Analysis of the association between glucose profiles and β-cell function for diabetic cardiovascular autonomic neuropathy in China

Ping Fang, Jingcheng Dong, Fangfang Zeng, Zihui Tang, Ping Fang, Jingcheng Dong, Fangfang Zeng, Zihui Tang

Abstract

Aims/introduction: The purpose of the present study was to investigate the severity of glucose profiles and β-cell function associated with diabetic cardiovascular autonomic neuropathy (DCAN) in a Chinese sample.

Materials and methods: A community-based, cross-sectional study to analyze the risk factors of DCAN was carried out with 455 individuals recruited from a Chinese population. The glucose profile risk score was calculated to identify the association between the severity of the glucose profiles and DCAN. The associations of the severity of the glucose profiles and β-cell function with DCAN were analyzed using multivariable logistic regression.

Results: Univariate analysis showed that the glucose profiles and homeostatic model assessment of insulin resistance were significantly associated with the DCAN outcome, respectively. Multivariable logistic regression showed that significant associations exist between glucose profile indices and DCAN, after controlling for potential confounding factors (P < 0.01 for all) in both models. Multivariable logistic regression also showed that parameters of β-cell function were associated with the DCAN outcome in the category model (P < 0.1 for all). The glucose profile risk score was independently and significantly associated with the DCAN outcome after controlling for confounding factors (P < 0.001 and P for a trend <0.001).

Conclusions: Our observations suggest that parameters of glucose profile indices and β-cell function are significantly and independently associated with DCAN, respectively. There was a tendency toward increased glucose profile risk score with increasing prevalence of DCAN.

Keywords: Diabetic cardiovascular autonomic neuropathy; Glucose profile; β-Cell function.

© 2016 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

Figures

Figure 1
Figure 1
Comparison of the prevalence of diabetic cardiovascular autonomic neuropathy (DCAN) according to glucose profile parameters. (a) Comparison of DCAN prevalence according to fasting plasma glucose (FPG). DCAN prevalence was 21.60%, 33.33% and 43.24% in the three groups, respectively. Significant differences among the three groups were reported (P < 0.001 and P for a trend <0.001). (b) Comparison of DCAN prevalence according to plasma blood glucose (PBG). DCAN prevalence was 18.18% and 38.27% in the two groups, respectively. A significant difference between the two groups was reported (P < 0.001). (c) Comparison of DCAN prevalence according to hemoglobin A1c (HbA1c). DCAN prevalence was 19.54%, 32.50% and 47.61% in the three groups, respectively. Significant differences among the three groups were reported (P < 0.001 and P for a trend <0.001). (d) Comparison of DCAN prevalence according to DMD. DCAN prevalence was 18.18%, 26.34%, 36.25% and 51.72% in the four groups, respectively. Significant differences between the two groups were reported (P < 0.001 and P for a trend <0.001).
Figure 2
Figure 2
Comparison of prevalence of diabetic cardiovascular autonomic neuropathy (DCAN) according to β‐cell function parameters. (a) Comparison of DCAN prevalence according to fasting insulin resistance (FINS). DCAN prevalence was 32.33%, 26.01% and 52.17% in the three groups, respectively. Significant differences among the three groups were reported (P < 0.001 and P for a trend <0.001). (b) Comparison of DCAN prevalence according to homeostasis model assessment of insulin resistance (HOMA‐IR). DCAN prevalence was 24.39% and 38.25% in the two groups, respectively. Significant differences between the two groups were reported (P < 0.001). (c) Comparison of DCAN prevalence according to homeostasis model assessment of insulin sensitivity index (HOMA‐ISI). DCAN prevalence was 34.49%, 25.92% and 20.75% in the three groups, respectively. There were significant differences among the three groups (P = 0.005 and P for a trend = 0.001). (d) Comparison of DCAN prevalence according to homeostasis model assessment of β –cell function (HOMA‐β). DCAN prevalence was 31.45% and 26.31% in the two groups, respectively. There were no significant differences between the two groups (P = 0.098).
Figure 3
Figure 3
Comparison of prevalence of diabetic cardiovascular autonomic neuropathy (DCAN) according to glucose profile risk score (GRS) and its predictive performance analysis. (a) Comparison of DCAN prevalence according to glucose profile risk score. DCAN prevalence was 14.00%, 21.43%, 22.69%, 38.67%, 45.65% and 61.54% in the six groups, respectively. There were significant differences among these groups (P < 0.001 and P for a trend <0.001). (b) Receiver operating characteristic curves showed the performance of GRS in predicting prevalence of DCAN. Area under the curve 0.671, 95% confidence interval 0.633–0.710, P < 0.001.

