Retiring Friedewald, Rethinking Direct LDL-C: Modern LDL-C Equations Outperform Both the Friedewald Equation and Direct Assays.

Background: Hypertriglyceridemia is common in HIV-infected individuals on antiretroviral therapy. Triglyceride (TG) levels >400 mg/dL interfere with the accurate determination of low-density lipoproteins (LDL-C) by the Friedewald equation, making it difficult to assess coronary heart disease risk. Objective: The objective of this study is to compare the agreement of the direct LDL-C assay and the Friedewald equation with a reference ultracentrifugation method in the estimation of LDL-C concentrations. Method: Samples from ACTG 5087 were assayed by ultracentrifugation and a direct enzymatic assay and calculated using the Friedewald equation. Results: In subjects with TG <400 mg/dL (n = 271), 90% of the direct LDL-C values and Friedewald calculations were within 30 mg/dL and 32 mg/dL of the ultracentrifugation values, respectively. With TG ⩾400 mg/dL (n = 186), 90% of the direct assay and Friedewald observations were within 68 mg/dL and 120 mg/dL of the ultracentrifugation results, respectively. Only 27% of the LDL-C values were within 15 mg/dL of the ultracentrifugation LDL-C results for direct assay and 16.3% for the Friedewald equation. Conclusion: The direct LDL-C assay and the calculated LDL-C values did not display adequate agreement with the reference ultracentrifugation method. In subjects with TG >400 mg/dL, the direct assay overestimates the actual LDL-C whereas the Friedewald calculation underestimates the actual LDL. Clinical usage of these methods may lead to misclassification of the severity of dyslipidemia, resulting in improper management.

Evaluation of five methods for determining low-density lipoprotein cholesterol (LDL-C) in hemodialysis patients

A More Valid Measurement of Low-Density Lipoprotein Cholesterol in Diabetic Patients

Background/Aim: This study was performed to comparatively evaluate the results obtained for low-density lipoprotein (LDL) cholesterol concentrations by either a newly described direct method or the Friedewald equation in subjects with and without chronic renal disease. Methods: Fasting plasma was obtained from a total of 169 subjects, 105 with normal renal function (including 53 hyperlipidaemic) and 64 with chronic renal disease (nephrotic syndrome and/or chronic renal failure; including 40 hyperlipidaemic patients), and analyzed for LDL cholesterol using the Friedewald equation and a direct LDL assay method. Results: The Friedewald equation and the direct LDL cholesterol assay correlated well with each other (r = 0.79–0.90 in all subjects with plasma triglyceride, TG, levels greater than or less than 4.0 mmol/l and with and without chronic renal disease and/or hyperlipidaemia, all p < 0.0001). The values for LDL cholesterol, however, tended to be higher with the direct measurement. This mean difference was trivial in hyperlipidaemic subjects with (8.5%) and without (7.1%) normal renal function (both p < 0.05), but could be clinically significant in those with TG >4.0 mmol/l (mean difference 18%, p < 0.001). Indeed, bias plots confirmed this observation of wider negative bias for Friedewald estimation in these moderately hypertriglyceridaemic subjects. Conclusion: For most routine laboratories the options immediately available for assessment of lipid levels are the Friedewald equation or the direct measurement. The Friedewald equation and the direct assay method for LDL cholesterol are about equally good for assessment of the LDL status in patients with chronic renal disease and plasma TG <4.0 mmol/l. Where there are restraints on laboratory budgets, it would appear appropriate that the more expensive direct assay method be restricted to cases in whom plasma TG >4.0 mmol/l or to patients who, for whatever reason, are unable to produce fasting samples.

