Predictors of Peripheral Retinal Non-Perfusion in Clinically Significant Diabetic Macular Edema

临床显著性糖尿病性黄斑水肿中周边视网膜无灌注的预测因素

阅读:1

Abstract

Background/Objectives: Diabetic macular edema (DME) is a significant cause of vision loss. The development of peripheral non-perfusion (PNP) might be associated with the natural course, severity, and treatment of DME. The present study seeks to understand the predictive power of central macular changes and clinico-demographic features for PNP in patients with clinically significant DME. Methods: A prospective study using contemporaneous multi-modal retinal imaging was performed. In total, 48 eyes with DME from 33 patients were enrolled. Demographic, clinical history, laboratory measures, ultrawide field photography, fluorescein angiography, optical coherence tomography (OCT), and OCT angiography results were acquired. Anatomic and vascular features of the central macula and peripheral retina were quantified from retinal images. Separate (generalized) linear mixed models were used to assess differences between PNP present and absent groups. Mixed effects logistic regression was used to assess which features have predictive power for PNP. Results: Variables with significant differences between eyes with and without PNP were insulin use (p = 0.0001), PRP treatment (p = 0.0003), and diffuse fluorescein leakage (p = 0.013). Importantly, there were no significant differences for any of the macular vascular metrics including vessel density (p = 0.15) and foveal avascular zone (FAZ) area (p = 0.58 and capillary tortuosity (p = 0.55). Features with significant predictive power (all p < 0.001) were subretinal fluid, FAZ eccentricity, ellipsoid zone disruption, past anti-VEGF therapy, insulin use, and no ischemic heart disease. Conclusions: In the setting of DME, macular vascular changes did not predict the presence of PNP. Therefore, in order to detect peripheral non-perfusion in DME, our results implicate the importance of peripheral retinal vascular imaging.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。