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 (CV_R-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 CV_R-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[CV_R-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 CV_R-R could improve diagnostic efficiency and accessibility for DPN assessment in patients with diabetes.