Nicola Pritchard1, Katie Edwards1, Anthony W Russell2, Bruce A Perkins3, Rayaz A Malik4, Nathan Efron5. 1. Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Queensland, Australia. 2. Princess Alexandra Hospital, Woolloongabba, Queensland, Australia School of Medicine, University of Queensland, Woolloongabba, Queensland, Australia. 3. Division of Endocrinology and Metabolism, Department of Medicine, University of Toronto, Toronto, Ontario, Canada. 4. Center for Endocrinology and Diabetes, Institute of Human Development, University of Manchester, Manchester, U.K. Central Manchester Foundation Trust, Manchester, U.K. 5. Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Queensland, Australia n.efron@qut.edu.au.
Abstract
OBJECTIVE: This study determined if deficits in corneal nerve fiber length (CNFL) assessed using corneal confocal microscopy (CCM) can predict future onset of diabetic peripheral neuropathy (DPN). RESEARCH DESIGN AND METHODS: CNFL and a range of other baseline measures were compared between 90 nonneuropathic patients with type 1 diabetes who did or did not develop DPN after 4 years. The receiver operator characteristic (ROC) curve was used to determine the capability of single and combined measures of neuropathy to predict DPN. RESULTS: DPN developed in 16 participants (18%) after 4 years. Factors predictive of 4-year incident DPN were lower CNFL (P = 0.041); longer duration of diabetes (P = 0.002); higher triglycerides (P = 0.023); retinopathy (higher on the Early Treatment of Diabetic Retinopathy Study scale) (P = 0.008); nephropathy (higher albumin-to-creatinine ratio) (P = 0.001); higher neuropathy disability score (P = 0.037); lower cold sensation (P = 0.001) and cold pain (P = 0.027) thresholds; higher warm sensation (P = 0.008), warm pain (P = 0.024), and vibration (P = 0.003) thresholds; impaired monofilament response (P = 0.003); and slower peroneal (P = 0.013) and sural (P = 0.002) nerve conduction velocity. CCM could predict the 4-year incident DPN with 63% sensitivity and 74% specificity for a CNFL threshold cutoff of 14.1 mm/mm(2) (area under ROC curve = 0.66, P = 0.041). Combining neuropathy measures did not improve predictive capability. CONCLUSIONS: DPN can be predicted by various demographic, metabolic, and conventional neuropathy measures. The ability of CCM to predict DPN broadens the already impressive diagnostic capabilities of this novel ophthalmic marker.
OBJECTIVE: This study determined if deficits in corneal nerve fiber length (CNFL) assessed using corneal confocal microscopy (CCM) can predict future onset of diabetic peripheral neuropathy (DPN). RESEARCH DESIGN AND METHODS: CNFL and a range of other baseline measures were compared between 90 nonneuropathicpatients with type 1 diabetes who did or did not develop DPN after 4 years. The receiver operator characteristic (ROC) curve was used to determine the capability of single and combined measures of neuropathy to predict DPN. RESULTS:DPN developed in 16 participants (18%) after 4 years. Factors predictive of 4-year incident DPN were lower CNFL (P = 0.041); longer duration of diabetes (P = 0.002); higher triglycerides (P = 0.023); retinopathy (higher on the Early Treatment of Diabetic Retinopathy Study scale) (P = 0.008); nephropathy (higher albumin-to-creatinine ratio) (P = 0.001); higher neuropathy disability score (P = 0.037); lower cold sensation (P = 0.001) and cold pain (P = 0.027) thresholds; higher warm sensation (P = 0.008), warm pain (P = 0.024), and vibration (P = 0.003) thresholds; impaired monofilament response (P = 0.003); and slower peroneal (P = 0.013) and sural (P = 0.002) nerve conduction velocity. CCM could predict the 4-year incident DPN with 63% sensitivity and 74% specificity for a CNFL threshold cutoff of 14.1 mm/mm(2) (area under ROC curve = 0.66, P = 0.041). Combining neuropathy measures did not improve predictive capability. CONCLUSIONS:DPN can be predicted by various demographic, metabolic, and conventional neuropathy measures. The ability of CCM to predict DPN broadens the already impressive diagnostic capabilities of this novel ophthalmic marker.
Authors: Xin Chen; Jim Graham; Mohammad A Dabbah; Ioannis N Petropoulos; Mitra Tavakoli; Rayaz A Malik Journal: IEEE Trans Biomed Eng Date: 2016-06-07 Impact factor: 4.538
Authors: Bruce A Perkins; Leif Erik Lovblom; Evan J H Lewis; Vera Bril; Maryam Ferdousi; Andrej Orszag; Katie Edwards; Nicola Pritchard; Anthony Russell; Cirous Dehghani; Danièle Pacaud; Kenneth Romanchuk; Jean K Mah; Maria Jeziorska; Andrew Marshall; Roni M Shtein; Rodica Pop-Busui; Stephen I Lentz; Mitra Tavakoli; Andrew J M Boulton; Nathan Efron; Rayaz A Malik Journal: Diabetes Care Date: 2021-07-01 Impact factor: 17.152
Authors: Evan J H Lewis; Bruce A Perkins; Leif E Lovblom; Richard P Bazinet; Thomas M S Wolever; Vera Bril Journal: Neurology Date: 2017-05-17 Impact factor: 9.910