Simplified electrophysiological approach combining a point-of-care nerve conduction device and an electrocardiogram produces an accurate diagnosis of diabetic polyneuropathy.

AIMS/INTRODUCTION: This study aimed to investigate the diagnostic potential of two simplified tests, a point-of-care nerve conduction device (DPNCheck™) and a coefficient of variation of R-R intervals (CVR-R), as an alternative to traditional nerve conduction studies for the diagnosis of diabetic polyneuropathy (DPN) in patients with diabetes. MATERIALS AND METHODS: Inpatients with type 1 or type 2 diabetes (n = 167) were enrolled. The study population consisted of 101 men, with a mean age of 60.8 ± 14.8 years. DPN severity was assessed using traditional nerve conduction studies, and differentiated based on Baba's classification (BC). To examine the explanatory potential of variables in DPNCheck™ and CVR-R regarding the severity of DPN according to BC, a multiple regression analysis was carried out, followed by a receiver operating characteristic analysis. RESULTS: Based on BC, 61 participants (36.5% of the total) were categorized as having DPN severity of stage 2 or more. The multiple regression analysis yielded a predictive formula with high predictive power for DPN diagnosis (estimated severity of DPN in BC = 2.258 - 0.026 × nerve conduction velocity [m/s] - 0.594 × ln[sensory nerve action potential amplitude (µV)] + 0.528In[age(years)] - 0.178 × ln[CVR-R], r = 0.657). The area under the curve in receiver operating characteristic analysis was 0.880. Using the optimal cutoff value for DPN with severer than stage 2, the predictive formula showed good diagnostic efficacy: sensitivity of 83.6%, specificity of 79.2%, positive predictive value of 51.7% and negative predictive value of 76.1%. CONCLUSIONS: These findings suggest that DPN diagnosis using DPNCheck™ and CVR-R could improve diagnostic efficiency and accessibility for DPN assessment in patients with diabetes.

Power spectral analysis of heart rate variability is useful as a screening tool for detecting sympathetic and parasympathetic nervous dysfunctions in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder that causes motor symptoms and autonomic dysfunction. However, autonomic function tests commonly performed in PD can only evaluate either the sympathetic or parasympathetic nervous system. Therefore, the purpose of this pilot study is to investigate whether power spectral analysis of heart rate variability could detect both sympathetic and parasympathetic nervous dysfunctions in patients with PD. METHODS: Seventeen patients with PD and 11 healthy control subjects underwent electrocardiogram recording for the spectral analysis of heart rate variability to obtain values of low-frequency (LF) (0.04-0.15 Hz) and high-frequency (HF) (0.15-0.4 Hz) powers. Moreover, we examined the coefficient of variation of R-R intervals (CVRR) as a parameter of parasympathetic function in all participants and performed 123I-metaiodobenzylguanidine scintigraphy to measure the heart-to-mediastinum ratio as a parameter of cardiac sympathetic innervation in patients with PD. RESULTS: The median age of control subjects and PD patients was 63 and 66 years old, respectively. The median Hoehn and Yahr scale of PD patients was stage 2. The values of resting LF and HF powers widely varied. The median values of resting LF powers of control subjects and PD patients and those of HF powers were 169 and 70 ms2, 279 and 65 ms2, respectively, the difference was statistically insignificant. Approximately 41% of patients with PD had values below the first quartile of resting LF powers (< 58 ms2) or HF powers (< 50 ms2); however, no control subject had such low values. Positive correlations were found between resting LF powers and heart-to-mediastinum ratios of 123I-metaiodobenzylguanidine uptake (r = 0.6) and between resting HF powers and CVRRs (r = 0.7). The resting LF power was also associated with CVRRs and constipation. Furthermore, a positive correlation was observed between resting LF powers and resting HF powers in patients with PD (r = 0.8). CONCLUSIONS: The power spectral analysis of heart rate variability may be useful as a screening tool for detecting autonomic dysfunctions by detecting low resting LF and HF powers in patients with PD. Sympathetic and parasympathetic nerves may be concurrently damaged in patients with PD.

Estimation of heart rate variability using a compact radiofrequency motion sensor.

Physiological indices that reflect autonomic nervous activity are considered useful for monitoring peoples' health on a daily basis. A number of such indices are derived from heart rate variability, which is obtained by a radiofrequency (RF) motion sensor without making physical contact with the user's body. However, the bulkiness of RF motion sensors used in previous studies makes them unsuitable for home use. In this study, a new method to measure heart rate variability using a compact RF motion sensor that is sufficiently small to fit in a user's shirt pocket is proposed. To extract a heart rate related component from the sensor signal, an algorithm that optimizes a digital filter based on the power spectral density of the signal is proposed. The signals of the RF motion sensor were measured for 29 subjects during the resting state and their heart rate variability was estimated from the measured signals using the proposed method and a conventional method. A correlation coefficient between true heart rate and heart rate estimated from the proposed method was 0.69. Further, the experimental results showed the viability of the RF sensor for monitoring autonomic nervous activity. However, some improvements such as controlling the direction of sensing were necessary for stable measurement.