Comparing a novel equation for calculating low-density lipoprotein cholesterol with the Friedewald equation: A VOYAGER analysis

Aim Plasma low density lipoprotein cholesterol (LDL-C) is a unit measure of cholesterol mass &amp; an estimate of circulating LDL-C. LDL-C is commonly calculated indirectly by Friedewald equation and not directly with enzymatic method. The Friedewald equation underestimates the LDLC compared to direct LDLC particularly in patients with low LDLC and high Triglycerides (TGL). Recently developed Sampson equation (2020) also estimates LDL-C indirectly but is less dependent on the TGL values. The present study compares directly measured LDL-C with above friedewald and sampsons equations. Methodology A Multicentric study (three health centers) measured LDL-C with direct enzymatic method in 8332 samples. The data was collected using electronic database and computed in Microsoft excel. Retrospective analysis was performed after ethical committee approval and waiver of consent. LDL-C values derived from Friedewald equation &amp; Sampson equation was compared with LDL-C from direct enzymatic method. Subgroup analysis for accuracy was done among various direct LDL-C subgroups such as values less than 50 mg/dl, 50–70 mg/dl, 70–150 mg/dl and more than 150 mg/dl. The entire cohort was also subdivided into triglyceride subgroups &amp;lt;150 mg/dl, 150–450 mg/dl, &amp;gt;450 mg/dl and compared with direct LDL-C values. Results Our study results shows that mean direct LDL-C was 85.7mg/dl, mean calculated LDL-C by Sampson and Friedewald equation were 80mg/dl and 76mg/dl respectively. There was statistical significance in mean difference when direct LDL-C is compared with combined Sampson and Friedewald equation as per Games - Howell multiple comparison study in which mean difference was more with Friedewal's equation than with Sampson equation. The overall concordance upwards between Friedewald's equation versus direct LDL-C and Sampson LDL-C equation versus direct LDL-C was similar (81% and 83% respectively). The overall discordance upwards was more with Sampson LDL-C when compared with direct LDL-C (4%), unlike 1.5% when Friedewald's LDL-C compared with direct LDL-C. The overall discordance downwards was less with Sampson's LDL-C when compared with direct LDL-C (12%) unlike, 16% when Friedewald's LDL-C compared with direct LDL-C. Our study showed that mean LDL-C by Friedewald's equation is less accurate in comparison to the mean direct LDL-C values. But mean LDL-C by Sampson equation had close proximity to mean direct LDL-C values and less magnitude of discordance was noted in patients with low LDL-C &amp; high TGL Conclusions Sampson's equation is better than friedewald's equation in estimation of LDL-C. Sampson's equation is ideal, better, easily calculated and incorporated. We have also developed a simple android application to estimate the LDL-C using both the Sampson and the Friedewald equation. We recommend that sampson's equation can be utilized in third world developing countries in planning low LDL-C targets during secondary prevention. Funding Acknowledgement Type of funding sources: None.

Background Ultracentrifugation for LDL-C (low-density lipoprotein cholesterol) measurement is the gold standard, but it is unsuitable for routine use. Direct LDL-C assays and predictive equations such as the Friedewald equation are thus used as alternatives. The Friedewald equation is known to be error-prone in hypertriglyceridaemic patients, as well as in LDL-C levels &amp;lt; 1.8 mmol/L (70 mg/dL) which has become increasingly attainable with the use of pro-protein convertase subtilisin/kexin type 9 inhibitors. This study evaluates the comparability of the Friedewald, extended Martin/Hopkins, Sampson/NIH and four other equations to a direct LDL-C assay to establish a suitable alternative to the Friedewald equation. Methods We analysed 44 194 lipid profiles from a mixed South African population. The Friedewald, extended Martin/Hopkins and Sampson/NIH LDL-C and four other predictive equations (Vujovic, Puavilai, Delong, Anandaraja) were compared to the Beckman Coulter direct LDL-C assay. Non-parametric statistics were used to analyse the data. Results The extended Martin/Hopkins equation displayed the best correlation with direct LDL-C, having the most values fall within the desirable bias (59%) and total allowable error (89%) specifications. In patients with TG values between 4.5 mmol (400 mg/dL) and 9.0 mmol/L (800 mg/dL), the extended Martin/Hopkins equation was more likely to overestimate LDL-C levels, showing a positive median bias of 7.3%, while Friedewald (−21.2%) and Sampson/NIH (−9.8%) showed larger negative median biases as compared to the direct LDL-C assay. The direct LDL-C assay classified 13.9% of patients in the low LDL-C (1.0–1.8 mmol/L) (39–70 mg/dL) category, in comparison to the Martin/Hopkins equation (13.4%), the Sampson equation (14.6%) and the Friedewald equation (16.0%). The extended Martin/Hopkins equation performed better than Sampson/NIH equation in the cohort. Conclusion We suggest the extended Martin/Hopkins equation as an alternative to Friedewald’s equation and direct LDL-C assay. Careful consideration is advised as the choice of analyser platform for the lipid profile used in the equations may influence their performance.

