Determining a new formula for calculating low-density lipoprotein cholesterol: data mining approach.
Determining a new formula for calculating low-density lipoprotein cholesterol: data mining approach.
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DOI：
10.17179/excli2015-162
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发表时间：
2015
期刊：
影响因子：
4.6
通讯作者：
Pidetcha P
中科院分区：
文献类型：
--
作者：
Dansethakul P;Thapanathamchai L;Saichanma S;Worachartcheewan A;Pidetcha P
低密度脂蛋白胆固醇（LDL-C）是冠心病的危险因素。在甘油三酯（TG）水平小于400 mg/dL时，使用Friedewald方程估算LDL-C （LDL-Cal）水平。因此，本研究的目的是生成新的LDL-Cal公式，并验证LDL-Cal与LDL-C直接测量值（LDL-Direct）之间的相关系数。本研究使用了2008年泰国玛希隆大学医疗技术学院每年进行体检的1786人的数据集。脂质谱包括总胆固醇（TC）、TG、高密度脂蛋白胆固醇（HDL-C）和LDL-C，采用罗氏/日立模块化系统分析仪测定。用弗里德瓦尔德方程和均相酶法计算LDL-C。将TG水平分为TG<200、<300、<400、<500、<600、< 1000 mg/dL 6组，构建LDL-Cal公式。采用pace回归模型构建LDL-Cal候选公式，确定与LDL-Direct的相关系数(r)。生成了6组TG水平的候选LDL-Cal公式，LDL-Cal与LDL-Direct之间具有良好的相关性。有趣的是，当TG水平小于1000 mg/dL时，使用LDL-Direct的回归模型能够生成方程，强r为0.9769。利用外部数据集（n = 666） TG测量值（36-1480 mg/dL）验证新公式，LDL-Cal与LDL-direct之间的r值高达0.971。本研究探索了一种新的LDL-Cal计算公式，其r值为0.9769，远远超出了TG大于1000 mg/dL的限制，具有应用于临床常规实验室LDL-C估算的潜力。
Low-density lipoprotein cholesterol (LDL-C) is a risk factor of coronary heart diseases. The estimation of LDL-C (LDL-Cal) level was performed using Friedewald's equation for triglyceride (TG) level less than 400 mg/dL. Therefore, the aim of this study is to generate a new formula for LDL-Cal and validate the correlation coefficient between LDL-Cal and LDL-C directly measured (LDL-Direct). A data set of 1786 individuals receiving annual medical check-ups from the Faculty of Medical Technology, Mahidol University, Thailand in 2008 was used in this study. Lipid profiles including total cholesterol (TC), TG, high-density lipoprotein cholesterol (HDL-C) and LDL-C were determined using Roche/Hitachi modular system analyzer. The estimated LDL-C was obtained using Friedewald's equation and the homogenous enzymatic method. The level of TG was divided into 6 groups (TG<200, <300, <400, <500, <600 and < 1000 mg/dL) for constructing the LDL-Cal formula. The pace regression model was used to construct the candidate formula for the LDL-Cal and determine the correlation coefficient (r) with the LDL-Direct. The candidate LDL-Cal formula was generated for 6 groups of TG levels that displayed well correlation between LDL-Cal and LDL-Direct. Interestingly, The TG level was less than 1000 mg/dL, the regression model was able to generate the equation as shown as strong r of 0.9769 with LDL-Direct. Furthermore, external data set (n = 666) with TG measurement (36-1480 mg/dL) was used to validate new formula which displayed high r of 0.971 between LDL-Cal and LDL-direct. This study explored a new formula for LDL-Cal which exhibited higher r of 0.9769 and far beyond the limitation of TG more than 1000 mg/dL and potential used for estimating LDL-C in routine clinical laboratories.