不同OCT分型糖尿病黄斑水肿发病的影响因素分析

目的 探讨2型糖尿病患者不同光学相干断层成像(OCT)分型糖尿病黄斑水肿(DME)发病的影响因素。方法 选取2019年1月至2021年12月天津市第三中心医院内分泌科确诊为2型糖尿病合并DME的患者117例117眼作为研究对象。由2位经验丰富的眼科医师依据患者OCT的黄斑区横断面图像对DME进行分型：弥漫性视网膜增厚(DRT)型、黄斑囊样水肿(CME)型、神经上皮脱离(NSD)型,如果患者双眼分型不一致,则取表现最为显著眼作为研究对象。收集患者年龄、病程(患者首次诊断糖尿病为起始时间)、体重指数(BMI)、入院后首次收缩压和舒张压、入院后首次空腹取外周血所得糖化血红蛋白(HbA1c)、随机尿白蛋白尿肌酐比值(UACR)、肾小球滤过率估算值(eGFR)、胱抑素C浓度(SCysC)等指标信息。分析不同DME分型与各指标的相关性并行无序多分类Logistic回归分析。结果 117例DME患者中DRT型患者53例,CME型和NSD型患者各32例。NSD并Spearman相关分析结果显示：不同DME分型与收缩压、舒张压、UACR、SCysC均呈正相关(r=0.377、0.297、0.670、0....

Influencing factors on the attack of different types of diabetic macular edema classified by optical coherence tomography

Objective　To explore the influencing factors of different types of diabetic macular edema (DME) in type 2 diabetes patients classified by optical coherence tomography (OCT).
Methods　A total of 117 patients (117 eyes) with type 2 diabetes combined with DME diagnosed by the Department of Endocrinology of Tianjin Third Central Hospital from January 2019 to December 2021 were selected as the subjects. Two experienced ophthalmologists classified the DME into the following types according to the cross-sectional images of the macular region in the OCT: diffuse retinal thickening (DRT), cystoid macular edema (CME), and neurosensory retinal detachment (NSD). If the classification of the patient’s two eyes was inconsistent, the more prominent eye was selected as the study object. Patient’s age, course of disease (the time when patients were first diagnosed with diabetes was regarded as the starting time), body mass index, the first measurement of systolic and diastolic blood pressure after admission, the first measurement of fasting glycosylated hemoglobin (HbAlc) in peripheral blood after admission, random urinary albumin-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), concentration of serum cystatin C (SCysC) and other indicators were collected. The correlation between different DME types and various indicators was analyzed, and the disordered multinomial logistic regression analysis was performed.
Results　Among the 117 DME patients, 53 had DRT, 32 had CME, and 32 had NSD. NSD and Spearman correlation analysis showed that different DME types were positively correlated with systolic and diastolic blood pressure, UACR and concentration of SCysC (r=0.377, 0.297, 0.670 and 0.460, P=0.000, 0.001, 0.000 and 0.000), negatively correlated with eGFR (r=-0.507, P=0.000), and not correlated with HbA1c level (P>0.05). With DME type as the dependent variable, and systolic and diastolic blood pressure, concentration of SCysC, eGFR and UACR as the independent variables, a disordered multinomial logistic regression analysis was conducted. Taking DRT as a reference, eGFR and UACR were independent influencing factors of different DME types. That is, the higher the UACR level and the lower the eGFR, the greater the possibility of CME and NSD.
Conclusion　The eGFR and UACR are independent influencing factors for different types of DME; the higher the UACR level and the lower the eGFR, the greater the possibility of CME and NSD.