Validation of a novel method for determination of low-density lipoprotein cholesterol levels in Indian patients with type 2 diabetes

LDL-cholesterol (LDL-C), being the primary predictor of cardiovascular disease in Type 2 diabetes (T2D), is associated with cardiovascular risk stratification and requires to be estimated with better accuracy with minimal bias. Different formulae have been devised to calculate the LDL-C from the measured lipid profile parameters. In this analytical cross-sectional study, a total of 150 patients with T2D were studied, and blood samples were subjected for lipid profile analysis at the Central Biochemistry laboratory. Different formulae assessed calculated LDL-C. We observed that all formulae, except Ahmadi, underestimated the LDL-C compared to direct assay. A significant difference was observed between all calculated LDL-C and directly measured LDL-C. On linear regression analysis, the newer formula Martin's has a better approximation with direct assay (slope: 0.9708) than Friedewald (slope: 0.9477). Similarly, Martin's formula exhibited lesser bias (−13.56) in calculating LDL-C in patients with T2D compared with Friedewald's formula. The study demonstrated that in patients with T2D, all formulae except Ahmadi significantly underestimated the LDL-C when compared with the direct assay. The newer Martin's formula appeared to more precisely calculate LDL-C in T2D when compared with the traditional Friedewald's formula. •All formulae except Ahmadi underestimated the LDL-C in patients with type 2 diabetes (T2D).•Martin's has a lesser bias in calculating LDL-C in patients with T2D when compared with traditional Friedewald's.•Martin's has a better approximation with direct assay for LDL-C than Friedewald and other formulae in patients with T2D.•The study needs to be validated within a larger study population.