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糖化差值与糖尿病患者的死亡率和血管并发症的关系。

Association of glycation gap with mortality and vascular complications in diabetes.

机构信息

Corresponding author: Ananth U. Nayak,

出版信息

Diabetes Care. 2013 Oct;36(10):3247-53. doi: 10.2337/dc12-1040. Epub 2013 Jul 8.

Abstract

OBJECTIVE

The "glycation gap" (G-gap), an essentially unproven concept, is an empiric measure of disagreement between HbA1c and fructosamine, the two indirect estimates of glycemic control. Its association with demographic features and key clinical outcomes in individuals with diabetes is uncertain.

RESEARCH DESIGN AND METHODS

The G-gap was calculated as the difference between measured HbA1c and a fructosamine-derived standardized predicted HbA1c in 3,182 individuals with diabetes. The G-gap's associations with demographics and clinical outcomes (retinopathy, nephropathy, macrovascular disease, and mortality) were determined.

RESULTS

Demographics varied significantly with G-gap for age, sex, ethnic status, smoking status, type and duration of diabetes, insulin use, and obesity. A positive G-gap was associated with retinopathy (odds ratio 1.24 [95% CI 1.01-1.52], P=0.039), nephropathy (1.55 [1.23-1.95], P<0.001), and, in a subset, macrovascular disease (1.91 [1.18-3.09], P=0.008). In Cox regression analysis, the G-gap had a "U"-shaped quadratic relationship with mortality, with both negative G-gap (1.96 [1.50-2.55], P<0.001) and positive G-gap (2.02 [1.57-2.60], P<0.001) being associated with a significantly higher mortality.

CONCLUSIONS

We confirm published associations of G-gap with retinopathy and nephropathy. We newly demonstrate a relationship with macrovascular and mortality outcomes and potential links to distinct subpopulations of diabetes.

摘要

目的

“糖化差值”(G-gap)是一个未经证实的概念,是衡量糖化血红蛋白(HbA1c)和果糖胺这两种间接血糖控制指标之间差异的经验性指标。其与糖尿病患者的人口统计学特征和主要临床结局的关系尚不确定。

研究设计和方法

在 3182 名糖尿病患者中,计算了 G-gap,即测量的 HbA1c 与果糖胺衍生的标准化预测 HbA1c 之间的差值。确定了 G-gap 与人口统计学特征和临床结局(视网膜病变、肾病、大血管疾病和死亡率)的关系。

结果

G-gap 与年龄、性别、种族状态、吸烟状况、糖尿病类型和持续时间、胰岛素使用和肥胖等人口统计学特征差异显著。正 G-gap 与视网膜病变(比值比 1.24 [95%可信区间 1.01-1.52],P=0.039)、肾病(1.55 [1.23-1.95],P<0.001)以及在一个亚组中与大血管疾病(1.91 [1.18-3.09],P=0.008)相关。在 Cox 回归分析中,G-gap 与死亡率呈“U”型二次关系,负 G-gap(1.96 [1.50-2.55],P<0.001)和正 G-gap(2.02 [1.57-2.60],P<0.001)均与死亡率显著升高相关。

结论

我们证实了 G-gap 与视网膜病变和肾病的关联。我们新发现了 G-gap 与大血管疾病和死亡率结局的关系,并可能与糖尿病的不同亚群有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fba3/3781552/39ea7bc8ece1/3247fig1.jpg

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