Department of Endocrinology, Longgang Central Hospital, Shenzhen 1228 Longgang Road, Shenzhen, 518116, Guangdong, China.
Department of Biostatistics, The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.
Sci Rep. 2021 Mar 24;11(1):6784. doi: 10.1038/s41598-021-85831-0.
To investigate the relationship between geometrical changes of retinal vessels and diabetic peripheral neuropathy (DPN), and to determine the effectiveness of retinal vascular geometry analysis and vibration perception threshold (VPT) for DPN assessment. Type 2 diabetes patients (n = 242) were categorized by stage of DPN. VPT and fundus photography was performed to obtain retinal vascular geometry parameters. The risk factors for DPN and the correlation between DPN stages were analyzed. The efficiency of the retinal vascular geometric parameters obtained with VPT as a diagnostic tool for DPN was examined. Stages of DPN showed a linear correlation with VPT (r = 0.818), central retinal vein equivalent (CRVE) (r = 0.716), and fractal dimension arterioles (DFa) (r = - 0.769). VPT, CRVE, DFa, and fractal dimension veins (DFv) showed high sensitivity (80%, 55%, 82%, and 67%, respectively) and specificity (92%, 93%, 82%, and 80%, respectively) for DPN diagnosis. Good agreement was observed between combined use of geometric parameters (CRVE, DFa and DFv) and VPT (Kappa value 0.430). The detection rate of DPN with combined use of geometric parameters of retinal vessels (64.88%) was significantly higher than that with use of VPT (47.52%). Retinal vascular geometry changes demonstrated significant correlation with DPN severity. VPT, CRVE, DFa, and DFv may provide insights for understanding DPN.
为了探讨视网膜血管几何变化与糖尿病周围神经病变(DPN)的关系,并确定视网膜血管几何分析和振动感觉阈值(VPT)在 DPN 评估中的有效性。将 242 例 2 型糖尿病患者按 DPN 分期进行分类。进行 VPT 和眼底摄影以获得视网膜血管几何参数。分析 DPN 的危险因素以及 DPN 分期之间的相关性。检查 VPT 获得的视网膜血管几何参数作为 DPN 诊断工具的效率。DPN 分期与 VPT(r=0.818)、中心视网膜静脉当量(CRVE)(r=0.716)和小动脉分形维数(DFa)(r=−0.769)呈线性相关。VPT、CRVE、DFa 和小静脉分形维数(DFv)对 DPN 诊断具有较高的敏感性(分别为 80%、55%、82%和 67%)和特异性(分别为 92%、93%、82%和 80%)。几何参数(CRVE、DFa 和 DFv)与 VPT 联合使用(Kappa 值为 0.430)观察到良好的一致性。联合使用视网膜血管几何参数(CRVE、DFa 和 DFv)检测 DPN 的检出率(64.88%)明显高于 VPT(47.52%)。视网膜血管几何变化与 DPN 严重程度有显著相关性。VPT、CRVE、DFa 和 DFv 可能为理解 DPN 提供一些思路。