Direct Measurement Of Low-density Lipoprotein Cholesterol Research Articles

Comparison of Performance of Various Calculated Low-Density Lipoprotein (LDL) Methods in the Indian Population: A Hospital-Based Study.

In recent times, there has been a surge in proposed alternative approaches to computing low-density lipoprotein cholesterol (LDL-C), with a focus on enhancing precision, particularly within diverse demographic and clinical groups. Our aim is to assess the agreement, precision, and practicality of these methods compared to direct LDL-C measurements, with the goal of identifying the most effective approach for estimating LDL-C in the Indian context. It is a retrospective analytical study. Lipid profile data were gathered from the laboratory and organized in Microsoft Excel for analysis. LDL-C was computed using three different methods: the Friedwald formula, the Martin-Hopkins formula, and Sampson's formula. These calculations were then compared with the direct method of LDL-C estimation in two distinct groups: when triglyceride (TG) levels were less than 400 mg/dL and when TG levels exceeded 400 mg/dL. Bland-Altman plots were generated, and concordance correlation coefficients (CCCs) were computed to determine the most suitable calculated method. Data from 1,776 participants were analysed and divided into two groups. In both Group 1 (TG < 400 mg/dL) and Group 2 (TG > 400 mg/dL) considering bias, limits of agreements, and correlation coefficient, as seen on the Bland-Altman and CCC, Martin-Hopkins equation was found to be performing better than Friedwald and Sampson's equation. In this study, the Martin-Hopkins formula appears to be the most appropriate choice for precise LDL-C level measurements and indicated improved accuracy and consistency in LDL-C measurements, especially in individuals with elevated TG levels. This underscores its importance in ensuring precise assessment and suitable clinical management.

Does LDL-C determination method affect statin prescribing for primary prevention? A register-based study in Southern Denmark.

Examine whether low-density lipoprotein cholesterol (LDL-C) determination method influences the rate of statin initiation for primary prevention of cardiovascular disease. We conducted a register-based retrospective study in the Region of Southern Denmark. Two hospital-based laboratories in the Region directly measure LDL-C whereas four laboratories calculate LDL-C using Friedewald's formula. Physicians do not choose which method is used. We included all statin-naïve patients ≥40 years with no history of cardiovascular disease, diabetes, or chronic kidney disease, who had their LDL-C determined during 2018-2019. There were 202,807 people who had LDL-C determined during the study period (median age 59 years, 44% women) of which 37% had a direct LDL-C measurement. The median reported LDL-C was 3.40 mmol/L (IQR 2.90 to 4.00) for those with a direct measurement versus 3.00 mmol/L (IQR 2.40 to 3.50) for those with calculated LDL-C. For those with direct measurement, re-calculated LDL-C (using Friedewald's formula) was 0.35 mmol/L lower than the reported direct LDL-C measurement. Among those with directly measured LDL-C, 3.6% initiated statins compared with 2.7% of those with a calculated LDL-C. Direct LDL-C measurement led to higher odds of having a statin initiated compared to calculated LDL-C (adjusted odds ratio 1.23, 95% CI 1.17 to 1.30); for those with triglycerides > 1.7 mmol/L the adjusted odds ratio was 1.41 (95% CI 1.30 to 1.52). Differences in the reporting of LDL-C from laboratories using different methods have a substantial influence on physician's decisions to prescribe statins.

Concordance between low density lipoprotein cholesterol concentration measurement by enzymatic method and calculation by Friedewald formula in cardiovascular risk classification

