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2型糖尿病患者视网膜微血管参数的变化糖尿病病或没有糖尿病病

Ruirui Ma^1,2, Chunwen Zheng³, Yuling Niu^1,2

¹Department of Ophthalmology, The People's Hospital of Baoan Shenzhen, Shenzhen, China.

Frontiers in endocrinology

|March 13, 2026

概括

由AI检测到的视网膜微血管变化可以帮助识别患有2型糖尿病 (T2DM) 的糖尿病病 (DKD) 风险患者. 这种非侵入性方法有助于早期发现功能障碍.

科学领域:

眼科医生眼科眼科
腎臟病學 (nephrology) 是一種醫學專業.
医疗成像医学成像

背景情况:

糖尿病病 (DKD) 是2型糖尿病 (T2DM) 的一个主要并发症.
早期发现DKD对于及时干预和管理至关重要.
视网膜微血管结构可能反映出与糖尿病和脏疾病相关的全身血管变化.

研究的目的:

在T2DM患有或没有DKD的患者中调查视网膜微血管的定量参数.
为了确定与DKD的存在和风险相关的视网膜参数.
探索视网膜成像作为DKD查的非侵入性工具的潜力.

主要方法:

对117名患有DKD的T2DM患者和179名没有DKD的T2DM患者进行了回顾性研究.
人工智能 (AI) 系统用于从 fundus 照片中提取视网膜微血管的定量参数.
分析包括视网膜损伤,血管几何 (角度,碎形尺寸,直径,扭曲度) 和血管密度.
系统性参数 (血压,葡萄糖,脂质,功能标志物) 也被收集.

主要成果:

在多个视网膜参数 (例如,硬排泄物,棉花斑点,微动脉瘤,碎形尺寸,血管直径,血管密度) 中,在各组之间观察到显著差异.
无变量分析将DKD风险与SBP,BUN,eGFR,肌素,T2DM持续时间以及各种视网膜参数联系起来.
多变量分析确定了年龄,SBP,T2DM持续时间,糖尿病视网膜病变阶段,以及视网膜血管密度在3mm的foveal无血管区内作为DKD的独立风险因素.

结论:

定量视网膜微血管参数,特别是血管密度,显示出在识别T2DM患有DKD风险的患者中的潜力.
视网膜成像分析可以作为一种非侵入性方法,用于早期检测T2DM中功能障碍.
进一步的研究可以验证这些发现在DKD查中的临床应用.

关键词:

糖尿病脏病糖尿病脏病糖尿病视网膜病变糖尿病视网膜病变微血管并发症微血管并发症视网膜血管系统的血管结构 2型糖尿病是什么?

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