摘要
目的探讨2型糖尿病患者视网膜微血管形态学特征与糖尿病肾病(DKD)的相关性。方法回顾性分析2018年1月至2020年12月于郑州大学第一附属医院就诊的2型糖尿病患者的临床资料及眼底照相图片。根据是否伴有肾功能异常分为DKD组和对照组。应用U-Net深度卷积神经网络将视网膜血管形态学及结构数字化,应用多因素logistic回归分析视网膜血管形态学特征与DKD的相关性。结果共纳入2型糖尿病患者648例,男410例,女238例,年龄(53±10)岁。2型糖尿病不伴肾功能异常的对照组398例,DKD组250例;收集双侧眼底图像1296张。DKD组患者男性占比(68.4%比60.1%,P=0.032)、年龄[(54±9)比(52±10)岁,P=0.005]、收缩压[(136.8±17.3)比(130.3±15.4)mmHg(1 mmHg=0.133 kPa),P<0.001]、总胆固醇[(4.5±1.4)比(4.2±1.0)mmol/L,P=0.009]、甘油三酯[M(Q_(1),Q_(3))][1.7(1.2,3.0)比1.4(1.0,2.3)mmol/L,P<0.001]、胱抑素C[(0.9(0.8,1.0))比0.8(0.7,0.9)mg/L,P<0.001]均高于对照组,高密度脂蛋白[(1.0±0.3)比(1.1±0.3)mmol/L,P=0.001]低于对照组。多因素logistic回归分析结果显示,调整年龄、性别后,相对于血管弯曲度最低四分位数组,第三分位数组(右眼:OR=1.825,95%CI:1.204~2.768,P=0.005)和第四分位数组(左眼:OR=1.929,95%CI:1.218~3.055,P=0.005)DKD的发生风险增加;视网膜静脉血管管径平均值增加(左眼:OR=1.044,95%CI:1.013~1.075,P=0.005)与DKD发生风险相关;血管分形维数(左眼第四分位数组:OR=0.444,95%CI:0.199~0.987,P=0.046)和视网膜血管密度(右眼第二、四分位数组:OR=0.639,95%CI:0.409~0.998,P=0.049;OR=0.534,95%CI:0.331~0.864,P=0.010)降低与DKD的发生风险相关。结论视网膜微血管形态学特征异常与DKD存在关联,视网膜静脉血管管径增加、血管密度降低与DKD的发生相关。
Objective To explore the correlation between the morphological characteristics of retinal microvessels and diabetic kidney disease(DKD)in patients with type 2 diabetes mellitus(T2DM).Methods The clinical data and fundus photography of patients with T2DM treated in the First Affiliated Hospital of Zhengzhou University from January 2018 to December 2020 were retrospectively collected and analyzed.According to the presence of abnormal renal function,the patients were divided into DKD group and control group.The morphology and structure of fundus vessels were digitized by U-Net depth convolution neural network,and the correlation between fundus vascular morphology and DKD was analyzed by multivariate logistic regression.Results A total of 648 patients with T2DM were enrolled,including 410 males and 238 females,and aged(53±10)years.There were 398 and 250 cases in control and DKD groups,respectively.Meanwhile,1296 fundus images were collected.Compared with control group,the male ratio(68.4%vs 60.1%,P=0.032),age[(54±9)vs(52±10)years,P=0.005],blood pressure[(136.8±17.3)vs(130.3±15.4)mmHg(1 mmHg=0.133 kPa),P<0.001],total cholesterol[(4.5±1.4)vs(4.2±1.0)mmol/L,P=0.009],triglyceride[M(Q_(1),Q_(3))][1.7(1.2,3.0)vs 1.4(1.0,2.3)mmol/L,P<0.001]and Cystatin C[0.9(0.8,1.0)vs 0.8(0.7,0.9)mg/L,P<0.001]were higher in the DKD group,while high-density lipoprotein[(1.0±0.3)vs(1.1±0.3)mmol/L,P=0.001]was lower in the DKD group.Multivariate logistic regression analysis showed that the risk of DKD in the third quartile(right eye:OR=1.825,95%CI:1.204-2.768,P=0.005)and fourth quartile(left eye:OR=1.929,95%CI:1.218-3.055,P=0.005)was higher than that in the lowest quartile of vascular curvature after adjusting for age and gender.The increase of average diameter of retinal vein was associated with the risk of DKD(left eye:OR=1.044,95%CI:1.013-1.075,P=0.005).The decrease of vascular fractal dimension(fourth quartile of left eye:OR=0.444,95%CI:0.199-0.987,P=0.046)and retinal vascular density(the second and fourth quartile of the right ey
作者
杨雪柯
刘章锁
李广普
段家宇
刘东伟
Yang Xueke;Liu Zhangsuo;Li Guangpu;Duan Jiayu;Liu Dongwei(Department of Integrated Traditional and Western Nephrology,the First Affiliated Hospital of Zhengzhou University,Institute of Nephrology of Zhengzhou University,Henan Province Research Center For Kidney Disease,Key Laboratory of Precision Diagnosis and Treatment for Chronic Kidney Disease in Henan Province,Zhengzhou 450052,China)
出处
《中华医学杂志》
CAS
CSCD
北大核心
2023年第18期1393-1400,共8页
National Medical Journal of China
基金
国家自然科学基金(82103916,81970633)
关键词
糖尿病
2型
糖尿病肾病
视网膜微血管参数
机器学习模型
Diabetes mellitus,type 2
Diabetic nephropathies
Retinal microvascular parameters
Machine learning model
