摘要
目的从影像学和临床检验数据综合评估2型糖尿病患者(T2DM)中糖尿病肾病(DN)和糖尿病视网膜病变(DR)的相关性。方法选取2021年3月至2022年12月就诊于资阳市第一人民医院的T2DM患者600例,所有患者均行眼底照相和荧光素眼底血管造影检查,收集患者年龄、性别、T2DM持续时间、心血管疾病、脑血管疾病、高血压、吸烟史、饮酒史、体重指数、收缩压和舒张压等临床数据。测量空腹血糖、甘油三酯、总胆固醇、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、糖化血红蛋白、24 h尿白蛋白、尿白蛋白/肌酐、血肌酐和血尿素氮水平。采用Logistic回归分析与DR相关的危险因素。根据眼底图片进行DR分期,采用卷积神经网络(CNN)算法作为图像分析方法,通过ECT成像技术和临床检验数据评估DR和DN之间的相关性。结果采用CNN算法进行分析,无明显DR、轻度非增生型DR(NPDR)、中度NPDR、重度NPDR和增生型DR(PDR)组患者的DR和DN病变面积率均高于采用传统算法(TCM)的结果。随着DR的加重,患者血肌酐、血尿素氮、24 h尿白蛋白和尿白蛋白/肌酐均逐渐升高,无明显DR、轻度NPDR、中度NPDR、重度NPDR和PDR组患者的DN发生率分别为1.67%、8.83%、16.16%、22.16%和30.83%。Logistic回归分析结果显示,T2DM持续时间、吸烟史、糖化血红蛋白、总胆固醇、甘油三酯、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、24 h尿白蛋白、血肌酐、血尿素氮、尿白蛋白/肌酐、肾小球滤过率是DR的独立危险因素。肾动态ECT成像分析结果表明,随着DR的加重,肾血流灌注逐渐减少,从而导致肾过滤功能下降。结论在T2DM患者中,CNN算法早期应用于DR和DN图像的分析,将有助于提高DR和DN病变面积诊断准确性,随着DR病变的加重,DN的严重程度逐渐增加。
Objective To evaluate the relationship between diabetic nephropathy(DN)and diabetic retinopathy(DR)in patients with type 2 diabetes mellitus(T2DM)based on imaging and clinical testing data.Methods Totally 600 T2DM patients who visited the First People’s Hospital of Ziyang from March 2021 to December 2022 were included.The fundus photography and fundus fluorescein angiography were performed on all these patients and their age,gender,T2DM duration,cardiovascular diseases,cerebrovascular disease,hypertension,smoking history,drinking history,body mass index,systolic blood pressure,diastolic blood pressure and other clinical data were collected.The levels of fasting blood glucose(FPG),triglyceride(TG),total cholesterol(TC),high-density lipoprotein cholesterol(HDL-C),low-density lipoprotein cholesterol(LDL-C),glycosylated hemoglobin(HbA1c),24 h urinary albumin(UAlb),urinary albumin to creatinine ratio(ACR),serum creatinine(Scr)and blood urea nitrogen(BUN)were measured.Logistic regression was used to analyze the risk factors associated with DR.DR staging was performed according to fundus images,and the convolutional neural network(CNN)algorithm was used as an image analysis method to explore the correlation between DR and DN based on emission computed tomography(ECT)and clinical testing data.Results The average lesion area rates of DR and DN detected by the CNN in the non-DR,mild-non-proliferative DR(NPDR),moderate-NPDR,severe-NPDR and proliferative DR(PDR)groups were higher than those obtained by the traditional algorithm(TCM).As DR worsened,the Scr,BUN,24 h UAlb and ACR gradually increased.Besides,the incidence of DN in the non-DR,mild-NPDR,moderate-NPDR,severe-NPDR and PDR groups was 1.67%,8.83%,16.16%,22.16%and 30.83%,respectively.Logistic regression analysis showed that the duration of T2DM,smoking history,HbA1c,TC,TG,HDL-C,LDL-C,24 h UAlb,Scr,BUN,ACR and glomerular filtration rate(GFR)were independent risk factors for DR.Renal dynamic ECT analysis demonstrated that with the aggravation of DR,renal blood flow perfusion gradually decreased,resulting in diminished renal filtration.Conclusion The application of CCN in the early stage DR and DN image analysis of T2DM patients will improve the diagnosis accuracy of DR and DN lesion area.The DN is worsening as the aggravation of DR.
作者
唐娟
李庆华
邓秀英
鲁婷
唐国强
林志武
刘兴德
吴小利
方其林
李盈
王潇
周燕
李彪
戴传强
李涛
TANG Juan;LI Qinghua;DENG Xiuying;LU Ting;TANG Guoqiang;LIN Zhiwu;LIU Xingde;WU Xiaoli;FANG Qilin;LI Ying;WANG Xiao;ZHOU Yan;LI Biao;DAI Chuanqiang;LI Tao(Department of Endocrinology,the First People’s Hospital of Ziyang,Ziyang 641300,Sichuan Province,China;Ziyang Psychiatric Hospital,Ziyang 641300,Sichuan Province,China;Pengshan District People’s Hospital of Meishan,Meishan 620800,Sichuan Province,China;Department of Cardiothoracic Surgery,the First People’s Hospital of Ziyang,Ziyang 641300,Sichuan Province,China;Department of Ophthalmology,Key Laboratory of Ophthalmology,the First People’s Hospital of Ziyang,Ziyang 641300,Sichuan Province,China;Department of Otorhlnolaryngologleal,the First People’s Hospital of Ziyang,Ziyang 641300,Sichuan Province,China;Department of Orthopedics,the First People’s Hospital of Ziyang,Ziyang 641300,Sichuan Province,China)
出处
《眼科新进展》
CAS
北大核心
2024年第2期127-132,共6页
Recent Advances in Ophthalmology
基金
四川省资阳市科技计划项目(编号:zykjjsc20-cxpt-2020-02,zykjjsc20-yyjc-2023-04)
成都医学院-附属(教学)医院联合科研基金(编号:2022LHZY05)。
关键词
卷积神经网络
2型糖尿病
糖尿病视网膜病变
糖尿病肾病
ECT成像技术
convolutional neural network
type 2 diabetes mellitus
diabetic retinopathy
diabetic nephropathy
emission computed tomography
