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Comparison of Novel Equations for Estimating Low-Density Lipoprotein Cholesterol in Patients Undergoing Coronary Angiography. | LitMetric

Aim: The importance of precisely quantifying low-density lipoprotein cholesterol (LDL-C) has become more pronounced over the years, with the rise of metabolic syndrome in the population and the reduction in LDL-C treatment goals. This study aims to compare two novel equations indirectly estimating LDL-C and assess their compatibility with Friedewald formula, in a population with high cardiovascular risk.

Methods: This study is a retrospective analysis of the lipid profiles of 10,006 patients who underwent coronary angiography. LDL-C was calculated using Friedewald, Martin, and Sampson equations, and the compatibility between estimations was compared using methods of concordance and reclassification.

Results: Our findings show that Martin and Sampson equations displayed high rates of upward LDL-C reclassification (10.8% and 7.5%, respectively) when compared with Friedewald equation. In comparison to the Sampson method, Martin also reclassified 3.8 % of patients to a higher LDL-C category. The magnitude of discordance between LDL-C estimates was more pronounced in hypertriglyceridemic patients, and this increased progressively with the reduction in LDL-C. The proportion of patients with LDL-C <70 mg/dL reclassified to a higher LDL-C category reached 44% (Sampson vs. Friedewald), 65% (Martin vs. Friedewald), and 37% (Martin vs.Sampson) in those with triglyceride levels between 200 and 399 mg/dL.

Conclusions: Both Martin and Sampson LDL-C estimates displayed significant proportion of upward discordance with reclassification to higher LDL-C categories compared to Friedewald formula, particularly in patients with elevated triglycerides and low LDL-C, a population in whom more accurate estimation of LDL-C is required. Further studies are warranted to validate the recently developed Sampson equation with comparison to Martin method that tended to more significantly overestimate LDL-C.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840162PMC
http://dx.doi.org/10.5551/jat.57133DOI Listing

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