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基于光学相干断层扫描的生物标志物与初治糖尿病性黄斑水肿患者的全身炎症相关。

OCT-Based Biomarkers are Associated with Systemic Inflammation in Patients with Treatment-Naïve Diabetic Macular Edema.

作者信息

Zhou Jingxin, Song Siyuan, Zhang Yi, Jin Kai, Ye Juan

机构信息

Department of Ophthalmology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, 310009, China.

Department of Ophthalmology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, 310009, China.

出版信息

Ophthalmol Ther. 2022 Dec;11(6):2153-2167. doi: 10.1007/s40123-022-00576-x. Epub 2022 Sep 27.

DOI:10.1007/s40123-022-00576-x
PMID:36166152
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9587150/
Abstract

INTRODUCTION

Diabetic macular edema (DME) is one of the major sight-threatening complications of diabetic retinopathy, which is associated with retinal inflammation. However, it is still unknown whether DME is associated with systemic inflammation. The study aimed to investigate the association between systemic inflammatory and optical coherence tomography (OCT) biomarkers in patients with treatment-naïve center-involving diabetic macular edema (DME) and to further explore the role of systemic inflammation in DME.

METHODS

Medical records including clinical characteristics and ophthalmic examinations were collected from patients with treatment-naïve center-involving DME. Systemic inflammation markers including systemic immune-inflammatory index (SII), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) were calculated. OCT biomarkers, including intraretinal cyst (IRC) size, disorganization of retinal inner layers (DRIL), external limiting membrane (ELM)/ellipsoid zone (EZ) integrity, retinal hyperreflective foci (HRF), subretinal fluid (SRF) and vitreomacular (VM) status were evaluated manually. Correlation analysis and multivariable linear regression models were used to investigate the relationship between systemic inflammatory markers and OCT biomarkers.

RESULTS

A total of 82 patients with treatment-naïve center-involving DME were included. The number of HRF on OCT was correlated with SII, NLR, and PLR and positively associated with SII (p < 0.001) in both univariate and multivariate linear regression analyses. The differences remained largely the same during subgroup analysis controlling DM duration, SRF, and ELM/EZ integrity. No significant association was observed between other OCT biomarkers and blood inflammatory markers.

CONCLUSION

Retinal HRF in diabetic macular edema is associated with blood inflammatory markers, which supports the theory of HRF's inflammatory nature and emphasizes the important role of inflammation in DME. SII may be a potential marker for DME treatment decisions.

摘要

引言

糖尿病性黄斑水肿(DME)是糖尿病视网膜病变主要的视力威胁性并发症之一,与视网膜炎症相关。然而,DME是否与全身炎症相关仍不清楚。本研究旨在调查初治的累及黄斑中心凹的糖尿病性黄斑水肿(DME)患者全身炎症与光学相干断层扫描(OCT)生物标志物之间的关联,并进一步探讨全身炎症在DME中的作用。

方法

收集初治的累及黄斑中心凹的DME患者的病历,包括临床特征和眼科检查结果。计算全身炎症标志物,包括全身免疫炎症指数(SII)、中性粒细胞与淋巴细胞比值(NLR)和血小板与淋巴细胞比值(PLR)。手动评估OCT生物标志物,包括视网膜内囊肿(IRC)大小、视网膜内层紊乱(DRIL)、外界膜(ELM)/椭圆体带(EZ)完整性、视网膜高反射灶(HRF)、视网膜下液(SRF)和玻璃体黄斑(VM)状态。采用相关性分析和多变量线性回归模型研究全身炎症标志物与OCT生物标志物之间的关系。

结果

共纳入82例初治的累及黄斑中心凹的DME患者。在单变量和多变量线性回归分析中,OCT上HRF的数量与SII、NLR和PLR相关,且与SII呈正相关(p<0.001)。在控制糖尿病病程、SRF和ELM/EZ完整性的亚组分析中,差异基本保持不变。未观察到其他OCT生物标志物与血液炎症标志物之间存在显著关联。

结论

糖尿病性黄斑水肿中的视网膜HRF与血液炎症标志物相关,这支持了HRF具有炎症性质的理论,并强调了炎症在DME中的重要作用。SII可能是DME治疗决策的潜在标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0159/9587150/1045099bf342/40123_2022_576_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0159/9587150/47055ff71507/40123_2022_576_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0159/9587150/0a9e47ee7b76/40123_2022_576_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0159/9587150/1045099bf342/40123_2022_576_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0159/9587150/47055ff71507/40123_2022_576_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0159/9587150/0a9e47ee7b76/40123_2022_576_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0159/9587150/1045099bf342/40123_2022_576_Fig3_HTML.jpg

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