Accurate estimation of low-density lipoprotein cholesterol (LDL-C) is important for cardiovascular risk assessment and guiding cholesterol-lowering therapy. Due to the high cost of β-quantification (Gold standard) and time-consuming, direct measurement of LDL-C is an alternative method. However, unlike the calculation of LDL-C by Friedewald formula, there is an additional cost in terms of reagents for performing a direct LDL-C test. The current study aimed to compare direct LDL-C concentration determination to data calculated by Friedewald formula. 752 lipid profiles of 710 people with LDL-C estimated by direct LDL assay, in the Biochemistry laboratory of university hospital center of Angré, were included in the study. In the same group, LDL-C was calculated using Friedewald formula. Lin’s concordance correlation coefficient (ccc) and Passing-Bablok regression analysis using, MedCal software, were performed to assess the strength of concordance between the 2 methods, and identify any possible bias. The concordance between the two methods was moderate (ρc = 0.9466). Passing-Bablok regression analysis revealed a systematic bias between the two methods. The total error observed (TEobs) between the two methods was higher than allowable total error recommended by the NCEP-ATPIII when LDL-C values was less than 159 mg/dL (4.112 mmol/L). The Friedewald formula resulted in lower LDL-C concentration values. Despite its cost-effectiveness in the estimation of LDL-C, an underestimation of LDL-C levels could result in inaccurate cardiovascular diseases (CVD) risk assessments and potentially significant future societal costs due to inadequate prevention and treatment of CVD.

Comparison of Sampson and extended Martin/Hopkins methods of low-density lipoprotein cholesterol calculations with direct measurement in pediatric patients with hypertriglyceridemia.

The Friedewald equation is the commonly used method of low-density lipoprotein cholesterol (LDL-C) calculation, requiring reflex to direct LDL-C measurement when triglycerides (TG) ≥ 400mg/dL. Recently formulated Sampson and extended Martin/Hopkins methods have been validated with TG up to 800mg/dL and thus have the potential to replace direct LDL-C measurement. Given the growing prevalence of childhood dyslipidemia, the objective of this study was to compare Sampson and extended Martin/Hopkins methods of LDL-C calculation with the direct measurement in a pediatric cohort with 400≤ TG ≤ 799mg/dL. This study retrieved standard lipid panels and corresponding direct LDL-C measurements of 131 patients with 400≤ TG ≤ 799mg/dL from a pediatric population. Following the application of Sampson and extended Martin/Hopkins calculations, calculated values were compared with direct LDL-C measurements using ordinary least squares linear regression analysis and bias plotting. Both Sampson and extended Martin/Hopkins LDL-C calculations exhibited a strong correlation with the direct measurements (Pearson r=0.89) in patients with 400≤ TG ≤ 800mg/dL. Average percentages of bias of 45% and 21% were found between the direct LDL-C measurements and Sampson or extended Martin/Hopkins calculations, respectively. Both Sampson and extended Martin/Hopkins calculations are applicable as clinical alternatives of direct LDL-C measurement in pediatric patients given 400≤ TG ≤ 799mg/dL.

Correlation of LDL Cholesterol Calculated by Friedewald’s, Puavilai’s, Vujovic’s, de Cordova’s and Martin’s Formulae with Directly Measured LDL Cholesterol: A Cross-sectional Study

Introduction: Measurement of Low Density Lipoprotein Cholesterol (LDL-C) carries high importance in the management of Cardiovascular Disease (CVD). Direct LDL-C measurement is preferred method but this is expensive and inconvenient for the routine laboratories. To date, various types of formulae have been introduced. However, accurate estimation of LDL-C by formula is a challenge. Aim: To determine that which of these calculated formulae (Friedewald’s, Puavilai’s, Vujovic’s, de Cordova’s and Martin’s formulae) show maximum correlation with directly measured LDL-C at different serum triglyceride levels. Materials and Methods: The present cross-sectional study was conducted in the Department of Biochemistry, KLE Centenary Charitable Hospital and Medical Research Centre, Belgaum, Karnataka, India, from December 2020 to December 2021. A total of 280 outpatient fasting complete lipid profiles of patients, aged between 18-50 years were included in the study. LDL-C measured by Friedewald’s formula, Puavilai’s formula, Vujovic’s formula, de Cordova’s formula and Martin’s formula were compared with directly measured LDL-C. Comparison of calculated LDL-C with directly measured LDL-C was done at following Triglyceride (TG) ranges as group 1: &lt;200 mg/dL, group 2: 200-300 mg/dL, group 3: 300-400 mg/dL and group 4: &gt;400 mg/dL. Data analysis was done using Pearson’s correlation coefficient and two paired t-test. Results: Of total 280 samples, 124 participants were in group 1, 91 participants in group 2, 36 participants in group 3 and 29 participants in group 4, and there were 130 males and 150 females. The mean age in group 1, 2, 3 and 4 was 40.9±8.0 years, 38.8±9.2 years, 39.1±10.0 years and 39.8±8.2 years, respectively. Martin’s formula showed maximum correlation with r-value of 0.9979 compared to Friedewald’s, Puavilai’s formula, Vujovic’s formula and de Cordova’s formula. The mean difference was least for Martin’s formula 0.31±3.53 compared to other formulas. Percentage of error was least for Martin’s formula (0.23%) in total study sample and in all groups. Martin’s LDL-C shows highest concordance (90.90%) compared to Frielwald’s (79.60%), Puavilai’s (86.00%), Vujovic’s (83.88%) and de Cordova’s formula (82.76%). Conclusion: In the present study, Martin’s formula showed highest correlation, least mean difference, highest concordance and low percentage of errors in all the groups compared to Frieldwald’s formula, Puavilai’s formula, Vujovic’s formula and de Cordova’s formula.

