Calculated LDL-cholesterol: comparability of the extended Martin/Hopkins, Sampson/NIH, Friedewald and four other equations in South African patients.

AIMS: The reference method for low-density lipoprotein-cholesterol (LDL-C) is ultracentrifugation. However, this is unsuitable for routine use and therefore direct LDL-C assays and predictive equations are used. In this study, we compared the Friedewald, extended Martin/Hopkins, Sampson/NIH and four other equations to a direct assay. METHODS: We analysed 44 194 lipid profiles from a mixed South African population. The LDL-C predictive equations were compared with direct LDL-C assay and analysed using non-parametric statistics and error grid analysis. RESULTS: Both the extended Martin/Hopkins and Sampson/NIH equations displayed the best correlation with direct LDL-C in terms of desirable bias and total allowable error. The direct LDL-C assay classified 13.9% of patients in the low LDL-C (1.0-1.8 mmol/L) category, in comparison to the extended Martin/Hopkins equation (13.4%), the Sampson equation (14.6%) and the Friedewald equation (16.0%). The Sampson/NIH was least biased in the low LDL-C category (<1.8 mmol/L) and produced the least overall clinically relevant errors compared with the extended Martin/Hopkins and Friedewald equations in the low-LDL-C category. CONCLUSIONS: Our findings suggest only a marginal difference between the extended Martin/Hopkins equation and the Sampson/NIH equation with the use of the Beckman Coulter DxC800 analyser in this population. The results favour the implementation of the Sampson/NIH equation when the Beckman Coulter DxC analyser is used, but the extended Martin/Hopkins may also be safely implemented. Both of these equations performed significantly better than the Friedewald equation. We recommend that patients be monitored using one of these methods and that each laboratory perform its own validation of either equation to ensure continuation and accuracy, and to prevent between-method variation.

Neonatal presentation of a patient with Liddle syndrome, South Africa.

Introduction: Liddle syndrome is an autosomal dominantly inherited disorder usually arising from single mutations of the genes that encode for the alpha, beta and gamma epithelial sodium channel (ENaC) subunits. This leads to refractory hypertension, hypokalaemia, metabolic alkalosis, hyporeninaemia and hypoaldosteronism, through over-activation of the ENaC. Case presentation: We describe a 5-day old neonate who presented with severe hypernatraemic dehydration requiring admission to Steve Biko Academic Hospital in South Africa in 2012. Further evaluation revealed features in keeping with Liddle syndrome. Two compound heterozygous mutations located at different subunits encoding the ENaC were detected following genetic sequencing done in 2020. The severe clinical phenotype observed here could be attributed to the synergistic effect of these known pathological mutations, but may also indicate that one of the other variants detected has hitherto undocumented pathological effects. Management and outcome: This child's treatment course was complicated by poor adherence to therapy, requiring numerous admissions over the years. Adequate blood pressure control was achieved only after the addition of amiloride at the end of 2018, which raised the suspicion of an ENaC abnormality. Conclusion: To our knowledge, this is the first Liddle syndrome case where a combined effect from mutations resulted in severe disease. This highlights the importance of early recognition and management of this highly treatable genetic disease to prevent the grave sequelae associated with long-standing hypertension. Whole exome sequencing may assist in the detection of known mutations, but may also unveil new potentially pathological variants. What this study adds: This study highlights the importance of developing a high index of suspicion of tubulopathy such as Liddle syndrome for any child presenting with persistent hypertension associated with hypokalaemic metabolic alkalosis.

Performance of equations for calculated LDL-C in hypertriglyceridaemia: Which one correlates best with directly measured LDL-C?

