on values for HRV corrected for age but not for other confounding variables [2]. Using the same approach for our data, we found lower percentages for incipient : approximately one-third of these patients showed signs of autonomic dysfunction (Figs 1 and 2). Percentages for overt were approximately equal to the results of Molgaard. All spectral analyses in this study were performed on patients taking their usual medication which essentially consisted of insulin and anti-hypertensive drugs. Most anti-hypertensives in uence HRV [24±26]. Therefore, we have adjusted for treatment with b-blockers which were used in the majority of patients with hypertension. Nevertheless, an additional in uence of the remaining anti-hypertensive medication (diuretics, ACE inhibitors, a-blockers and calcium antagonists) cannot be ruled out. b-blockers and ACE inhibitors for example increase HRV in the HF band and decrease it in the LF band [24±26], whereas the in uence of a-blockers, calcium antagonists and diuretics still has to be clari ed. In contrast to Molgaard et al., who investigated a similar cohort with 24 h analysis of HRV [2,3], we used shortterm spectral analysis. Our results show that use of the simpler short-term spectral analysis is also possible for the diagnosis of CAN. However, to assess the individual advantages of short- and long-term analysis, one would have to examine patients with both methods. In the present study, QTc interval and QTc dispersion were signi cantly prolonged in many patients with incipient and overt. However, the correlation between HRV in the LF or HF band and QTc prolongation was weak. This is probably because the QT interval is not only related to CAN. Other factors such as hypertension, coronary artery disease, electrolyte imbalance and/or myocardial wall stress in uid overload contribute to the length of the QT interval [27,28]. Therefore, QTc prolongation is only a moderately sensitive indicator of CAN, but highly speci c [29]. The clinical importance of prolonged QTc intervals and reduced HRV lies in the connection to increased mortality in Type 1 diabetes; for example, QTc dispersion is a useful predictor of patients with Type 2 diabetes and a high mortality risk [28]. For those with Type 1 diabetes and, QTc interval prolongation is associated with increased mortality [30]. Reduced HRV may contribute to `sudden death' Type 1 diabetes [31] and is associated with increased mortality in diabetes [32]. 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