Cardiac Autonomic Neuropathy in Type 2 Diabetes Mellitus: Prevalence Profile and Independent Risk Factor Impacts

Dr. U. S. Ghosh, Dr. Santa Subhra Chatterjee, Dr. Samar Banerjee

Background :
Data regarding cardiac autonomic neuropathy (CAN) in type 2 diabetes mellitus (T2DM) and its risk factor associations are sparse in Indian context, though it has serious consequences. This study was planned to assess CAN status and independent risk factor impacts on the tests.

Methods :
Two hundred forty-two patients of T2DM were studied. Assessment was as total patients and by gender, duration and smoking status segregation. Risk factors studied were age of patient, duration of T2DM, body mass index (BMI), lipids, systolic and diastolic blood pressure, HbA1c, urinary albuminñcreatinine ratio (ACR) and retinopathy. The autonomic function tests were heart rate variability on standing, Valsalva maneuver and deep breathing (parasympathetic), and blood pressure variability with standing and hand grip (sympathetic). The duration segments were less than 5 years, between 5 to 10 years and more than 10 years.

Results :
Prevalence of parasympathetic abnormalities was higher (33.5% versus 18.2%), females had higher sympathetic abnormalities (24.7% versus 4.1%) though parasympathetic tests were similar. Nonsmokers had higher autonomic abnormalities; highest duration had higher sympathetic dysfunction. The predominant impacts were from lipids, age, duration of diabetes and insulin resistant status. High triglyceride affected both autonomic functions in all patients nearly uniformly. Age was important in males, while duration in females. Higher BMI and male gender seemed protective. Blood pressure, smoking and HbA1c had segmental impacts. Separate role of ACR and retinopathy is questionable.

Conclusion: Modifiable risk is insulin resistant state. Lean females with longer duration are probably of high risk. Testing protocols are lacking.

Keywords: Type 2 Diabetes Mellitus, Cardiac Autonomic Neuropathy, Risk Factor Impacts.

Introductions:
Cardiac autonomic neuropathy (CAN) is a common form of autonomic neuropathy, causing abnormalities in heart rate control and vascular dynamics; it often manifests early progresses faster in type 2 diabetes mellitus (T2DM).[1] CAN is a less recognized, less understood and often overlooked complication of T2DM despite its significant negative impacts.[2] The prevalence of CAN in T2DM is not precisely known. Tests, on an average, reveal a prevalence of 20-60%.[3,1] Risk factors include hyperglycemia, duration of diabetes, hypertension, dyslipidemia, age, body mass index (BMI), smoking and physical fitness.[4,5] Cumulative glucotoxicity is the major factor; hyperinsulinemia is probably more important in the early stage.[6] It may be associated with proliferative retinopathy and is commoner in nephropathy.[7] Strict glycemic control improves CAN significantly.[8] Data regarding prevalence profiles and independent risk factor impacts on each CAN test in different patients segments are hardly available from the Indian subcontinent, most of them reveal prevalence.[9,10,3] This study was aimed at assessing the prevalence patterns and independent impact of prevalent risk factors on CAN tests, in T2DM in general as well as by their gender, duration and smoking status segregation.

