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Assessing the Validity of Nine Different Formulae for LDL-C Estimation in a Tertiary Care Centre, Hyderabad, India
BC06-BC11
Correspondence
Manaswini Namilakonda,
Assistant Professor, Department of Biochemistry, Employees State Insurance
Corporation Medical College and Hospital, Sanathnagar, Hyderabad, Telangana, India.
E-mail: drkmanaswini@gmail.com
Introduction: Conventionally, Friedewald’s formula has been used to calculate Low Density Lipoprotein- Cholesterol (LDL-C) due to its simplicity and convenience although it has limitations. Many researchers have proposed different formulae to increase the accuracy of calculated LDL-C, but none of those have concluded about a single best formula owing to differences in selected study populations. As LDL-C measurement is of utmost importance for assessing the cardiovascular risk according to National Cholesterol Education Programme’s (NCEP) Adult Treatment Panel III (ATP III), a search for a better formula to improve accuracy of cardiovascular disease (CVD) risk prediction is essential.
Aim: To assess the validity of calculated LDL-C by nine formulae and compare them to values obtained by the direct method.
Materials and Methods: A total of 324 participants were assessed retrospectively for serum lipid profile by standard methods from December 2020 to February 2021 at Employee State Insurance Corporation Medical College and Hospital, Sanathnagar, Hyderabad, Telangana, India. LDL-C was calculated using nine different formulae (Ahmadi, Anand, Chen, de Cordova, Friedewald, Hattori, Martin-Hopkins, Puavillai and Vujovic) and correlated with direct LDL-C. For further analysis, subjects were divided into five groups based on the Triglyceride levels (TG) viz; group 1 (TG <100 mg/dL), group 2 (TG: 100-150 mg/dL), group 3 (TG: 151-200 mg/dL), group 4 (TG: 201-400 mg/dL), group 5 (TG >400 mg/dL). Statistical analysis was done using Statistical Package for Social Sciences (SPSS) version 23.0.
Results: Total of 324 lipid profile reports were analysed and calculated LDL-C by nine formulas were compared. At TG levels <100 mg/dL, Puavillai was the most accurate. Between TG levels 100-200 mg/dL, Martin-Hopkins showed better accuracy and correlation with direct LDL-C. At TG levels 201-400 and >400 mg/dL, Puavillai had better accuracy. But, none of the formulae showed strong correlation with Direct LDL-C at TG >400 mg/dL. ROC curves also showed that Puavillai performed better among all formulae, at all TG levels.
Conclusion: Among the nine equations, Puavillai and Martin-Hopkins showed highest accuracy and better performance than others in the present study population. Martin-Hopkins can be used at TG levels of 100-200 mg/dL while Puavillai can be used at lower and higher TG levels in this demographic population for estimating LDL-C.