Small nerve fibre quantification in the diagnosis of diabetic sensorimotor polyneuropathy: comparing corneal confocal microscopy with intraepidermal nerve fibre density

Chen, Xin and Graham, Jim and Dabbah, Mohammad and Petropoulos, Ioannis N. and Ponirakis, Georgis and Asghar, Omar and Alam, Uazman and Marshall, Andrew and Fadavi, Hassan and Ferdousi, Maryam and Azmir, Shazli and Tavakoli, Mitra and Efron, Nathan and Jeziorska, Maria and Malik, Rayaz (2015) Small nerve fibre quantification in the diagnosis of diabetic sensorimotor polyneuropathy: comparing corneal confocal microscopy with intraepidermal nerve fibre density. Diabetes Care, 38 (6). pp. 1138-1144. ISSN 1935-5548

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Abstract

OBJECTIVE: Quantitative assessment of small fiber damage is key to the early diagnosis and assessment of progression or regression of diabetic sensorimotor polyneuropathy (DSPN). Intraepidermal nerve fiber density (IENFD) is the current gold standard, but corneal confocal microscopy (CCM), an in vivo ophthalmic imaging modality, has the potential to be a noninvasive and objective image biomarker for identifying small fiber damage. The purpose of this study was to determine the diagnostic performance of CCM and IENFD by using the current guidelines as the reference standard.

RESEARCH DESIGN AND METHODS: Eighty-nine subjects (26 control subjects and 63 patients with type 1 diabetes), with and without DSPN, underwent a detailed assessment of neuropathy, including CCM and skin biopsy.

RESULTS: Manual and automated corneal nerve fiber density (CNFD) (P < 0.0001), branch density (CNBD) (P < 0.0001) and length (CNFL) (P < 0.0001), and IENFD (P < 0.001) were significantly reduced in patients with diabetes with DSPN compared with control subjects. The area under the receiver operating characteristic curve for identifying DSPN was 0.82 for manual CNFD, 0.80 for automated CNFD, and 0.66 for IENFD, which did not differ significantly (P = 0.14).

CONCLUSIONS: This study shows comparable diagnostic efficiency between CCM and IENFD, providing further support for the clinical utility of CCM as a surrogate end point for DSPN.

Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: doi:10.2337%2Fdc14-2422
Depositing User: Chen, Xin
Date Deposited: 31 Aug 2017 09:22
Last Modified: 01 Sep 2017 15:15
URI: http://eprints.nottingham.ac.uk/id/eprint/45033

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