Methods :
All patients of clinical T2DM above the age of 30 years, attending for the first time with or without therapy, were included from the diabetes clinic of NRS Medical College of Kolkata between October 2009 and January 2010 and worked up over the next 2 months. A detailed history was taken and clinical examination was done. Patients with significant comorbidities like COPD, severe hypertension, overt heart or renal failure, cerebrovascular accident, proliferative retinopathy, active foot disease, heart rate modifying and ACEI therapy were excluded.[2,11] A resting ECG, fasting serum creatinine and urine microscopy for pus cell and RBC was done for these initially selected patients – those with dysrrhythmia, ischemic heart disease, abnormally cellular urine and a serum creatinine above 2 mg% were excluded.[3,10]
The study parameters were age, gender, duration of T2DM, BMI, total cholesterol (TC), LDL cholesterol (LD), HDL cholesterol (HD), triglyceride (TG), systolic (SBP) and diastolic (DBP) blood pressure, HbA1c, urinary albumincreatinine ratio (ACR), smoking status, insulin resistance (IR) level, retinopathy, gender and CAN tests along with a total autonomic score (ANC).[3] The parameters were studied in total patients as well as by gender, smoking status and duration segregation. The duration segregation was done arbitrarily into those less than 5 years duration (D1), between 5 to 10 years (D2) and above 10 years (D3). Five CAN tests were – heart rate variation with Valsalva manoeuvre (VRV), deep breathing (RRV) and standing up (SRV) for parasympathetic, and SBP response to standing (BPS) up and DBP to sustained handgrip (BPG) for sympathetic function – and were performed according to established formats.[12,13] The tests were segregated into normal, borderline and abnormal.[13]
Age was documented from the voter ID card. BMI was calculated by the standard formula of age in years divided by height in meter squared. Duration of diabetes was estimated from history and previous medical records. Serum lipids and creatinine were assayed by fasting (overnight 8 to 14 hours) clotted blood in auto-analyzer (EBRAS 600) and HbA1c by Biorad HPLC i10. A single test of morning spot urine ACR was done by estimation the urinary microalbumin level by immuno-turbidimetry (Transasia) and creatinine by gas kinetic method (Transasia). Fasting serum insulin was measured by elisa. Insulin resistance was calculated by HOMA-IR: as the product of blood glucose (fasting blood glucose) and immunoreactive insulin: (fasting blood glucose (mg per 100ml) x fasting serum Insulin (mU/l)/405). Retinopathy was assessed by indirect fundoscopy with a dilated pupil and no separate grading was done. Patients giving a history of having more than one cigarette per day persistently for more than 5 years and still continuing were considered as smokers.[14] Patients underwent CAN testing after a mandatory rest of 30 minutes without smoking or tea, and usually in the fasting state.[15] Autonomic neuropathy scoring (ANC) was done by assigning 0 for normal value, 0.5 for borderline abnormality and 1 for absolute abnormal value in each parameter studied.[16] The total of the 5 tests were computed for each patient and taken as the autonomic neuropathy score of that patient (range from 0 to 5).

Statistical Analysis :
Univariate data for the continuous variables were presented as mean ± standard deviation and the difference was assessed by Students T test for normally distributed continuous variables. Discrete variables were put as percentage and differences assessed by Z score of the standard error of proportions. More than 2 groups were compared by one way Anova with post hoc analysis by Bonferroni modification. Bivariate analysis by linear correlation between the various CAN parameters (of each group) and the different risk parameters were calculated by Pearson’s Correlation. The risk factors for CAN were examined by multiple linear regression analyses with stepwise removal of the independent variables to find the most significant ones contributing to the individual CAN parameters (the dependent variable) in a particular group; a negative a and t value were considered to have a negative – approximately 8 to 12 patients per independent variable were considered. These independent variables were selected from the results of Pearsons correlation coefficient values – the best correlating variables were chosen according to the calculated number of cases in each patient group.
Positive smoking status and male gender were given a score of 1 while non-smoking status and female gender were given a score of 0 while inputting them as variables in the linear regression analysis. A two-tailed p>0.05 was considered statistically significant. A negative impact on regression or correlation of a factor on SRV, VRV, RRV and BPG, and a positive impact or correlation on BPS and ANC are considered adverse. However the reverse in each situation was considered protective except for HD.

Result Analysis :
A total of 268 patients were selected for the study of which 26 could not complete the study protocol primarily due to failure of performing the CAN tests. There were 145 males and 97 females, 106 were smokers, and the duration segments D1, D2, D3 had 54, 108 and 80 patients respectively. Age group range was from 31 to 75 years and duration from 0.75 to 17 years. Around 24% of patients did not reveal any abnormality in autonomic testing, 6% had one borderline abnormality while nearly 20% had two borderline abnormal tests. Around 46.3% had an ANC of 2 or above. Written consent was taken from all the patients and the study was approved by the institutional ethical committee in accordance with Helsinki declaration. Table 1 depicts prevalence distribution of the various CAN parameters in the different patient groups. Table 2 enumerates clinical and biochemical characteristics of the various groups. Tables 3, 4, 5 and 6 shows the correlations of CAN parameters in total patients, the genders, the three duration groups and the smokers and nonsmokers respectively.