References

    1. Singh JP, Larson MG, O'Donnell CJ, et al Association of hyperglycemia with reduced heart rate variability (The Framingham Heart Study). Am J Cardiol 2000; 86: 309–312.
    1. Spallone V, Ziegler D, Freeman R, et al Cardiovascular autonomic neuropathy in diabetes: clinical impact, assessment, diagnosis, and management. Diabetes Metab Res Rev 2011; 27: 639–653.
    1. Ziegler D, Zentai C, Perz S, et al Selective contribution of diabetes and other cardiovascular risk factors to cardiac autonomic dysfunction in the general population. Exp Clin Endocrinol Diabetes 2006; 114: 153–159.
    1. Kamphuis MH, Geerlings MI, Dekker JM, et al Autonomic dysfunction: a link between depression and cardiovascular mortality? The FINE Study. Eur J Cardiovasc Prev Rehabil 2007; 14: 796–802.
    1. Papanas N, Ziegler D. Risk factors and comorbidities in diabetic neuropathy: an update 2015. Rev Diabet Stud 2015; 12: 48–62.
    1. Selvin E, Steffes MW, Zhu H, et al Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med 2010; 362: 800–811.
    1. Li Z, Tang ZH, Zeng F, et al Associations between the severity of metabolic syndrome and cardiovascular autonomic function in a Chinese population. J Endocrinol Invest 2013; 36: 993–999.
    1. Liu J, Tang ZH, Zeng F, et al Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population. BMC Med Inform Decis Mak 2013; 13: 80.
    1. Ge X, Chen H, Zhang K, et al The analysis of blood pressure profiles and their severity in relation to diabetic cardiovascular autonomic neuropathy in the Chinese population: preliminary analysis. J Endocrinol Invest 2016; 39: 891–898.
    1. Song L, Zhou L, Tang Z. An association analysis of lipid profile and diabetic cardiovascular autonomic neuropathy in a Chinese sample. Lipids Health Dis 2016; 15: 122.
    1. Lacigova S, Brozova J, Cechurova D, et al The influence of cardiovascular autonomic neuropathy on mortality in type 1 diabetic patients; 10‐year follow‐up. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 2016; 160: 111–117.
    1. Suarez GA, Clark VM, Norell JE, et al Sudden cardiac death in diabetes mellitus: risk factors in the Rochester diabetic neuropathy study. J Neurol Neurosurg Psychiatry 2005; 76: 240–245.
    1. Jun JE, Jin SM, Baek J, et al The association between glycemic variability and diabetic cardiovascular autonomic neuropathy in patients with type 2 diabetes. Cardiovasc Diabetol 2015; 14: 70.
    1. Grundy SM, Hansen B, Smith SC Jr, et al Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management. Circulation 2004; 109: 551–556.
    1. Zeng F, Tang ZH, Li Z, et al Normative reference of short‐term heart rate variability and estimation of cardiovascular autonomic neuropathy prevalence in Chinese people. J Endocrinol Invest 2014; 37: 385–391.
    1. Tang ZH, Zeng F, Yu X, et al Bayesian estimation of cardiovascular autonomic neuropathy diagnostic test based on baroreflex sensitivity in the absence of a gold standard. Int J Cardiol 2014; 171: e78–e80.
    1. Martin CL, Albers JW, Pop‐Busui R. Neuropathy and related findings in the diabetes control and complications trial/epidemiology of diabetes interventions and complications study. Diabetes Care 2014; 37: 31–38.
    1. Perciaccante A, Fiorentini A, Paris A, et al Circadian rhythm of the autonomic nervous system in insulin resistant subjects with normoglycemia, impaired fasting glycemia, impaired glucose tolerance, type 2 diabetes mellitus. BMC Cardiovasc Disord 2006; 6: 19.
    1. Malliani A, Pagani M, Lombardi F, et al Cardiovascular neural regulation explored in the frequency domain. Circulation 1991; 84: 482–492.
    1. Ewing DJ, Neilson JM, Shapiro CM, et al Twenty four hour heart rate variability: effects of posture, sleep, and time of day in healthy controls and comparison with bedside tests of autonomic function in diabetic patients. Br Heart J 1991; 65: 239–244.
    1. Zeng F, Tang ZH, Li Z, et al Normative reference of short‐term heart rate variability and estimation of cardiovascular autonomic neuropathy prevalence in Chinese people. J Endocrinol Invest 2014; 37: 385–391.
    1. Yun JS, Cha SA, Lim TS, et al Cardiovascular autonomic dysfunction predicts diabetic foot ulcers in patients with type 2 diabetes without diabetic polyneuropathy. Medicine 2016; 95: e3128.
    1. Axelrod S, Lishner M, Oz O, et al Spectral analysis of fluctuations in heart rate: an objective evaluation of autonomic nervous control in chronic renal failure. Nephron 1987; 45: 202–206.
    1. Pop‐Busui R, Kirkwood I, Schmid H, et al Sympathetic dysfunction in type 1 diabetes: association with impaired myocardial blood flow reserve and diastolic dysfunction. J Am Coll Cardiol 2004; 44: 2368–2374.
    1. Ward KD, Sparrow D, Landsberg L, et al Influence of insulin, sympathetic nervous system activity, and obesity on blood pressure: the Normative Aging Study. J Hypertens 1996; 14: 301–308.
    1. Ciccacci C, Morganti R, Di Fusco D, et al Common polymorphisms in MIR146a, MIR128a and MIR27a genes contribute to neuropathy susceptibility in type 2 diabetes. Acta Diabetol 2014; 51: 663–671.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe