AIMS: Most of the laboratories make use of the Friedewald formula to assess low-density lipoprotein cholesterol (LDL-C). The accuracy of this approach, however, crucially depends on triglyceride concentrations. Since hypertriglyceridaemia is a characteristic trait of the lipid profile in chronic kidney disease (CKD), the present study examines the accuracy of the Friedewald formula in this population. It aims to derive and validate a more accurate equation for CKD. METHODS: Cross-sectional study on two cohorts of subjects (overall n = 3.514) with estimated glomerular filtration rate (eGFR) <60 mL/min comparing directly measured LDL-C (LDL-Cmeas) as assessed by an enzymatic assay (Roche, Switzerland) to concentrations estimated by the Friedewald (LDL-CF) and the Martin's formula (LDL-CM). Accuracy was analysed by Bland-Altman and linear regression analyses. In the first cohort, a novel formula was derived to assess LDL-C in CKD. The formula was validated in Cohort 2. RESULTS: Cohort 1 comprised 1738 subjects, and Cohort 2 comprised 1776 subjects. The mean eGFR was 29.4 ± 14.4 mL/min. In Cohort 1, LDL-CF was highly correlated with LDL-Cmeas (R2 = 0.92) but significantly underestimated LDLmeas by 11 mg/dL. LDL-C = cholesterol - HDL - triglycerides/7.98 was derived as the optimal equation for the calculation of LDL-C in Cohort 1 and was successfully validated in Cohort 2 (bias of 1.6 mg/dL). The novel formula had a higher accuracy than both the Friedewald (bias -12.2 mg/dL) and the Martin's formula (bias -4.8 mg/dL). CONCLUSION: The Friedewald formula yields lower LDL-C concentrations in CKD than direct enzymatic measurements, which may lead to undersupply of this cardiovascular high-risk population in a treat-to-target approach.
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Bauer et al. (2020) studied this question.
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