Z Score Analysis :
With increasing duration prevalence of all CAN parameters increased but there is hardly any further increase beyond 10 years especially for the parasympathetic abnormalities; though BPS is an exception (p=0.001). Earliest abnormal change was observed with SRV (p=0.002) followed by RRV. Borderline abnormalities are more common in females; abnormal BPG is significantly higher (p=0.002) in them. Adverse CAN parameter prevalence is more common in nonsmokers especially SRV, RRV and BPG (p=0.01). (Table1.)

T-Test analysis :
Age, SBP, DBP, HbA1c, and ACR progressively increased with duration. TC, LD, TG, IR and retinopathy were highest while HD lowest in D3. BMI of the duration groups were similar, Males differed from females by having higher TG and smokers. Nonsmokers were of higher age, duration, TC and LD but had lower ACR and BMI. (Table2.)

Pearson Correlation :
In total patients age, duration and lipids had significant association with both variety of autonomic function tests (AFT) abnormality; male gender, retinopathy and DBP were correlated predominantly with sympathetic tests; HbA1c associations were variable; SBP was with BPG and ANC, ACR with RRV and IR with VRV (Table 3). In females AFT abnormalities correlated better with age, retinopathy and DBP while smoking, SBP and HbA1c was better in males; ACR and IR being poor in both (Table 4). In the duration groups – D1: AFT correlated with BMI, LD and smoking, D2: with duration and lipids and D3 with age and BMI. The male gender status had significant correlations with VHR in D1, with BPS and BPG in D2 and none in D3. The blood pressures, ACR, IR, retinopathy and HbA1c did not have any significant correlation (Table 5). In smokers HbA1c, retinopathy, male gender, IR and SBP adversely correlated with parasympathetic AFT; in nonsmokers it was age, ACR and BPB for both AFT (Table 6).

