Neuroretinal dysfunction revealed by a flicker electroretinogram correlated with peripheral nerve dysfunction and parameters of atherosclerosis in patients with diabetes. Issue 7 (18th December 2020)

• Record Type: Journal Article
• Authors: Kawai, Miyuka; Himeno, Tatsuhito; Shibata, Yuka; Hirai, Nobuhiro; Asada‐Yamada, Yuriko; Asano‐Hayami, Emi; Ejima, Yohei; Kasagi, Rina; Nagao, Eriko; Sugiura‐Roth, Yukako; Nakai‐Shimoda, Hiromi; Nakayama, Takayuki; Yamada, Yuichiro; Ishikawa, Takahiro; Morishita, Yoshiaki; Kondo, Masaki; Tsunekawa, Shin; Kato, Yoshiro; Nakamura, Jiro; Kamiya, Hideki
• Is Part Of: Journal of diabetes investigation. Volume 12:Issue 7(2021)
• Page Start: 1236
• Page End: 1243
• Publication Date: 2020-12-18
• Subjects: Diabetic neuropathies -- Electroretinography -- Point‐of‐care testing; Diabetes -- Periodicals; Diabetes -- Research -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462005
• DOI: 10.1111/jdi.13465
• Languages: English
• ISSNs: 2040-1116

Abstract

Abstract: Aims/Introduction: Diabetic polyneuropathy (DPN) develops in the early stage of diabetes. However, no common diagnostic protocol has yet been established. Here, to verify that the flicker electroretinogram using a hand‐held device can detect the early dysfunction of the peripheral nervous system in patients with diabetes, we investigated the correlation between the progression of DPN and neuroretinal dysfunction. Materials and Methods: In total, 184 participants with type 1 or 2 diabetes underwent a flicker electroretinogram (ERG) using a hand‐held device RETeval™ and nerve conduction study. Participants were also evaluated for intima‐media thickness, ankle‐brachial index, toe brachial index and brachial‐ankle pulse wave velocity. Parameters of the nerve conduction study were used to diagnose the severity according to Baba's classification. A multiple regression analysis was used to examine the associations of ERG parameters with the severity of DPN categorized by Baba's classification. Diagnostic properties of the device in DPN were evaluated using a receiver operating characteristic curve. Results: A multiple regression model to predict the severity of DPN was generated using ERG. In the model, moderate‐to‐severe DPN was effectively diagnosed (area under the receiver operating characteristic curve 0.692, sensitivity 56.5%, specificity 78.3%, positive predictive value 70.6%, negative predictive value 66.1%, positive likelihood ratio 2.60, negative likelihood ratio 0.56). In the patients without diabetic retinopathy, the implicit time and amplitude in ERG significantly correlated with the parameters of the nerve conduction study, brachial‐ankle pulse wave velocity and intima‐media thickness. Conclusions: Electroretinogram parameters obtained by the hand‐held device successfully predict the severity of DPN. The device might be useful to evaluate DPN. Abstract : The progression of diabetic retinopathy and the dysfunction of neuroretina evaluated using the mydriasis‐free flicker electroretinogram showed a significant correlation. In patients without apparent diabetic retinopathy, the electroretinogram data correlated with parameters indicating vascular dysfunction, and with parameters indicating diabetic polyneuropathy, such as data of a nerve conduction study. Therefore, the electroretinogram data might reflect the neural and vascular impairments of the retina in patients with diabetes. The electroretinogram data were able to be used to predict the severity of diabetic polyneuropathy.