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

Autor: Georgios Ponirakis; Hassan Fadavi; Ioannis N. Petropoulos; Shazli Azmi; Maryam Ferdousi; Mohammad A. Dabbah; Ahmad Kheyami; Uazman Alam; Omar Asghar; Andrew Marshall; Mitra Tavakoli; Ahmed Al-Ahmar; Saad Javed; Maria Jeziorska; Rayaz A. Malik
Sprache: Englisch
Veröffentlicht: 2015
Quelle: Directory of Open Access Journals: DOAJ Articles
Online Zugang: http://dx.doi.org/10.1155/2015/847854
https://doaj.org/toc/2314-6745
https://doaj.org/toc/2314-6753
2314-6745
2314-6753
doi:10.1155/2015/847854
https://doaj.org/article/b6a01776d40b46a99b5b0ed96ce663f3
https://doi.org/10.1155/2015/847854
https://doaj.org/article/b6a01776d40b46a99b5b0ed96ce663f3
Erfassungsnummer: ftdoajarticles:oai:doaj.org/article:b6a01776d40b46a99b5b0ed96ce663f3

Zusammenfassung

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.