Background It is essential to accurately assess Low-density lipoprotein cholesterol (LDL-C) levels, a key marker for cardiovascular disease often used for treatment recommendations. The Friedewald equation has been used for many years to calculate plasma LDL-C levels, but it has limitations. Therefore, before implementing the NIH equation, we compared LDL-C results from NIH Equation 2 to the Friedewald formula and then to Atellica direct homogeneous assay LDL-C results. Methods A retrospective study of 1200 randomly selected patients out of 53,258 data points pulled from the laboratory information (LIS) system between November 2021 and October 2023. The study evaluated triglycerides, LDL-C, total cholesterol, and HDL-C measurements. The LDL-C calculated using NIH equation 2 has been set in the LIS as a non-reportable test component since November 1, 2021. The results obtained from NIH equation 2 and Friedewald equation were compared. LDL-C levels were measured using an Atellica direct homogeneous assay for an additional 75 specimens. Deming regression analysis compared measured and calculated LDL-C using both formulae. Results The LDL-C calculated using the Friedewald equation has a mean of 106.1 mg/dL and SD 40.1 mg/dL, while the NIH equation has a mean of 108.5 mg/dL and SD 39.9 mg/dL. The average difference between both equations is 2.5 mg/dL, and there is a significant difference between both calculations using paired t-tests (p-value&amp;lt;0.0001). We first compared the calculated LDL-C derived from the Friedewald formula to the NIH equation 2. The regression analysis equation for the Friedewald formula was y = -2.7 + 1.001 X (r = 0.99). When the Triglyceride values &amp;lt;150 mg/dL (N=879), the average difference is 1.3, and the regression equation is -0.45+1.01X(r=0.99). However, when the Triglyceride value &amp;gt;= 150 mg/dL (N=321), the average bias is 5.4 mg/dL, and the regression equation is -11.2+1.05X(r=0.99). The Friedewald formula was compared to the measured LDL-C in 75 specimens; the regression analysis for the Friedewald formula was y = -19.6 + 1.06 X (r = 0.91, p-value &amp;lt;0.0001). The 75 measured LDL-C results were also compared with the NIH formula. The regression analysis of NIH LDL-C with measured LDL-C was y = -5.6 + 0.981 x (r = 0.90, p-value = 0.0002). Both formulae showed a linear relationship against measured LDL-C. The NIH formula outperformed the Friedewald formula; bias difference -7.8(-6.8%) compared to the Friedwald equation bias -12.9(-12.0%). If the NIH equation had been used during this period, an additional 1,116 patients would have had LDL-C results. This is because the Friedewald equation should not be used if the triglyceride value is above 400 mg/dL. Out of the additional patients, 513 (46%) had a high LDL (&amp;gt;100 mg/dL). Conclusions The NIH formula performed better than the Friedewald formula, with a less negative bias when both calculations were compared to direct homogenous measurement. The average difference between the two formulas showed the lowest value when triglyceride &amp;lt; 150 mg/dL. Moving to NIH equation 2 will benefit our population as we had 2% of our patients in the past two years have triglyceride &amp;gt;400 mg/dL.

