河北医科大学学报 ›› 2023, Vol. 44 ›› Issue (11): 1274-1278.doi: 10.3969/j.issn.1007-3205.2023.11.006

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2型糖尿病合并大血管病变与血浆NGAL表达、胫前色素沉着斑的相关性

  

  1. 河北省沧州市人民医院内分泌代谢科,河北 沧州 061000

  • 出版日期:2023-11-25 发布日期:2023-12-05
  • 作者简介:王臣廷(1986-),女,河北献县人,河北省沧州市人民医院主治医师,医学硕士,从事内分泌代谢研究。
  • 基金资助:
    河北省医学科学研究课题计划(20211479)

Correlation of type 2 diabetes mellitus with macroangiopathy with plasma NGAL expression and pretibial pigmentation spot

  1. Department of Endocrinology and Metabolism, Cangzhou People′s Hospital, Hebei Province, Cangzhou 061000, China

  • Online:2023-11-25 Published:2023-12-05

摘要: 目的 分析2型糖尿病(diabetes mellitus type 2,T2DM)合并大血管病变与血浆中性粒细胞明胶酶相关脂质运载蛋白(neutrophil gelatinase-associated lipocalin,NGAL)表达、胫前色素沉着斑的相关性。
方法 选我院收入的T2DM患者400例,根据其是否合并大血管病变分为观察组(103例)、对照组(297例)。比较2组血浆NGAL表达、胫前色素沉着斑情况,采用Spearman相关性分析T2DM合并大血管病变与NGAL、胫前色素沉着斑的相关性。收集所有患者临床资料,采用二元Logistic回归分析影响T2DM出现大血管病变的因素。建立受试者工作曲线(receiver operating curve,ROC)评估血浆NGAL水平与胫前色素沉着斑联合诊断T2DM合并大血管病变的价值。
结果 与对照组相比,观察组NGAL水平更高,胫前色素沉着斑发生率(64.08%)更高,差异有统计学意义(P<0.05)。T2DM合并大血管病变与胫前色素沉着斑呈正相关性(P<0.05)。与对照组相比,观察组抽烟、饮酒占比更高,糖化血红蛋白(hemoglobin A1c,HbA1c)、空腹血糖(fasting plasma glucose,FPG)、餐后2 h血糖(2 hour postprandial blood glucose,2 hPG)、三酰甘油(triglyceride,TG)、总胆固醇(total cholestero,TC)、低密度脂蛋白胆固醇(low-density lipoprotein cholesterol, LDL-C)、水平更高,差异有统计学意义(P<0.05)。Logistic回归分析显示胫前色素沉着斑发生率、NGAL水平、饮酒、TG、TC、LDL-C是影响T2DM合并大血管病变的因素(P<0.05)。ROC结果显示胫前色素沉着斑发生率、NGAL水平单独、联合诊断T2DM合并大血管病变曲线下面积为0.719、0.896、0.911,敏感度为0.641、0.757、0.777,特异度为0.798、0.902、0.936。
结论 T2DM患者出现大血管病变与NGAL、胫前色素沉着斑有一定联系,两项指标联合可为临床诊断、预防T2DM合并大血管病变提供一定参考。


关键词: 糖尿病, 2型, 糖尿病血管病变, 影响因素分析

Abstract: Objective To analyze the correlation of type 2 diabetes mellitus (T2DM) with macroangiopathy with the expression of neutrophil gelatinase related lipid transporter (NGAL) and pretibial pigmentation spot. 
Methods A total of 400 T2DM patients in our hospital were selected and divided into the observation group (n=103) and the control group (n=297) according to presence of combined macroangiopathy. The plasma NGAL expression and pretibial pigmentation spots were compared between two groups. The Spearman correlation analysis was used to analyze the correlation of T2DM with macroangiopathy with NGAL and pretibial pigmentation spots. The clinical data of all patients were collected, and binary logistic regression analysis was used to analyze the factors influencing macroangiopathy in T2DM patients. The receiver operating curve (ROC) was established to evaluate the combined diagnostic value of plasma NGAL level and pretibial pigmentation spot in T2DM patients with macroangiopathy. 
Results Compared with the control group, the level of NGAL in the observation group was higher, and the incidence of pretibial pigmentation spot (64.08%) was higher, with a statistically significant difference (P<0.05). T2DM with macroangiopathy was positively correlated with pretibial pigmentation spot (P<0.05). Compared with the control group, the observation group had a higher proportion of smoking and drinking, and higher levels of hemoglobin A1c (HbA1C), fasting plasma glucose (FPG), 2 hour postprandial blood glucose (2 hPG),  triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C), with a significant difference (P<0.05). Logistic regression analysis showed that the incidence of pretibial pigmentation spot, NGAL level, alcohol consumption, TG, TC, and LDL-C were the factors influencing T2DM with macroangiopathy (P<0.05). ROC results showed that the incidence rate of pretibial pigmentation spot and NGAL level alone and in combination in diagnosing T2DM with macroangiopathy were 0.719, 0.896, and 0.911, respectively, the sensitivity was 0.641, 0.757, and 0.777, respectively, and the specificity was 0.798, 0.902, and 0.936, respectively. 
Conclusion The occurrence of macroangiopathy in T2DM patients is related to NGAL and pretibial pigmentation spot. The combination of the two indicators can provide certain reference for clinical diagnosis and prevention of T2DM with macroangiopathy.


Key words: diabetes mellitus, type 2,  , diabetic angiopathies, influencing factor analysis