Linear Regression Analysis :
In total patients the independent variables were age, male gender, duration, TC, HD, TG, LD, smoking, HbA1c, ACR, IR, SBP, DBP and retinopathy. The significant independent impacts were-1) SRV: age and LD had negative but TC, BMI, and duration of T2DM had a positive; 2) VRV: TG, IR, LD and SBP had negative while HbA1c, BMI, TC, and male gender had positive; 3) RRV: duration, TG and age had negative while LD had positive; 4) BMI, male gender and TC had negative while TG, LD and duration had positive on BPS; 5) BPG: age, male gender BMI and TC had positive while duration, TG and LD were negative ; and 6) ANC: duration, IR, LD and TG had positive while BMI, male gender and TG had negative. The adjusted R2 was highest for ANC and RRV-0.49 and 0.45 respectively.
In males, the independent variables were age, BMI, duration of T2DM, ACR, IR, smoking, LD,TG, HD SBP and retinopathy and the significant independent impacts were – 1)SRV: age, SBP and HbA1c were negative while ACR and smoking positive; 2) VRV: TG, IR and SBP was negative while age, HD and BMI was positive; 3) RRV: duration, TG, HD and ACR was negative but none was positive ; 4) BPS: none were negative though duration, BMI, and TG were positive; 5) BPG: SBP, duration and TG had negative while BMI, ACR, HD and age had positive impacts; 6) ANC: BMI, HD and smoking had a negative while IR, SBP and TG had positive. The adjusted R2 was highest for ANC, VRV and RRV-0.63, 0.48 and 0.47 respectively. In females, the independent variables were age, duration, BMI, DBP, HbA1c, IR, retinopathy, HD, LD and TG and the significant independent impacts were : 1) SRV : age, BMI, LD and DBP had negative and HDL, TG, IR and duration had positive; 2) VRV: age, TG and DBP had negative while HbA1c and duration had positive; 3) RRV:TG and age had negative but it was positive for IR and retinopathy; 4) BPS: HD, LD and HbA1c had negative but TG had positive; 5) BPG: HDL and TG had positive 6) ANC: HD, IR and HbA1c was negative while age positive. The adjusted R2 was highest for SRV and RRV- 0.71 and 0.61 respectively. For duration D1 the independent variables used were TG, HD, IR, BMI, smoking and age and the significant independent impacts were – 1) SRV: TC, HD and age had negative while IR and smoking were positive; 2) VRV: TC was negative ; 3) RRV:TC, IR, HD and smoking had positive; 4) BPS : Smoking had negative impact; 5) BPG: TC had negative but smoking positive; 6) ANC: Smoking and IR had negative and age and TC were positive. Adjusted R2 was highest for SRV and ANC- 0.58 and 0.49 respectively. For D2 the independent variable were age, BMI, duration, SBP, IR, HbA1c, smoking, TC, TG and HD and the significant impacts were – 1) SRV: TC and HbA1c had negative while HD and TG positive; 2)VRV: age, BMI, HD, HbA1c and smoking were positive while TG, IR and SBP were negative; 3) RRV: Duration, age, HD, TG and smoking had negative but BMI was positive; 4) BPS: HD, age and BMI had negative but duration was positive; 5) BPG: age, smoking and HD were positive; 6) ANC: age and BMI were negative and TC, TG, IR and duration were positive. Adjusted R2 was highest for RRV and VRV-0.67 and 0.57 respectively. In D3, the independent variables were age, BMI, duration, gender, ACR, smoking, HD and TG and the independent impacts were – 1) SRV: age had negative and BMI, TG had positive; 2) VRV: age and TG were negative and none positive; 3) RRV: age, duration and BMI were negative and none positive; 4) BPS: age and duration had negative while BMI and ACR had positive; 5) BPG: age negative and BMI positive; 6) ANC: BMI was negative and age positive. The adjusted R2 was highest for RRV, BPS and ANC- 0.64, 0.62 and 0.62 respectively. For smokers, the independent variables were age, BMI, duration, gender, SBP, IR, HbA1c, TG, LD and HD and the significant independent impacts were – 1) SRV: IR and LD had negative and male gender positive; 2) VRV: IR, TG and duration had negative while male gender positive; 3) RRV: TG, SBP, age, duration and HbA1c had negative and LD was positive; 4) BPS: male gender had negative but duration, IR and TG had positive; 5) BPG: duration had negative while male gender and age had positive; 6) ANC: male gender and BMI had negative while duration, TG and IR had positive. The adjusted R2 was highest for ANC and RRV-0.59 and 0.51 respectively. In nonsmokers, the independent variables were age, BMI, duration, gender, SBP, DBP, IR, ACR, retinopathy, HbA1c, TG, HD, and LD. The independent impacts were – 1) SRV: age and LD were negative while duration, TG and HD were positive; 2) VRV: TG was negative, and BMI, SBP and HbA1c were positive; 3) RRV: age, duration and TG had negative but LD, SBP and DBP were positive ; 4) BPS:HD, BMI, HbA1c and LD had negative but duration and TG had positive; 5) BPG: HD, LD, BMI and male gender were positive and duration negative; 6) ANC:BMI, HbA1c and HD had negative while duration and TG were positive. Adjusted R2 was highest for ANC and RRV – 0.54 and 0.56 respectively.