Background: Apolipoprotein B (Apo B) is an important predictor of the risk of atherosclerotic cardiovascular disease over and above low-density lipoprotein cholesterol (LDL-C), especially in statin-treated patients. Assays of Apo B are not available widely. Objectives: The objective of this study is to derive the Apo B from a lipid profile, using a regression equation and a neural network and compare the results, to compare LDL-C measured by direct assay and a Friedewald equation derived LDL-C in their efficacy to predict Apo B, to determine the effect of lower levels of LDL-C on the prediction models, and to develop an android app “Apo B Calculator” which will calculate the Apo B and also give the predictive accuracy of the result. Methodology: Eight hundred and eighty-five persons were split into a training set and a validation set. Both the regression equation and neural network methods were applied on the training set of 442 patients and the best regression equation and neural network predictive model for Apo B were derived. This was then applied on the validation set of 443 patients to test the R2 of the models. Results: The regression equation Apo B = 25.199 + 0.266 (LDL) + 0.062 (triglycerides level [TGL]) + 0.248 (non-high-density lipoprotein cholesterol) was the best predictor of Apo B when directly measured LDL-C was used. The predictive accuracy of the neural network was lesser than the regression equation (75% vs. 87.4% at 95% confidence interval [CI]). The regression equation for the Friedewald equation derived LDL-C was Apo B = 25.077 + 0.528 friedewald equation (F. LDL) +0.138 (TGL) and was comparable with the neural network (86.4% vs. 85% at 95% CI). The overall efficacy of both the direct assay and Friedewald equation-derived LDL-C were nearly the same (87.4% vs. 86.4% at 95% CI). There was a linear decline in the predictive accuracy of both methods at diminishing LDL-C levels. At lower levels of LDL-C (&lt;70 mg/dl), the accuracy of the Friedewald equation derived LDL-C was a better predictor of Apo B (70% vs. 59.8%). With this data, we developed an android app “Apo B Calculator” which will calculate the Apo B from a directly measured or Friedewald equation derived LDL-C. The app will also mention the predictive accuracy of the results. Conclusions: The regression equation derived from directly measured LDL-C and Friedewald equation derived LDL-C, and the neural network using the Friedewald equation showed near similar efficacy in predicting the Apo B value (87.4%, 86.4%, and 85%). A regression equation using a Friedewald formula is a better predictor of Apo B at LDL-C levels &lt;70 mg/dl. The app “Apo B Calculator” can predict the Apo B from both directly measured and Friedewald equation derived LDL-C and give the predictive accuracy for the method – This will help the clinician to know the Apo B and also the predictive accuracy of such calculated value.

Objective: The Friedewald equation is frequently used to estimate low-density lipoprotein cholesterol (LDL-C) in routine patient care; however, recently many limitations have emerged regarding its use. Aim: Analyse the use of Friedewald equation for dyslipidemia in metabolic syndrome. Methods: Subjects were selected with metabolic syndrome that fulfilled consensus statement for Asians Indians and excluded those with triglyceride (TG) ?400mg/dl, and chronic liver and/or kidney disease. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), TGs, and LDL-C were measured with direct assays. LDL-C was further estimated using the equation and compared with LDL-C by direct assay. Results: The mean and standard deviation of TC, TGs, HDL-C, and LDL-C were 194.7724.38mg/dl, 174.8460.27mg/dl (p&lt;0.0001), 40.685.40mg/dl (p&lt;0.05), and 122.3019.30mg/dl among subjects with metabolic syndrome. On the other hand, Friedewald estimated LDL-C and VLDL-C were 121.2918.84mg/dl and 35.0812.65mg/dl (p&lt;0.0001). Furthermore, a statistically significant higher TGs/HDL-C (p&lt;0.0001) and LDL-C/HDL-C ratios was observed in subjects with metabolic syndrome. However, no significant difference was recorded between the two methods of estimating LDL-C. Conclusion: TGs/HDL-C was found significantly higher among subjects with metabolic syndrome; however, no significant difference between both Friedewald equation and direct measurement method for LDL-C estimation was observed. Hence, the accuracy of LDL-C estimation formulas and direct methods for measurement in patients with the metabolic syndrome requires further exploration. Keywords: Dyslipidemia, Friedewald Equation, Metabolic Syndrome.