Machine Learning Estimation of Low-Density Lipoprotein Cholesterol in Women With and Without HIV.

Low-density lipoprotein cholesterol (LDL-C) is typically estimated from total cholesterol, high-density lipoprotein cholesterol, and triglycerides. The Friedewald, Martin-Hopkins, and National Institutes of Health equations are widely used but may estimate LDL-C inaccurately in certain patient populations, such as those with HIV. We sought to investigate the utility of machine learning for LDL-C estimation in a large cohort of women with and without HIV. We identified 7397 direct LDL-C measurements (5219 from HIV-infected individuals, 2127 from uninfected controls, and 51 from seroconvertors) from 2414 participants (age 39.4 ± 9.3 years) in the Women's Interagency HIV Study and estimated LDL-C using the Friedewald, Martin-Hopkins, and National Institutes of Health equations. We also optimized 5 machine learning methods [linear regression, random forest, gradient boosting, support vector machine (SVM), and neural network] using 80% of the data (training set). We compared the performance of each method using root mean square error, mean absolute error, and coefficient of determination (R2) in the holdout (20%) set. SVM outperformed all 3 existing equations and other machine learning methods, achieving the lowest root mean square error and mean absolute error, and the highest R2 (11.79 and 7.98 mg/dL, 0.87, respectively, compared with those obtained using the Friedewald equation: 12.45 and 9.14 mg/dL, 0.87). SVM performance remained superior in subgroups with and without HIV, with nonfasting measurements, in LDL <70 mg/dL and triglycerides > 400 mg/dL. In this proof-of-concept study, SVM is a robust method that predicts directly measured LDL-C more accurately than clinically used methods in women with and without HIV. Further studies should explore the utility in broader populations.

A Comparison between Eight Formulas for the Estimation of Plasma Low-Density Lipoprotein Cholesterol in the Saudi Arabian Population

CONTEXT: Low-density lipoprotein cholesterol (LDL-C) is the classical target in cardiovascular (CV) disease management and is usually estimated by Friedewald's formula. However, this formula may over- or underestimate LDL-C levels.AIMS: Our aim is to compare eight LDL-C-estimating formulas to the direct LDL-C measurement and validate their use in the Saudi population.SETTINGS AND DESIGN: This was a retrospective study.SUBJECTS AND METHODS: A blood sample of fasting 669 Saudi subjects was tested for lipid profiles in King Abdulaziz University Hospital Laboratory, from which directly measured LDL-C was obtained. LDL-C was then estimated from eight different formulas: Friedewald's, Cordova's, Hata's, Puavilai's, Chen's, Ahmadi's, Hattori's, and Vujovic's, which were all compared to direct LDL-C.STATISTICAL ANALYSIS USED: Mean and standard deviation, paired t-test, and Pearson's correlation were used for statistical analysis.RESULTS: The mean differences between the direct LDL-C and Hattori and Chen's LDL-C were 0.03 and 0.08 mmol/L, respectively; P < 0.001, while the mean difference observed with Hata, Friedewald, Puavilai, and Vujovic's formulas were higher in comparison: 0.15, 0.24, 0.29, and 0.33 mmol/L, respectively, P < 0.001. Ahmadi and Cordova's LDL-C were estimated to be 0.60 and 0.64 mmol/L more than direct LDL-C levels, respectively, which showed the highest discordance with direct LDL-C, P < 0.001. At a triglyceride (TG) level of <4.5 mmol/L, Hattori also had the best agreement with direct LDL-C, with a mean difference of 0.04 mmol/L, and with TG >4.5 mmol/L, their mean difference was 0.21 mmol/L. All estimated LDL-C strongly correlated with direct LDL-C, except for Ahmadi's.CONCLUSIONS: Hattori's LDL-C had the best agreement with the direct LDL-C, and across all TG levels. However, we recommend directly measuring LDL-C in those with high CV risk.