Discussion :
CAN severity increased with increasing duration of diabetes irrespective of the gender or smoking status but durations more than 10 years, does not necessarily lead to increase in CAN abnormalities linearly.[17,18] It could be that these patients had higher comorbidities and were excluded at the beginning leading to selection bias or it could be that patients with higher prevalence of CAN were eliminated from the population due to higher mortality beyond this duration. At any duration above 5 years, around 50% patients did not reveal any abnormality in CAN tests irrespective of gender or smoking status.[19] Parasympathetic functions were affected early, predominantly due to alterations of SRV and to a lesser extent RRV and VRV.[11,20] With increasing duration, prevalence of RRV and sympathetic abnormality increased.[17] This could either be the natural history of CAN progression in T2DM or just a reflection of lower sensitivity of the sympathetic function tests.[4,20]
Parasympathetic tests were primarily affected by lipid abnormalities of raised TG, LD and low HD, and age; sympathetic dysfunction was predominantly related to increasing duration, TG and to some extent LD levels.[20,21] Independent factor impacts were minimally evident for sympathetic dysfunction in females where BPG abnormality was significant.[11] Increasing age predominantly affected the parasympathetic AFT especially in females and nonsmokers; in durations above 10 years age it also affected sympathetic AFT especially in males.[18,22] Longer duration of T2DM was detrimental mainly for the sympathetic AFT in males, irrespective of smoking status, and the intermediate duration segment. Neither age nor duration could explain the cardiosympathetic dysfunction in females.[23] Higher BMI seemed protective for sympathetic AFT abnormality in males, nonsmokers and beyond 5 years of duration. Impact of BMI has been rather confusing in the literature; probably in Asians low BMI is detrimental and a waist circumference as a marker of obesity may be more valid marker of abnormal AFT.[24,25,26,8]
Increasing SBP and DBP predominantly affects parasympathetic AFT (SRV, VRV) in males and females respectively; probably the impact of age overshadows their impacts.[22,27] The exact cause for this divergence would not be ascertained and does not fit with usual reports. Increasing TG and LD nearly uniformly affected both AFT in all patient groups; low HD predominantly affected the parasympathetic AFT. Probably, HD impacts are more in type 1 diabetes.[20,27] The role of BMI and hypertension might also be more in T1DM.[28] The impact of high TG, low HD and to some extent the high IR and blood pressure levels indicate of the persistent association of CAN with the insulin resistant state, not only in the early stages but also at durations of 10 years or more.[20,21,26]
Though there were significant correlations, ACR, retinopathy status and HbA1c had little independent impact in AFT variability, especially the sympathetic component.[22,25] HbA1c predominantly affected RRV and SRV in male smokers of intermediate duration; ACR and smoking status had adverse impact on RRV in males and intermediate duration respectively.[22] Though both CAN and ACR can affect cardiovascular mortality, probably they do it by different pathways and either of these two may not necessarily have an impact on the progression of the other.[29] Though cumulative hyperglycemia is an important cause of advanced CAN, a point estimation of HbA1c may not be reflective and a mean of serial HbA1c measurements may be more meaningful.[30,31,32,19] The IR status predominantly affected VRV, ANC and to a lesser extent BPS.[20,21,22] Retinopathy status did not have any independent impact; this may be due to lack of grading and exclusion of proliferative eye diseases or it is not associated etiologically with CAN which is often proposed.[7,29,30,31] Smokers paradoxically had less prevalence of AFT dysfunction than nonsmokers. This may be because the smokers had significantly lower levels of other risk factors or it could be that they had higher comorbidities and were excluded from the primary study population or population in general due to early death. The risk factors studied could explain a significant 50-60% of the AFT alterations but predominantly the parasympathetic components, except in D3.[11,15]

Conclusion :
Though AFTs can be altered early, they are more significantly altered after some time.[10,12,18] Lipid abnormalities, age and duration of diabetes are the prime offenders; higher BMI and male gender are protective.[6,24,33] Blood pressure, HbA1c level and smoking may not have major independent impacts. ACR and retinopathy are just associated complications and probably not related to CAN.[27,29] Clinical or biochemical insulin resistant state is probably a definite area of intervention irrespective of the duration of T2DM.[15,20,21] The parasympathetic and sympathetic tests are not affected uniformly; though parasympathetic components are affected early, sympathetic abnormalities are fewer so probably tests need refinement.[17,23] There is noticeable absence of large datasets on CAN, both internationally and nationally, compared to vascular diseases, retinopathy or nephropathy in T2DM. Perhaps this is an indicator of the inadequate priority accorded to this very important component of diabetic complications; this may be related to lack of awareness or suitable guidelines regarding testing or both.[34] Future need is standardization of the tests in Indian perspectives and development of appropriate guidelines for their routine use.[34]

Table: 1 Distribution of CAN in the various patient groups.

Vas Score

NSm – non-smoker, D1= patients of duration < 5 years, D2= patients of duration 5-10 years, D3 = patients of duration > 10 years, SRV- Heart rate response to standing, VRV- Valsalva ratio, RRVHeart rate variation with deep breathing, BPS- SBP response to standing, BPG- DBP response to sustained hand grip, N – normal value of test parameter, B – borderline abnormal, A – abnormal value of the test, figure in parenthesis (n) is number of patients.