IntroductionThe accurate estimation of low-density lipoprotein cholesterol (LDL) is crucial for management of patients at risk of cardiovascular events due to dyslipidemia. The LDL is typically calculated using the Friedewald equation and/or direct homogeneous assays. However, both methods have their own limitations, so other equations have been proposed, including a new equation developed by Sampson. The aim of this study was to evaluate Sampson equation by comparing with the Friedewald and Martin-Hopkins equations, and with a direct LDL method.Materials and methodsResults of standard lipid profile (total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL) and triglycerides (TG)) were obtained from two anonymized data sets collected at two laboratories, using assays from different manufacturers (Beckman Coulter and Roche Diagnostics). The second data set also included LDL results from a direct assay (Roche Diagnostics). Passing-Bablok and Bland-Altman analysis for method comparison was performed.ResultsA total of 64,345 and 37,783 results for CHOL, HDL and TG were used, including 3116 results from the direct LDL assay. The Sampson and Friedewald equations provided similar LDL results (difference ≤ 0.06 mmol/L, on average) at TG ≤ 2.0 mmol/L. At TG between 2.0 and 4.5 mmol/L, the Sampson-calculated LDL showed a constant bias (- 0.18 mmol/L) when compared with the Martin-Hopkins equation. Similarly, at TG between 4.5 and 9.0 mmol/L, the Sampson equation showed a negative bias when compared with the direct assay, which was proportional (- 16%) to the LDL concentration.ConclusionsThe Sampson equation may represent a cost-efficient alternative for calculating LDL in clinical laboratories.

Introduction: Despite more accurate low-density lipoprotein cholesterol (LDL-C) estimates by the Martin (mLDL-C) method, most laboratories still use the Friedewald (fLDL-C) equation. Low non-high density lipoprotein (non-HDL-C) and high triglycerides (TG) drive inaccuracy in LDL-C estimation. We compared a strategy of identifying errors in fLDL-C using non-HDL-C/TG ratios with subsequent reflex direct LDL-C testing to a strategy of using mLDL-C. Methods: We included 4,939,542 individuals (2/3 derivation, 1/3 validation dataset) with TG &lt;400 mg/dL with lipid profiles directly measured via Vertical Auto Profile from the Very Large Database of Lipids. We compared directly measured LDL-C with estimated fLDL-C and mLDL-C. The direct LDL-C assay has an allowable error of 12% which was used as the threshold for accuracy assessment. LDL-C estimates above and below non-HDL-C/TG cutpoints (range 0-2.0) were evaluated for accuracy from the derivation dataset and the 4 best performing ratios were tested in the validation set. Individuals with non-HDL-C/TG ratios below the cutpoints were assumed to require direct LDL-C measurement. Medicare costs ($17 lipid panel; $12 direct LDL-C) were used to estimate added costs of direct LDL-C measurement. Results: Nearly 8% of fLDL-C results deviated &gt;12% from direct LDL-C compared with only 2.5% of mLDL-C results in the entire population. Non-HDL-C/TG ratios of 0.6-0.9 performed best in the derivation dataset. In the validation dataset, a non-HDL-C/TG ratio of 0.7 had the highest area under the curve for identifying &gt;12% error in fLDL-C estimates (Table). At this ratio, 14.5% of fLDL-C samples would need direct LDL-C measurement at an increase in costs of lipid testing by 10%. Conclusions: Use of non-HDL-C/TG ratio &lt;0.7 as screening for direct LDL-C measurement can improve the accuracy of LDL-C estimates in labs using the Friedewald equation. However, such an approach is significantly costlier than using mLDL-C.

