NerveCheck for the Detection of Sensory Loss and Neuropathic Pain in Diabetes.

BACKGROUND: Accurate and economic detection of nerve damage in diabetes is key to more widespread diagnosis of patients with diabetic peripheral neuropathy (DPN) and painful diabetic neuropathy. This study examined the diagnostic performance of NerveCheck, an inexpensive ($500) quantitative sensory testing (QST) device. METHODS: One hundred forty-four subjects (74 with and 70 without diabetes) underwent assessment with NerveCheck, neuropathy disability score (NDS), nerve conduction studies (NCS), intraepidermal and corneal nerve fiber density (IENFD and CNFD), and McGill questionnaire for neuropathic pain. RESULTS: Of the 74 subjects with diabetes, 41 were diagnosed with DPN based on the NDS. The NerveCheck scores for vibration perception threshold (VPT), cold perception threshold (CPT), and warm perception threshold (WPT) were significantly lower (P ≤ 0.0001) in diabetic patients with DPN compared to patients without DPN. The diagnostic accuracy of VPT was high with reference to NCS (area under the curve [AUC]: 82%-84%) and moderate for IENFD, CNFD, and neuropathic pain (AUC: 60%-76%). The diagnostic accuracy of CPT and WPT was moderate with reference to NCS, IENFD, and CNFD (AUC: 69%-78%) and low for neuropathic pain (AUC: 63%-65%). CONCLUSIONS: NerveCheck is a low-cost QST device with good diagnostic utility for identifying sensory deficits, comparable to established tests of large and small fiber neuropathy and for the severity of neuropathic pain.

Automated Quantification of Neuropad Improves Its Diagnostic Ability in Patients with Diabetic Neuropathy.

Neuropad is currently a categorical visual screening test that identifies diabetic patients at risk of foot ulceration. The diagnostic performance of Neuropad was compared between the categorical and continuous (image-analysis (Sudometrics)) outputs to diagnose diabetic peripheral neuropathy (DPN). 110 subjects with type 1 and 2 diabetes underwent assessment with Neuropad, Neuropathy Disability Score (NDS), peroneal motor nerve conduction velocity (PMNCV), sural nerve action potential (SNAP), Deep Breathing-Heart Rate Variability (DB-HRV), intraepidermal nerve fibre density (IENFD), and corneal confocal microscopy (CCM). 46/110 patients had DPN according to the Toronto consensus. The continuous output displayed high sensitivity and specificity for DB-HRV (91%, 83%), CNFD (88%, 78%), and SNAP (88%, 83%), whereas the categorical output showed high sensitivity but low specificity. The optimal cut-off points were 90% for the detection of autonomic dysfunction (DB-HRV) and 80% for small fibre neuropathy (CNFD). The diagnostic efficacy of the continuous Neuropad output for abnormal DB-HRV (AUC: 91%, P = 0.0003) and CNFD (AUC: 82%, P = 0.01) was better than for PMNCV (AUC: 60%). The categorical output showed no significant difference in diagnostic efficacy for these same measures. An image analysis algorithm generating a continuous output (Sudometrics) improved the diagnostic ability of Neuropad, particularly in detecting autonomic and small fibre neuropathy.