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eISSN: 1643-3750

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A Novel Method for Estimating Low-Density Lipoprotein (LDL) Levels: Total Cholesterol and Non-High-Density Lipoprotein (HDL) Can Be Used to Predict Abnormal LDL Level in an Apparently Healthy Population

Guo-Ming Zhang, Shu-Mei Bai, Gao-Ming Zhang, Xiao-Bo Ma, Hemant Goyal

(Laboratory Medicine, Shuyang People's Hospital, Shuyang, Jiangsu, China (mainland))

Med Sci Monit 2018; 24:1688-1692

DOI: 10.12659/MSM.909226


BACKGROUND: We aimed to predict the abnormal LDL level by using TG, TC, HDL, and non-HDL in this study.
MATERIAL AND METHODS: Triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) data were obtained from the Laboratory Information System (LIS) for 4 years (Oct 1, 2013 to Sept 30, 2017) from among 34 270 healthy Chinese patients at Shuyang People’s Hospital. TG, TC, HDL, and LDL (direct clearance method) were measured using a TBA2000FR biochemical analyzer. The non-HDL was calculated as TC minus HDL. Correlations between TG, TC, non-HDL, and LDL were analyzed using Spearman’s rank correlation. Receiver operating characteristics (ROC) curve analysis was used to evaluate the predictive utility of TG, TC, and non-HDL for the abnormal LDL level (<130 mg/dL).
RESULTS: Both TC (r=0.870) and non-HDL (r=0.893) were significantly positively correlated with LDL. The area under curve of TC and non-HDL can be used to predict abnormal LDL levels. Optimal thresholds were 182.5 mg/Dl (4.72 mmol/L) for TC and 135.3 mg/Dl (3.50 mmol/L) for non-HDL. Based on these optimal thresholds, less than 0.5% and 0.4% of tests with elevated LDL were missed using TC and non-HDL, respectively, but the value of these missed LDL levels was not very high (<147.3 mg/dL).
CONCLUSIONS: If the value of non-HDL is less than 135.3 mg/Dl (3.50 mmol/L) and/or TC is less than 182.5 mg/Dl (4.72 mmol/L) for the apparently healthy populations, the LDL level will be less than 130 mg/Dl (3.36 mmol/L). TC and non-HDL can be used to predict the abnormal LDL level in apparently healthy populations.

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