Comparison of Formulas for Calculating Low-density Lipoprotein Cholesterol in General Population and High-risk Patients with Cardiovascular Disease.
Аннотация
BACKGROUND AND
OBJECTIVES
Low-density lipoprotein cholesterol (LDL-C), an established cardiovascular risk factor, can be generally determined by calculation from total cholesterol, high-density lipoprotein cholesterol, and triglyceride concentrations. The aim of this study was to compare LDL-C estimations using various formulas with directly measured LDL-C in a community-based group and hospital-based group among the Korean population.
SUBJECTS AND
METHODS
A total of 1498 participants were classified into four groups according to triglyceride concentrations as follows: <100, 100-199, 200-299, and ≥300 mg/dL. LDL-C was calculated using the Friedewald, Chen, Vujovic, Hattori, de Cordova, and Anandaraja formulas and directly measured using a homogenous enzymatic method. Pearson's correlation coefficients, intraclass correlation coefficients (ICC), Passing & Bablok regression, and Bland-Altman plots were used to evaluate the performance of six formulas.
RESULTS
The Friedewald formula had the highest accuracy (ICC=0.977; 95% confidence interval 0.974-0.979) of all the triglyceride ranges, while the Vujovic formula had the highest accuracy (ICC=0.876; 98.75% confidence interval 0.668-0.951) in people with triglycerides ≥300 mg/dL. The mean difference was the lowest for the Friedewald formula (0.5 mg/dL) and the percentage error was the lowest for the Vujovic formula (30.2%). However, underestimation of the LDL-C formulas increased with triglyceride concentrations.
CONCLUSION
The accuracy of the LDL-C formulas varied considerably with differences in triglyceride concentrations. The Friedewald formula outperformed other formulas for estimating LDL-C against a direct measurement and the Vujovic formula was suitable for hypertriglyceridemic samples; it could be used as an alternative cost-effective tool to measure LDL-C when the direct measurement cannot be afforded.
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