A direct LDL cholesterol assay was evaluated using immunoprecipitation (Sigma Diagnostics, St. Louis, MO) with beta-quantification obtained by ultracentrifugation. Excellent intra- and interassay coefficients of variation were obtained (< 4.5%). There was a good correlation (r = 0.88, P < .0001) between the two methods for low-density lipoprotein cholesterol (LDL-C) in 249 samples with triglyceride levels ranging from 13 mg/dL to 2,236 mg/dL and LDL cholesterol levels ranging from 28 mg/dL to 290 mg/dL. Similar correlations were seen for patients with triglyceride levels < 400 mg/dL (r = 0.89, n = 174) and > or = 400 mg/dL (r = 0.89, n = 75). However, using the Friedewald equation, there was a good correlation only in samples with triglyceride levels < 400 mg/dL. No significant differences were found between LDL-C quantitated by the direct LDL assay and beta quantification for patients with dysbetalipoproteinemia (Type III disorder). However, calculated LDL values using the Friedewald equation were found to be significantly higher when compared to beta-quantification in patients with the Type III disorder. There was a slight but significant decrease in LDL-C determined by direct LDL cholesterol assay for non-fasting versus fasting serum (4.7%) despite a strong correlation between these samples (r = 0.98, P < .0001). In addition, freezing samples for 30 days resulted in a significant decrease in levels (15.1%). Thus, this direct LDL cholesterol assay is recommended in place of beta-quantification in hypertriglyceridemic samples (TG > or = 400 mg/dL) and to monitor LDL cholesterol levels in patients with Type III dyslipidemia, because it is less time consuming, more cost-effective and can be adapted to the clinical laboratory.

Background LDL-C represents the primary lipoprotein target for reducing cardiovascular risk. LDL-C can either be calculated or measured directly. Friedewald equation has certain limitations especially with high triglyceride and low LDL-C levels. Although a number of automated direct LDL-C assays are commercially available, non of them is considered to be equivalent to the “gold standard” of direct LDL-C, beta quantitation, a complex and expensive process that is unavailable in routine clinical practice. In atherogenic dyslipidemia condition (ADC) (triglycerides≥2.3 mmol/L and HDL-C&lt;1.0 mmol/L) non-HDL-C and remnant cholesterol are proven additional risk factors. Purpose We compared one of the direct homogeneous assays with the widely used Friedewald's and the new Martin/Hopkins methods of estimation of LDL-C to see the differences in average LDL-C, remnant cholesterol and non-HDL-C levels and in availability of less than 1.8 mmol/L of LDL-C in atherogenic dyslipidemia condition. Methods We investigated 14 906 lipid profiles from fasting blood samples of Hungarian individuals with triglycerides &lt;4.5 mmol/L. Total cholesterol (TC), HDL-C, triglycerides (TG) and direct LDL-C (D-LDL-C) were measured directly by the enzimatic assays. We also estimated calculated LDL-C by the Friedewald's formula (F-LDL-C) and by using the new Martin/Hopkins estimation (MH-LDL-C). We have now prepared first a variant of Martin/Hopkins table in mmol/L, in which the modified adjustable factors of 2.2 are included. We determined also non-HDL-C and remnant cholesterol (RC) as a difference of non-HDL-C and F-LDL-C (F-RC), MH-LDL-C (MH-RC), D-LDL-C (D-RC). Results In the investigated population 19.25% was F-LDL-C, 15.48% MH-LDL-C and 7.92% D-LDL-C below 1.8 mmol/L. ADC occurred at 8.12%. For ADC, when F-LDL-C&lt;1.8 mmol/L (A), mean values for F-LDL-C, MH-LDL-C, D-LDL-C and non-HDL-C were 1.23±0.4; 1.65±0.39; 2.06±0.4 and 2.46±0.5 mmol/L respectively. These mean levels were 1.01±0.36; 1.4±0.3; 1.83±0.3 and 2.15±0.34 mmol/L for MH-LDL-C&lt;1.8 mmol/L (B). For D-LDL-C&lt;1.8 mmol/L (C), mean values were 0.79±0.35; 1.13±0.26; 1.54±0.19 and 1.83±0.25 mmol/L respectively. The average RC values (in mmol/L) for A were F-RC: 1.23±0.36; MH-RC: 0.81±0.18; D-RC: 0.4±0.17, for B 1.14±0.33; 0.74±0.14; 0.32±0.13, and for C 1.04±0.27; 0.70±0.1; 0.29±0.12 respectively. Conclusions The Friedewald equation tends to underestimate and the homogeneous enzimatic direct LDL-C assays to overestimate the LDL-C levels compared to the new, accurate, calculated LDL-C values in atherogenic dyslipidemia condition. Based on the data presented in our investigation we should like to propose that more realistic vasculo-protective lipid status can be attained if we calculate LDL-C using the Martin/Hopkins estimation.

AimsThe 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...