Table 2: General Characteristics of the various groups.

Table 2: General Characteristics of the various groups.

BMI- body mass index, TC- total cholesterol, TG- triglyceride, HD- HDL cholesterol, LD- LDL cholesterol, Durat- duration, Fem – female, Sm- smoker, NSm – non-smoker, D1= patients of duration < 5 years, D2= patients of duration 5-10 years, D3 = patients of duration > 10 years, yrs- years, n= number of patients, * = significant p value, SBP – systolic blood pressure, DBP- diastolic blood pressure, ACR – albumin/creatinine ratio, Retin-retinopathy.

Table 3 : Risk Factor Correlations of CAN – Total Patients.

Table 3 : Risk Factor Correlations of CAN - Total Patients.

BMI- body mass index, Durat- duration, TC- total cholesterol, TG- triglyceride, HD- HDL cholesterol, LD- LDL cholesterol, Sm- smoker, SBP – systolic blood pressure, DBP- diastolic blood pressure, ACR – albumin/creatinine ratio, Retin-retinopathy, IR – insulin resistance level, SRV- Heart rate response to standing, VRV- Valsalva ratio, RRV- Heart rate variation with deep breathing, BPSSBP response to standing, BPG- DBP response to sustained hand grip, ANC – total autonomic score, Fem G – female gender, figure in parenthesis () is the p value, (000) indicates p value < 0.001.

Table 4: Correlations of risk factors with gender.

Table 4: Correlations of risk factors with gender.

BMI- body mass index, TC- total cholesterol, TG- triglyceride, HD- HDL cholesterol, LD- LDL cholesterol, Sm- smoker, SBP – systolic blood pressure, DBP- diastolic blood pressure, ACR – albumin/creatinine ratio, Retin-retinopathy, IR – insulin resistance level, SRV- Heart rate response to standing, VRV- Valsalva ratio, RRV- Heart rate variation with deep breathing, BPS- SBP response to standing, BPG- DBP response to sustained hand grip, ANC – total autonomic score, figure in parenthesis () is the p value, (000) indicates p value < 0.001.

Table-5: Risk factor correlation of the 3 duration groups.

Table-5: Risk factor correlation of the 3 duration groups.

D1= patients of duration < 5 years, D2= patients of duration 5-10 years, D3 = patients of duration > 10 years BMI- body mass index, TC- total cholesterol, TG- triglyceride, HD- HDL cholesterol, LD- LDL cholesterol, Sm- smoker, SBP – systolic blood pressure, DBP- diastolic blood pressure, ACR – albumin/creatinine ratio, Retin-retinopathy, IR – insulin resistance level, SRV- Heart rate response to standing, VRV- Valsalva ratio, RRV- Heart rate variation with deep breathing, BPS- SBP response to standing, BPG- DBP response to sustained hand grip, ANC – total autonomic score, figure in parenthesis () is the p value, (000) indicates p value < 0.001.

Table – 6 : Risk factor correlation of the Smoker and Non-smokers.

Vas Score

BMI- body mass index, TC- total cholesterol, TG- triglyceride, HD- HDL cholesterol, LD- LDL cholesterol, SBP – systolic blood pressure, DBP- diastolic blood pressure, Male G – male gender, ACR – albumin/creatinine ratio, Retin-retinopathy, IR – insulin resistance level, NSm- non-smoker, SRV- Heart rate response to standing, VRV- Valsalva ratio, RRV- Heart rate variation with deep breathing, BPS- SBP response to standing, BPG- DBP response to sustained hand grip, ANC – total autonomic score, figure in parenthesis () is the p value, (000) indicates p value <0.001.

