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从经典血脂指标估算血浆小而密 LDL 胆固醇。

Estimation of plasma small dense LDL cholesterol from classic lipid measures.

机构信息

Department of Pathology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.

出版信息

Am J Clin Pathol. 2011 Jul;136(1):20-9. doi: 10.1309/AJCPLHJBGG9L3ILS.

Abstract

Calculated low-density lipoprotein cholesterol (cLDL-C) may differ from direct measurement (dLDL-C), and this difference may depend on presence of small, dense LDL (sdLDL) particles in addition to variation in triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) concentrations. The presence of such dependence would offer a simple means to estimate sdLDL. We studied dependence of sdLDL on cLDL-C, dLDL-C, and other variables. We measured the levels of glucose, creatinine, total cholesterol, TG, HDL-C, and dLDL-C using standardized methods in 297 samples. For sdLDL cholesterol (sdLDL-C), a novel homogeneous assay was used. The cLDL-C was calculated using the Friedewald formula for 220 subjects after excluding for liver or renal disease. Using stepwise regression analysis identified non-HDL-C, cLDL-C, and dLDL-C as significant variables (P < .001; R(2) = 0.88). The regression equation was as follows: sdLDL-C (mg/dL) = 0.580 (non-HDL-C) + 0.407 (dLDL-C) - 0.719 (cLDL-C) - 12.05. The sdLDL-C concentration can be estimated from non-HDL-C, dLDL-C, and cLDL-C values. Identification of a simple, inexpensive marker for sdLDL particles provides a cost-effective method for screening cardiovascular disease risk.

摘要

计算得出的低密度脂蛋白胆固醇(cLDL-C)可能与直接测量值(dLDL-C)不同,这种差异可能取决于小而密的 LDL(sdLDL)颗粒的存在,以及甘油三酯(TG)和高密度脂蛋白胆固醇(HDL-C)浓度的变化。如果存在这种依赖性,就可以提供一种简单的方法来估计 sdLDL。我们研究了 sdLDL 与 cLDL-C、dLDL-C 和其他变量的依赖性。我们使用标准化方法测量了 297 个样本中的葡萄糖、肌酐、总胆固醇、TG、HDL-C 和 dLDL-C 的水平。对于 sdLDL 胆固醇(sdLDL-C),我们使用了一种新的均相测定法。对于 220 例排除了肝脏或肾脏疾病的患者,我们使用 Friedewald 公式计算 cLDL-C。通过逐步回归分析,确定非 HDL-C、cLDL-C 和 dLDL-C 为显著变量(P<.001;R2=0.88)。回归方程如下:sdLDL-C(mg/dL)=0.580(非 HDL-C)+0.407(dLDL-C)-0.719(cLDL-C)-12.05。sdLDL-C 浓度可以从非 HDL-C、dLDL-C 和 cLDL-C 值中估算出来。确定一种简单、廉价的 sdLDL 颗粒标志物为心血管疾病风险筛查提供了一种具有成本效益的方法。

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