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基于常规临床标志物的 2 型糖尿病分层。

Stratification of type 2 diabetes based on routine clinical markers.

机构信息

Steno Diabetes Center Copenhagen, Patient Care, Niels Steensens Vej 2-4, DK-2820 Gentofte, Denmark.

Steno Diabetes Center Copenhagen, Systems Medicine, Niels Steensens Vej 2-4, DK-2820 Gentofte, Denmark.

出版信息

Diabetes Res Clin Pract. 2018 Jul;141:275-283. doi: 10.1016/j.diabres.2018.05.014. Epub 2018 May 19.

Abstract

AIMS

We hypothesized that patients with dysregulated type 2 diabetes may be stratified based on routine clinical markers.

METHODS

In this retrospective cohort study, diabetes related clinical measures including age at onset, diabetes duration, HbA, BMI, HOMA2-β, HOMA2-IR and GAD65 autoantibodies, were used for sub-grouping patients by K-means clustering and for adjusting. Probability of diabetes complications (95% confidence interval), were calculated using logistic regression.

RESULTS

Based on baseline data from patients with type 2 diabetes (n = 2290), the cluster analysis suggested up to five sub-groups. These were primarily characterized by autoimmune β-cell failure (3%), insulin resistance with short disease duration (21%), non-autoimmune β-cell failure (22%), insulin resistance with long disease duration (32%), and presence of metabolic syndrome (22%), respectively. Retinopathy was more common in the sub-group characterized by non-autoimmune β-cell failure (52% (47.7-56.8)) compared to other sub-groups (22% (20.1-24.1)), adj. p < 0.001. The prevalence of cardiovascular disease, nephropathy and neuropathy also differed between sub-groups, but significance was lost after adjustment.

CONCLUSIONS

Patients with type 2 diabetes cluster into clinically relevant sub-groups based on routine clinical markers. The prevalence of diabetes complications seems to be sub-group specific. Our data suggests the need for a tailored strategy for the treatment of type 2 diabetes.

摘要

目的

我们假设,2 型糖尿病患者可以根据常规临床标志物进行分层。

方法

在这项回顾性队列研究中,使用与糖尿病相关的临床指标,包括发病年龄、糖尿病病程、HbA、BMI、HOMA2-β、HOMA2-IR 和 GAD65 自身抗体,通过 K 均值聚类和调整进行患者分组。使用逻辑回归计算糖尿病并发症的概率(95%置信区间)。

结果

基于 2290 例 2 型糖尿病患者的基线数据,聚类分析提示可分为多达五个亚组。这些亚组主要以自身免疫性β细胞衰竭(3%)、疾病病程短伴胰岛素抵抗(21%)、非自身免疫性β细胞衰竭(22%)、疾病病程长伴胰岛素抵抗(32%)和存在代谢综合征(22%)为特征。与其他亚组(22%(20.1-24.1))相比,非自身免疫性β细胞衰竭亚组的视网膜病变更为常见(52%(47.7-56.8)),调整后 adj.p<0.001。心血管疾病、肾病和神经病变的患病率在亚组之间也存在差异,但调整后失去了意义。

结论

2 型糖尿病患者根据常规临床标志物聚类为具有临床意义的亚组。糖尿病并发症的患病率似乎与亚组特异性相关。我们的数据表明,需要针对 2 型糖尿病制定个性化的治疗策略。

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