Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA.
Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
Clin Chem. 2021 Jul 6;67(7):987-997. doi: 10.1093/clinchem/hvab048.
Increased small dense low-density lipoprotein-cholesterol (sdLDL-C) is a risk factor for atherosclerotic cardiovascular disease (ASCVD) but typically requires advanced lipid testing. We describe two new equations, first one for calculating large buoyant LDL-C (lbLDL-C), based only upon results from the standard lipid panel, and the second one for sdLDL-C.
Equations for sdLDL-C and lbLDL-C were generated with least-squares regression analysis using the direct Denka sdLDL-C assay as reference (n = 20 171). sdLDL-C was assessed as a risk-enhancer test in the National Heart and Nutrition Examination Survey (NHANES), and for its association with ASCVD in the Multi-Ethnic Study of Atherosclerosis (MESA).
The newly derived equations depend on two terms, namely LDL-C as determined by the Sampson equation, and an interaction term between LDL-C and the natural log of triglycerides (TG). The lbLDL-C equation (lbLDLC=1.43 × LDLC-0.14 ×(ln(TG)× LDLC)- 8.99) was more accurate (R2 = 0.933, slope = 0.94) than the sdLDL-C equation (sdLDLC=LDLC- lbLDLC; R2 = 0.745, slope = 0.73). Using the 80th percentile (46 mg/dL) as a cut-point, sdLDL-C identified in NHANES additional high-risk patients not identified by other risk-enhancer tests based on TG, LDL-C, apolipoprotein B, and nonHDL-C. By univariate survival-curve analysis, estimated sdLDL-C was superior to other risk-enhancer tests in predicting ASCVD events in MESA. After multivariate adjustment for other known ASCVD risk factors, estimated sdLDL-C had the strongest association with ASCVD compared to other lipid parameters, including measured sdLDL-C.
Estimated sdLDL-C could potentially be calculated on all patients tested with a standard lipid panel to improve ASCVD risk stratification.
小而密的低密度脂蛋白胆固醇（sdLDL-C）升高是动脉粥样硬化性心血管疾病（ASCVD）的一个危险因素，但通常需要进行高级血脂检测。我们描述了两种新的方程，第一个是仅基于标准血脂谱计算大浮力 LDL-C（lbLDL-C）的方程，第二个是计算 sdLDL-C 的方程。
使用直接 Denka sdLDL-C 检测作为参考（n=20171），通过最小二乘回归分析生成 sdLDL-C 和 lbLDL-C 的方程。在国家心脏和营养检查调查（NHANES）中，sdLDL-C 被评估为风险增强测试，在多民族动脉粥样硬化研究（MESA）中，sdLDL-C 与 ASCVD 的相关性进行了评估。
新推导出的方程取决于两个项，即 Sampson 方程确定的 LDL-C，以及 LDL-C 和甘油三酯（TG）的自然对数之间的交互项。lbLDL-C 方程（lbLDLC=1.43×LDLC-0.14×(ln(TG)×LDLC)-8.99）更准确（R2=0.933，斜率=0.94）比 sdLDL-C 方程（sdLDLC=LDLC-lbLDLC；R2=0.745，斜率=0.73）。使用第 80 百分位数（46mg/dL）作为切点，sdLDL-C 在 NHANES 中识别出了其他风险增强测试（基于 TG、LDL-C、载脂蛋白 B 和非 HDL-C）未识别的高危患者。通过单变量生存曲线分析，在 MESA 中，估计的 sdLDL-C 在预测 ASCVD 事件方面优于其他风险增强测试。在对其他已知 ASCVD 风险因素进行多变量调整后，与其他脂质参数（包括测量的 sdLDL-C）相比，估计的 sdLDL-C 与 ASCVD 的相关性最强。
估计的 sdLDL-C 可以潜在地计算所有用标准血脂谱检测的患者，以改善 ASCVD 风险分层。