References

  1. 1. Maser RE, Mitchell BD, Vinik AI, Freeman R. The Association between Cardiovascular Autonomic Neuropathy and Mortality in Individuals with Diabetes: A Meta-Analysis. Diabetes Care 2003; 26:1895-1901.
  2. 2. Spallone V, Menzinger G. Diagnosis of Cardiovascular Autonomic Neuropathy in Diabetes. Diabetes 1997;46: 567-76.
  3. 3. Pappachan JM, Sebastian J, Bino BC, Jayaprakash K, Vijayakumar K, Sujathan P etal. Cardiac Autonomic Neuropathy in Diabetes Mellitus: Risk Factors and Utility of Corrected QT Interval in ECG for its Diagnosis. Postgrad Med J 2008;84:205-10.
  4. 4. Vinik AI, Maser RE, Mitchell BD, Freeman R. Diabetic Autonomic Neuropathy. Diabetes Care 2003; 26(5):1553-79.
  5. 5. Valensi P, Paries J, Attali JR. Cardiac Autonomic Neuropathy in Diabetic Patients: Influence of Diabetes Duration, Obesity and Microangiopathic Complications – The French Multicentre Study. Metabolism 2003; 52(7):815-820.
  6. 6. Sima AAF. Does insulin play a role in cardiovascular autonomic regulation? Diabetes Care 2000; 23:724-5.
  7. 7. Mehta S, Mathur D, Chaturvedi M. Incidence of Cardiac Autonomic Neuropathy in NIDDM. J Ind Med Assoc 2002; 100:141-3.
  8. 8. Carnethon MR, Prineas RJ, Temprosa M, Zhang Z-M, Uwaifo G, Molitch ME etal. The Association Among Autonomic Nervous System Function, Incident Diabetes, and Intervention Arm in the Diabetes Prevention Program. Diabetes Care 2006; 29(4): 914-19.
  9. 9. Jyotsna VP, Sahoo A, Sreenivas V, Deepak KK. Prevalence and Pattern of Cardiac Autonomic Dysfunction in Newly Detected Type 2 diabetes Mellitus Diabetes Res Clin Pract 2009;83(1):83-88.
  10. 10. Ahamed VIT, Dhanasekaran P, Naseem A, Karthick NG, Jaleel TKA, Joseph PK. Quantification of Heart Rate Variability: A Measure Based on Unique Heart Rates. Int J Biol Life Sci 2008; 4(4):201-4.
  11. 11. Maser RE, Lenhard MJ. Review: Cardiovascular Autonomic Neuropathy due to Diabetes Mellitus: Clinical Manifestations, Consequences and Treatment. J Clin Endocrinol Metab 2005; 90(10) : 5896-5903.
  12. 12. Ziegler D, Laux G, Dannehl K, Sp¸ler M, M¸hlen H, Mayer P et.al. Assessment of Cardiovascular Autonomic Function: Age-related Normal Ranges and Reproducibility of Spectral Analysis, vector Analysis and Standard Test of Heart Rate Variation and Blood Pressure Responses. Diabet Med 1992; 9: 166-85.
  13. 13. Ewing DJ, Clarke BF. Diagnosis and Management of Diabetic Autonomic Neuropathy. Br Med J 1982; 285:916-18.
  14. 14. Astrup AS, Tarnow L, Rossing P, Hansen BV, Hilsted J, Parving H. Cardiac Autonomic Neuropathy Predicts Cardiovascular Morbidity and Mortality in Type 1 Diabetic Patients with Nephropathy. Diabetes Care 2006; 29(2):334-39.
  15. 15. Schonauer M, Thomas A, Morbach S, Niebauer J, Schonauer U, Thiele H. Cardiac Autonomic Diabetic Neuropathy. Diab Vasc Dis Res. 2008; 5(4):336-44.
  16. 16. Bellavere F, Bosello G, Fedele D, Cardone C, Ferri M. Diagnosis and Management of Diabetic Autonomic Neuropathy. Br Med J 1983;287: 61.
  17. 17. Pop-Busui R. Cardiac Autonomic Neuropathy in Diabetes. A Clinical Perspective. Diabetes Care 2010; 33(2) :434-41.
  18. 18. Khatoon N, Kumar BS , Hazari MAH. Cardiovascular Autonomic Neuropathy in Patients with Diabetes Mellitus. Int J Pharma Bio Sci 2010;1(3):1-7.
