Assessment of autonomic dysfunction in patients with type 2 diabetes using reactive hyperemia

Highlights

• Diabetes is an important contributor to atherosclerosis and autonomic dysfunction.

• The study assessed autonomic function in healthy and diabetes subjects.

• Endothelial function is associated with autonomic function after reactive hyperemia.

Abstract

It is known that aging and type 2 diabetes mellitus contribute to atherosclerosis and autonomic dysfunction. By using the air pressure sensing system (APSS), peak–peak intervals (PPIs) of wrist arterial waveforms from baseline and reactive hyperemia (RH) were obtained. Through frequency domain analysis of heart rate variability (HRV) and nonlinear Poincaré method, the HRV of healthy young individuals (Group 1, n=25), healthy upper middle-aged individuals (Group 2, n=22), and patients with type 2 diabetes (Group 3, n=28) were assessed. By using the standard deviation (SD) of the instantaneous PPI variability (SD1)/the SD of the long PPI variability (SD2) ratio (SSR), PPIs of the same individuals before and after RH induction were compared. Reduced SSR_1–10 was noted only in patients with diabetes. Moreover, a significient correlation between SSR_1–10 and endothelial function was observed in all subjects (r=0.290, p=0.033) after RH. However, no correlation with low-frequency to high-frequency power ratio (LHR) was noted before and after RH. In conclusion, according to our results, campared to the baseline, there were more significant changes of SSR_1–10 after RH in patients with diabetes; and, a significient correlation between SSR_1–10 and endothelial function at the moment of RH was noted.

Introduction

Frequency domain analysis of heart rate variability (HRV) using electrocardiographic (ECG) is an assessment method of autonomic function and baroreflex sensitivity (Malik et al., 1996). The low-frequency to high-frequency power ratio (LFP/HFP, LHR) is the parameter for frequency domain analysis and it is considered to reflect the balance between sympathetic and parasympathetic activities (Dalla Pozza et al., 2007, Malik et al., 1996, Rosengard-Barlund et al., 2009).

Previous studies have demonstrated that low autonomic function is associated with an increased risk of cardiovascular morbidity and mortality (Gerritsen et al., 2001), and low autonomic function is a predictor of rapid progression of atherosclerosis (Huikuri et al., 1999). Patients with type 2 diabetes mellitus (DM) are at increased risk of developing atherosclerosis and autonomic nervous dysfunction (Bonetti et al., 2003, Bonetti et al., 2004, Grover-Paez and Zavalza-Gomez, 2009, Quattrini et al., 2008). In addition, according to some studies, aging is associated with a reduction of autonomic function (Eckberg and Sleight, 1992, Lenard et al., 2004), and autonomic function is associated with endothelial function in patients with type 2 DM and aging (Burnstock, 1993, Harris and Matthews, 2004, Pikkujamsa et al., 1998). The present study aims therefore at investigating the effect of aging and type 2 DM on atherosclerosis and on autonomic nervous dysfunction.

However, conventionally used frequency domain parameter is not always suitable for this purpose because of signal non-stationarity and nonlinear phenomena in physiological parameters variability (Climent et al., 2009, Kamen et al., 1996, Lerma et al., 2003, Merati et al., 2006, Spallone and Menzinger, 1997, Yuan et al., 2011). Several new parameters based on nonlinear dynamics theory were therefore recently applied to HRV studies (Climent et al., 2009, Kamen et al., 1996, Lerma et al., 2003, Spallone and Menzinger, 1997, Yuan et al., 2011). Among these parameters, the Poincaré index (SD1/SD2 ratio, SSR) has been used to refer to autonomic nervous activities and baroreflex sensitivity based on a nonlinear approach to investigating HRV (Guzik et al., 2007, Kamen et al., 1996, Karmakar et al., 2011, Lerma et al., 2003, Shi et al., 2009, Stein and Reddy, 2005). In recent years, Poincaré method has been applied to HRV analysis in patients with diabetes and chronic renal failure (CRF) and the results have been compared with those acquired using conventional time/frequency domain analyses (Javorka et al., 2005, Lerma et al., 2003). The results of one of these studies demonstrated that not only could SSR reflect the baseline autonomic nervous activities, but it could also demonstrate significant difference in autonomic function before and after hemodialysis in patients with CRF that could not be detected through the conventional HRV frequency domain approaches (Lerma et al., 2003).

Although it has been proven that the air pressure sensing system (APSS) can detect the degree of arteriosclerosis in aging and type 2 DM (Wu et al., 2012, Wu et al., 2011b), the impact of arterial post-occlusion induced changes on cardiac autonomic control is still unknown. According to a previous study (Sheila et al., 2011), a test of brachial artery occlusion in 11 healthy young female subjects was performed to observe the changes in autonomic function before and during occlusion but no changes were noted after occlusion. Thus, this study aimed at evaluating the validity of applying the APSS (Wu et al., 2011a) to the assessment of the impact of age and diabetes on autonomic function through the analysis of wrist pulse wave signals from baseline and phase of reactive hyperemia (RH) (Wu et al., 2011a, Wu et al., 2011b, Wu et al., 2012). While SSR was obtained through the analysis of peak–peak interval (PPI) series for assessing HRV, SSR data were compared with the conventional frequency domain analysis data.