Clinical data show that clinical manifestations of CAN appear in T2DM, and the estimated 5-year mortality is approximately 50% . Thus, evaluating the severity of CAN regression or progression is important for risk stratification and subsequent management. To our knowledge, efforts on those patients who had already suffered from CAN remain unsatisfactory.
Major findings of our study
Our study produced three major findings. First, SDNN, total power of HF and LF, and feet ESC had sufficient diagnostic accuracy in the presence of CAN in ROC analysis though only either HRV or ESC as a screening tool could be unsatisfactory. However, combined SDNN and feet ESC can increase the diagnostic accuracy of CAN (sensitivity, specificity, and AUC). Second, SDNN, total power of HF and LF, and feet ESC had been shown to bear a significant negative correlation with CAN score, indicating that they are surrogate markers of CAN severity. Finally, our study results showed that combining SDNN, total power of HF and LF, and feet ESC can improve assessment in a multiple linear regression model (R-squared value is highest in model 3).
Risk factors associated with the severity of CAN
The pathophysiological mechanism of CAN development is multifactorial, and several studies reported the important role of CV risk factors, such as diabetes duration, degree of glycemic control, SBP, triglyceride levels, and BMI, in the development of CAN [22-25]. Further, there is enough evidence that CAN may precede DM . A framework for screening and early multifactorial interventions (hyperglycemia, hypertension, dyslipidemia, and microalbuminuria) is the best prospect for preventing or halting CAN and its devastating sequelae and is the gold standard of diabetic care in T2DM  and T1DM . Diabetes duration is an important risk factor for CAN. CAN is a length-dependent pattern of disease, and parasympathetic activity can be damaged in the early phase of CAN with sympathetic predominance. As the diseases progress, sympathetic denervation occurs in the late stage of CAN . Our study also showed that all parasympathetic parameters (e.g., VR, E:I ratio, 30:15 ratio, and SDNN) were significantly lower in proportion to the severity of CAN.
Feet ESC and SDNN as electrophysiologic markers for evaluation of CAN severity
CARTs are the gold standard for the diagnosis of CAN. Nevertheless, there are some limitations to perform the whole test battery in clinical practice. It takes around 30 min to complete all the tests, and thus screening a large number of patients with diabetes may be impossible in some busy clinics. In addition, the tests sometimes may not be done due to patients’ limitation, such as patients’ underlying conditions (e.g., dementia or parkinsonism) and those who are unable to do deep breathing or Valsalva maneuver, or patients who are unable to stand. Therefore, a simplified effective method may be needed in busy outpatient clinics so that most patients can be screened or frequently followed up.
A clinical study showed that ESC reduction is proportional to the skin nerve fiber density  and can be used as a noninvasive measurement and is correlated with the gold standard measurement for the severity of small fiber neuropathy (e.g., skin biopsy with quantization of intra-epidermal nerve fiber density). Furthermore, ESC can be a clinically meaningful tool to measure severity and follow-up for progression and regression . Although several studies have demonstrated that SUDOSCAN risk score is a good screening test for CAN [12, 31], the diagnostic accuracy of CAN in our study is not established. The available information was calculated automatically from ESC values, BMI, and age using an algorithm included in the device software as we did not know the detailed algorithm of SUDOSCAN risk scores. However, several CV risk factors, such as diabetes duration, degree of glycemic control, SBP, triglyceride levels, and diseases of central or peripheral autonomic dysfunctions, could contribute to the severity of CAN, but may not be considered in the device software. Further, different ethnic groups also can affect the normal values of ESC that seemed to lower in Chinese populations . However, other studies and our study showed that feet ESC is significantly correlated with the severity of CAN , which is compatible with the length-dependent pattern of diseases.
Sympathetic and parasympathetic stimuli directly influence heart rate and are responsible for the physiologic variation in HRV. HRV can be evaluated in the time and frequency domains . Short-term HRV may be another time-saving tool that can be used in busy clinics. Only a 5-min resting recording of ECG is needed for computation and the requirement of patient’s cooperation is decreased.
There are several different approaches of HRV in the time and frequency domains. Among these methods, the time domain parameter, SDNN, is the most intuitional with the simplest computation. Furthermore, the parameter is essential for almost all portable HRV devices. Since variance is mathematically equal to the total power of spectral analysis, SDNN reflects all the cyclic components responsible for the variability at the time of recording.
Although parameters in the frequency domain may provide information about parasympathetic and sympathetic modulations or balance in addition to cardiovagal function , it bears some pitfalls in the interpretation of results. Application of the such technique is critically dependent on the understanding of the underlying physiology, the mathematical analyses used, and the many confounders and possible technical artifacts. The measurement of VLF, LF, and HF power components is usually made in absolute values of power (power density, ms2). LF and HF may also be measured in normalized units (n.u.), which represent the relative value of each power component in proportion to the total power minus the VLF component. The representation of LF (n.u.) and HF (n.u.) emphasizes the control and balance between the sympathetic and parasympathetic systems and tends to minimize the effect of the changes on the values of LF and HF total power components. Nevertheless, normalized units should always be quoted with absolute values of the LF and HF power in order to describe completely the distribution of power in spectral components. Our study showed that the values of LF and HF total power decreased in proportion to the severity to CAN, and both LF and HF total power were negatively correlated with the CAN score. It implies that both parasympathetic and sympathetic impairments were more severe as the severity of CAN progressed. In view of our current data in HRV, SDNN has the highest correlation coefficient with the CAN score among these HRV parameters. We recommend using SDNN as an indicator for the severity of CAN.
Finally, our study confirmed that this combination of electrophysiologic biomarkers (SDNN and feet ESC) as a simplified test battery is a feasible time-effective CV autonomic screening service for outpatient clinics and can be completed in less than 10 min. It also reduces clinic visits and provides objective and quantitative measures of CAN in those patients who already had CAN. Similar to the idea of a one-stop service for microvascular screening , our test battery can serve as a one-stop CAN screening service. If the test battery shows CAN progression, they will resort to the more sophisticated and specific, but ultimately more time-consuming complete autonomic function testings (e.g., CARTs).
This study is a cross-sectional prospective study. Although we observed close relationship between SDNN and feet ESC and the severity of CAN in this observational study, the role of the test battery together with the combination of the two electrophysiologic biomarkers (SDNN and feet ESC) in a longitudinal study to evaluate the regression or progression of CAN is mandatory. Second, our study only included a Chinese population with type 2 diabetes. We did not included those patients who had pre-diabetes, non-diabetes or normal control.