Chumpon Wilasrusmee, Jackrit Suthakorn, Yuttana Itsarachaiyot, Napaphat Proprom, Panuwat Lertsithichai, Sopon Jirasisrithum and Dilip Kittur
Background: We have reported a novel robotic monofilament inspector (RMI) as a standard machine for screening of diabetic neuropathy. In this study, we aimed to evaluate the efficacy of RMI as compared to the manual Semmes- Weinstein monofilament test (SW), vibration perception test (VP), and Toronto Clinical Scoring (TC) in the screening of diabetic neuropathy.
Methods: 116 consecutive patients with Type II diabetes were included. The examiner conducted the RMI, VP, TC, and SW test without knowledge of patients’ lower-extremity symptoms and blinded from the patients’ perception. The performance of each test was analyzed by generating ROC curves for the detection diabetic neuropathy. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined by logistic regression analysis with adjustment for underlying disease.
Results: The prevalence of diabetic neuropathy detected (true positive) was highest in RMI, followed by SW, VP, and TC. The false positive rate for RMI, SW, VP, and TC were 26.42%, 24.53%, 33.96%, and 50.94%, respectively. The AUC of ROC curve for RMI was highest. It was slightly but not significantly higher than SW test. The AUCs of ROC curves of VP test and TC were significantly lower than RMI and SW test (Table 3, Figure 1). The sensitivity was highest in RMI, whereas the specificity was highest in SW test.
Conclusions: Difference screening tests result in different detection prevalence of diabetic neuropathy even in the same group of patients. The RMI could be used as a reliable tool in the screening of diabetic neuropathy.