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J Diabetes Res. 2015;2015:847854. doi: 10.1155/2015/847854. Epub 2015 May 12.

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

Author information

1
Research Division, Weill Cornell Medical College in Qatar, Qatar Foundation, P.O. Box 24144, Education City, Doha, Qatar ; Institute of Human Development, Centre for Endocrinology & Diabetes, Faculty of Medical and Human Sciences, University of Manchester and NIHR/Wellcome Trust Clinical Research Facility, Manchester M13 9NT, UK.
2
Institute of Human Development, Centre for Endocrinology & Diabetes, Faculty of Medical and Human Sciences, University of Manchester and NIHR/Wellcome Trust Clinical Research Facility, Manchester M13 9NT, UK.
3
Institute of Human Development, Centre for Endocrinology & Diabetes, Faculty of Medical and Human Sciences, University of Manchester and NIHR/Wellcome Trust Clinical Research Facility, Manchester M13 9NT, UK ; Roke Manor Research Ltd, Old Salisbury Lane, Romsey, Hampshire SO51 0ZN, UK.

Abstract

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.

PMID:
26064991
PMCID:
PMC4443893
DOI:
10.1155/2015/847854
[Indexed for MEDLINE]
Free PMC Article

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