PDF(Pubmed)
Abstract：
Low-density lipoprotein cholesterol (LDL-C) is typically estimated by the Friedewald equation to guide atherosclerotic cardiovascular disease (ASCVD) management despite its flaws. Martin-Hopkins and Sampson-NIH equations were shown to outperform Friedewald\'s in various populations. Our aim was to derive a novel equation for accurate LDL-C estimation in Saudi Arabians and to compare it to Friedewald, Martin-Hopkins and Sampson-NIH equations. This is a cross-sectional study on 2245 subjects who were allocated to 2 cohorts; a derivation (1) and a validation cohort (2). Cohort 1 was analyzed in a multiple regression model to derive an equation (equationD) for estimating LDL-C. The agreement between the measured (LDL-CDM) and calculated levels was tested by Bland-Altman analysis, and the biases by absolute error values. Validation of the derived equation was carried out across LDL-C and triglyceride (TG)-stratified groups. The mean LDL-CDM was 3.10 ± 1.07 and 3.09 ± 1.06 mmol/L in cohorts 1 and 2, respectively. The derived equation is: LDL-CD = 0.224 + (TC × 0.919) - (HDL-C × 0.904) - (TG × 0.236) - (age × 0.001) - 0.024. In cohort 2, the mean LDL-C (mmol/L) was estimated as 3.09 ± 1.06 by equationD, 2.85 ± 1.12 by Friedewald, 2.95 ± 1.09 by Martin-Hopkins, and 2.93 ± 1.11 by Sampson-NIH equations; statistically significant differences between direct and calculated LDL-C was observed with the later three equations (P < 0.001). Bland-Altman analysis showed the lowest bias (0.001 mmol/L) with equationD as compared to 0.24, 0.15, and 0.17 mmol/L with Friedewald, Martin-Hopkins, and Sampson-NIH equations, respectively. The absolute errors in all guideline-stratified LDL-C categories was the lowest with equationD, which also showed the best classifier of LDL-C according to guidelines. Moreover, equationD predicted LDL-C levels with the lowest error with TG levels up to 5.63 mmol/L. EquationD topped the other equations in estimating LDL-C in Saudi Arabians as it could permit better estimation when LDL-C is < 2.4 mmol/L, in familial hyperlipidemia, and in hypertriglyceridemia, which improves cardiovascular outcomes in high-risk patients. We recommend further research to validate equationD in a larger dataset and in other populations.
摘要：
尽管存在缺陷，但通常通过Friedewald方程估计低密度脂蛋白胆固醇（LDL-C），以指导动脉粥样硬化性心血管疾病（ASCVD）的管理。在各种人群中，Martin-Hopkins和Sampson-NIH方程的表现优于Friedewald。我们的目的是得出一个新的方程，用于沙特阿拉伯人的准确LDL-C估计，并将其与Friedewald进行比较。马丁-霍普金斯和桑普森-NIH方程。这是一项针对2245名受试者的横断面研究，这些受试者被分配到2个队列中；推导（1）和验证队列（2）。在多元回归模型中分析队列1，以得出用于估计LDL-C的方程（方程D）。通过Bland-Altman分析测试了测量水平（LDL-CDM）和计算水平之间的一致性，以及绝对误差值的偏差。在LDL-C和甘油三酸酯（TG）分层组之间进行了推导方程的验证。第1组和第2组的LDL-CDM平均值分别为3.10±1.07和3.09±1.06mmol/L。推导方程为:LDL-CD=0.224+(TC×0.919)-(HDL-C×0.904)-(TG×0.236)-(年龄×0.001)-0.024。在队列2中，通过等式D估计平均LDL-C（mmol/L）为3.09±1.06，2.85±1.12作者：Friedewald，2.95±1.09由马丁-霍普金斯，Sampson-NIH方程为2.93±1.11；后三个方程观察到直接LDL-C和计算LDL-C之间的统计学差异（P<0.001）。Bland-Altman分析显示，与Friedewald的0.24、0.15和0.17mmol/L相比，方程D的偏差最低（0.001mmol/L），马丁-霍普金斯,和Sampson-NIH方程,分别。所有指南分层LDL-C类别的绝对误差在等式D中最低，根据指南，这也显示了LDL-C的最佳分类器。此外，方程D预测LDL-C水平的误差最低，TG水平高达5.63mmol/L。EquationD在估计沙特阿拉伯的LDL-C方面超过了其他方程，因为当LDL-C<2.4mmol/L时，它可以允许更好的估计，家族性高脂血症，在高甘油三酯血症中，改善高危患者的心血管预后。我们建议进一步研究以在更大的数据集和其他人群中验证方程D。
