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载脂蛋白 B 代谢障碍简化诊断算法。

A simplified diagnosis algorithm for dysbetalipoproteinemia.

机构信息

Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Québec, Canada.

Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Québec, Canada; Department of Medicine, Division of Endocrinology, Université de Montreal, Québec, Canada.

出版信息

J Clin Lipidol. 2020 Jul-Aug;14(4):431-437. doi: 10.1016/j.jacl.2020.06.004. Epub 2020 Jun 10.

Abstract

BACKGROUND

Dysbetalipoproteinemia (DBL) is a disease of remnant lipoprotein accumulation caused by a defective apolipoprotein (apo) E and is associated with a considerable atherogenic burden. However, there exists confusion concerning the diagnosis of this disorder, and as a consequence, misdiagnosis is frequent.

OBJECTIVE

The objective of the present study is to propose an algorithm for the diagnosis of DBL using simple clinical variables.

METHODS

In a large cohort of 12,434 dyslipidemic patients, 4891 patients presented with mixed dyslipidemia (total cholesterol ≥ 5.2 mmol/L [200 mg/dL] and triglycerides ≥ 2.0 mmol/L [175 mg/dL]), and 188 DBL patients were identified based on the presence of an elevated very-low-density lipoprotein cholesterol/triglyceride ratio and were carriers of apoE2/E2. The APOE genotype or phenotype as well as the lipoprotein ultracentrifugation results were available for all patients.

RESULTS

Among the laboratory variables associated with the lipid profile, the non-high-density lipoprotein cholesterol (HDL-C)/apoB ratio was the best predictor of DBL diagnosis based on the C-statistic. Previous proposed criteria had either low sensitivity or low specificity for the diagnosis of DBL. Using a non-HDL-C/apoB cut point of 3.69 mmol/g (1.43 in conventional units) followed by the presence of apoE2/E2 resulted in a good sensitivity (94.8%), negative predictive value (99.8%), specificity (99.6%), positive predictive value (88.5%), accuracy (99.4%), and area under the curve (0.97 [0.95-0.99]) for the prediction of DBL.

CONCLUSION

We therefore propose a 3-step algorithm for the diagnosis of DBL using total cholesterol and triglycerides as a first step, the non-HDL-C/apoB ratio as a second screening criterion and finally the APOE genotype, lipoprotein ultracentrifugation, or electrophoresis as a confirmatory test.

摘要

背景

载脂蛋白(apo)E 缺陷导致的残粒脂蛋白积聚引起的血脂异常(DBL)是一种疾病,与相当大的动脉粥样硬化负担有关。然而,对于这种疾病的诊断存在混淆,因此误诊很常见。

目的

本研究旨在提出一种使用简单临床变量诊断 DBL 的算法。

方法

在一个 12434 名血脂异常患者的大队列中,4891 名患者患有混合性血脂异常(总胆固醇≥5.2mmol/L[200mg/dL]和甘油三酯≥2.0mmol/L[175mg/dL]),根据升高的极低密度脂蛋白胆固醇/甘油三酯比值和载脂蛋白 E2/E2 携带者,确定了 188 例 DBL 患者。所有患者均提供 APOE 基因型或表型以及脂蛋白超速离心结果。

结果

在与血脂谱相关的实验室变量中,非高密度脂蛋白胆固醇(HDL-C)/载脂蛋白 B 比值是基于 C 统计量预测 DBL 诊断的最佳预测因子。以前提出的标准对 DBL 的诊断要么敏感性低,要么特异性低。使用非 HDL-C/载脂蛋白 B 切点 3.69mmol/g(常规单位 1.43),然后存在 apoE2/E2,对 DBL 的预测具有良好的敏感性(94.8%)、阴性预测值(99.8%)、特异性(99.6%)、阳性预测值(88.5%)、准确性(99.4%)和曲线下面积(0.97[0.95-0.99])。

结论

因此,我们提出了一种使用总胆固醇和甘油三酯作为第一步、非高密度脂蛋白胆固醇/载脂蛋白 B 比值作为第二步筛选标准、最后使用 APOE 基因型、脂蛋白超速离心或电泳作为确认试验的三步算法来诊断 DBL。

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