  19. 19. Khandelwal E, Jaryal AK, Deepak KK. Pattern and Prevalence of Cardiovascular Autonomic Neuropathy in Diabetics Visiting a Tertiary Care Referral Centre in India. Indian J Physiol Pharmacol.2011;55(2):119.
  20. 20. Kempler P. Autonomic Neuropathy: A Marker of Cardiovascular Risk. Br J Diabetes Vasc Dis 2003;3(2):84-90.
  21. 21. Gottsater A, Ahmed M, Fernlund G, Sunkvist G. Autonomic Neuropathy in Type 2 Patients is Associated with Hyperinsulinemia and Hypertriglyceridemia. Diabet Med 1999;16:49-54.
  22. 22. Subbalakshmi N K, Adhikari P M R, Rajeev A, Asha K, Jeganathan P S. Independent Predictors of Cardiac Parasympathetic Dysfunction in Type 2 Diabetes Mellitus. Singapore Med J 2008; 49 (2):121-28.
  23. 23. Okada S, Tanokuchi S, Higuchi T, Ogino Y, Ichiki K, Ishii K etal. Cardiosympathetic neuropathy is independent of cardioparasympathetic neuropathy in patients with non-insulin-dependent diabetes mellitus. J Int Med Res. 1995;23(5):364-8.
  24. 24. Thi NN, Paries J, Attali JR, Valensi P. High Prevalence and Severity of Cardiac Autonomic Neuropathy in Vietnamese Diabetic Patients. Diabet Med. 2005;22(8):1072-8.
  25. 25. Makary SM, Selim HA, El-Wazir YM, Mahmoud AE. Physiologic assessment of cardiac autonomic reflexes in diabetics. Suez Canal Univ Med J 1999; 2(1) : 61-72.
  26. 26. Chen HT, Lin HD, Won JG, Lee CH, Wu SC, Lin JD etal. Cardiovascular Autonomic Neuropathy, Autonomic Symptoms and Diabetic Complications in 674 Type 2 Diabetes. Diabetes Res Clin Pract 2008;82(2):282-90.
  27. 27. Faulkner MS, Quinn L, Fritschi C. Microalbuminuria and Heart Rate Variability in Adolescents with Diabetes. J Pediatr Health Care 2010;24(1):34-41.
  28. 28. Rolim LCSP, de S· JR, Chacra AR, Dib SA. Diabetic Cardiovascular Autonomic Neuropathy: Risk Factors, Clinical Impact and Early Diagnosis. Arq Bras Cardiol 2008; 90(4): e23-e31.
  29. 29. Vinik AI, Maser RE, Ziegler D. Autonomic Imbalance: Prophet of Doom or Scope for Hope? Diabet Med. 2011; 28(6):643-51.
  30. 30. Basu AK, Bandyopadhyay R, Chakrabarti S, Paul R, Santra S. A Study on the Prevalence of Cardiac Autonomic Neuropathy in Type-2 Diabetes in Eastern India. JIACM 2010; 11(3):190-4.
  31. 31. Valensi P, Huard JP, Giroux C, Attali JR. Factors Involved in Cardiac Autonomic Neuropathy in Diabetes Patients. J Diabetes Complications 1997;11(3):180-7.
  32. 32. Felicio JS, Santos FM, de Souza ACCB, FelÌcio KM, Ribeiro AB, Zanella MT. Autonomic neuropathy tests correlate with left ventricular mass and cardiac diastolic function in normotensive patients with type 2 diabetes mellitus and without left ventricular hypertrophy. Exp Clin Cardiol 2010; 15(1):e5-e9.
  33. 33. Toyry JP, Niskanen LK, Mantysaari MJ Lansimies EA, Uusitupa MI. Occurrence, predictors and clinical significance of autonomic neuropathy in NIDDM: ten year follow-up from the diagnosis. Diabetes. 1996;45(3):308-15.
  34. 34. Sucharita S, Bantwal G, Idiculla J, Ayyar V, Vaz M. Autonomic Nervous System Function in Type 2 Diabetes Using conventional Clinical Autonomic Tests, Heart Rate and Blood Pressure Measures. Indian J Endocr Metab 2011; 15(3):198-203.