BACKGROUND: The gold standard for measuring LDL-C is impractical and direct measurements have numerous shortcomings. Older predictive equations are used only with triglycerides (TG's) below 4.52 mmol/L. We evaluated the newer equations validated for use in hypertriglyceridaemia by comparison with direct LDL-C. MATERIALS AND METHODS: Datasets from two platforms (Abbott Architect and Roche Cobas) comprised of a large cohort of 64,765 individuals were used to compare the Sampson-National Institutes of Health 2 (S-NIH2) and Extended Martin-Hopkins (E-MH) equations for LDL-C with direct LDL-C (dLDL-C) assays. RESULTS: With TG's of 4.52-9.04 mmol/L the S-NIH2 equation tended to calculate lower values than measured by dLDL-C and the E-MH equation calculated higher values. Both equations correlated better with the dLDL-C measured on Abbott than Roche with the E-MH equation having more values falling within acceptable concordance levels on both platforms. CONCLUSION: The E-MH equation correlates better with dLDL-C than the S-NIH2 on both platforms with TG levels up to 9.04 mmol/L. With hypertriglyceridaemia, the E-MH equation is less likely than the S-NIH2 equation to underestimate LDL-C when compared to the dLDL-C and will be less likely to underdiagnose patients with LDL-C levels requiring treatment according to current guidelines.

Best practice for LDL-cholesterol: when and how to calculate.

The lipid profile is important in the risk assessment for cardiovascular disease. The lipid profile includes total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglycerides (TGs) and low-density lipoprotein (LDL)-cholesterol (LDL-C). LDL-C has traditionally been calculated using the Friedewald equation (invalid with TGs greater than 4.5 mmol/L and is based on the assumption that the ratio of TG to cholesterol in very- low-density lipoprotein (VLDL) is 5 when measured in mg /dL). LDL-C can be quantified with a reference method, beta-quantification involving ultracentrifugation and this is unsuitable for routine use. Direct measurement of LDL-C was expected to provide a solution with high TGs. However, this has some challenges because of a lack of standardisation between the reagents and assays from different manufacturers as well as the additional costs. Furthermore, mild hypertriglyceridaemia also distorts direct LDL-C measurements. With the limitations of the Friedewald equation, alternatives have been derived. Newer equations include the Sampson-National Institutes of Health (NIH) equation 2 and the Martin-Hopkins equation. The Sampson-NIH2 equation was derived using beta-quantification in a population with high TG and multiple least squares regression to calculate VLDL-C, using TGs and non-HDL-C as independent variables. These data were used in a second equation to calculate LDL-C. The Sampson-NIH2 equation can be used with TGs up to 9 mmol/L. The Martin-Hopkins equation uses a 180 cell stratification of TG/non-HDL-C to determine the TG:VLDL-C ratio and can be used with TGs up to 4.5 mmol/L. Recently, an extended Martin-Hopkins equation has become available for TGs up to 9.04 mmol/L.This article discusses the best practice approach to calculating LDL-C based on the available evidence.

Comparability of calculated LDL-C with directly measured LDL-C in selected paediatric and adult cohorts.

BACKGROUND AND AIMS: The gold standard for measuring LDL-C is impractical for routine use while direct measurements have numerous shortcomings. This study investigated the correlation of predictive equations with currently used enzymatic assays in populations where these have historically proven unreliable to determine whether equations may be used interchangeably. No reference measure was available for comparison in this study. MATERIALS AND METHODS: We examined two analytical datasets from different platforms to evaluate the correlation of predictive equations for LDL-C (Friedewald, Sampson-NIH2, Martin-Hopkins, Extended Martin-Hopkins, Hattori and Anandaraja) with direct LDL-C assays in a large paediatric (n = 7598) and an adult cohort with uncontrolled diabetes (n = 57165). Non-parametric statistics were used for comparison. RESULTS: In the paediatric cohort, the Sampson-NIH2 equation correlated best with the direct LDL-C assays with the most values falling within desirable bias (35.9-44%) and TEa (68.6-72.9%) and the lowest RMSE (0.5904-0.6138) across platforms, but tended to underestimate LDL-C levels. The Martin-Hopkins equation is less likely to underestimate these values. In diabetes, the Martin-Hopkins equation correlated the best with values falling within acceptable bias (40.2-50.5%) and TEa (75-80.6%). In hypertriglyceridaemia the Extended Martin-Hopkins equation correlates best with the direct LDL-C assays. CONCLUSION: Different measurement platforms influence the results of predictive equations and directly measured LDL-C. We propose utilising the Martin-Hopkins equation as an alternative to dLDL-C assays in adults with diabetes and for screening purposes in paediatric populations to avoid underestimating cardiovascular risk.