Derivation of a new formula for the estimation of low-density lipoprotein cholesterol

Abstract

BACKGROUND: Low-density lipoprotein cholesterol (LDLc) is a well-known surrogate marker to assess the cardiovascular health and risk of atherosclerosis. Due to the feasibility of calculating the LDLc from the estimated values of other subfractions of cholesterol, it has been commonly applied in resource-limited settings. However, calculated LDLc presents with a significant bias, probably due to the lack of relevance of equation in the local population. MATERIALS AND METHODS: A total of 200 samples were assessed for serum lipid profile by automated method. Parallelly, based on the values of subfractions of cholesterol obtained, an equation was derived using polynomial multiregression analysis. We also tested the ability other published equations to accurately predict the LDLc value. RESULTS: We found the best fit equation as LDLcal= (0.88 × total cholesterol) − (0.02 × triglycerides) − (0.03 × high-density lipoprotein) − 37.48. The equation performed better than most other published equations, including Friedewald's equation. It was also noted that Chen's equation had the best prediction and Ahmidi's equation performed the poorest. CONCLUSION: This study highlights a significant need for improved formulas to estimate serum LDLc based on other cholesterol parameters.

Keywords

• Indirect estimation
• low-density lipoprotein cholesterol
• serum cholesterol