Comparison between Values of Low Density Lipoprotein Cholesterol as Estimated by Direct Enzymatic Method with Calculated Methods Applying Friedewald’s Equation and Novel’s Equation: A Cross-sectional Study

Introduction: Lipid profile is routinely used as a screening test to identify the risk of Cardiovascular Diseases (CVD). Elevated Low Density Lipoprotein cholesterol (LDL-c) is an important modifiable risk factor of atherosclerotic CVD. The LDL-c lowering strategy is a known recommendation for the prevention and treatment of CVD. The gold standard method of LDL-c estimation is β-quantification by ultra centrifugation. Other methods include Direct LDL-c measurement (D-LDL-c) using enzymatic assay which is tedious, time consuming and expensive. Hence, calculated method using Friedewald’s equation (F-LDL-c) is routinely used in clinical laboratories in India. Aim: To compare LDL-c values as estimated by direct enzymatic method with LDL-c values obtained by Friedewald’s equation and Novel’s equation, and, also to assess the effects of LDL-c values obtained by both the methods towards the risk stratification of CVD. Materials and Methods: A cross-sectional study, was conducted in the Central Diagnostic Laboratory of Mandya Institute of Medical Sciences, Mandya, Karnataka, India, for a duration of three months from July to September 2020, where, 600 subjects, aged 20-75 years, visiting for routine lipid profile estimation were included. LDL-c was estimated by direct enzymatic method (D-LDL-c) and calculated methods using Friedewald’s {F-LDL-c=TC-HDL-c- (TG/5)} and Novel’s equation {N-LDL-c=TC-HDL-c-(TG/Adjustable factor)}. Values obtained by calculated methods were compared with D-LDL-c values. The LDL-c values obtained were compared at different ranges of Total Cholesterol (TC), Triglycerides (TG) and High-Density Lipoprotein cholesterol (HDL-c). The association between direct and calculated LDL-c values were analysed by Pearson’s correlation. Receiver Operator Characteristic Curve (ROC) analysis was done to predict the better diagnostic method among the calculated methods of LDL-c. Results: The mean±SD of D-LDL-c (115.68±36.94 mg/dL) was high compared to F-LDL-c (106.95±33.48 mg/dL) and N-LDL-c (110.78±32.58 mg/dL). The mean difference between D-LDL-c and N-LDL-c (4.9±4.36 mg/dL) was low compared to F-LDL-c (8.75±3.46 mg/dL). Significant positive correlation was observed between D-LDL-c vs F-LDL-c (r=0.96; p=&lt;0.001) and D-LDL-c vs N-LDLc (r=0.97; p=&lt;0.001). The ROC showed maximum AUC value for N-LDL-c than F-LDL-c at a cut-off value of 100 mg/dL. LDL-c as estimated by Novel’s and Friedewald’s equation led to approximately 5% and 10% less patients being subjects for lipid lowering therapy respectively as compared to D-LDL-c. Conclusion: In conclusion, the use of Novel’s equation for LDL-c estimation instead of Friedewald’s equation could be associated with the small net increase in lipid lowering agent eligible population for primary prevention of atherosclerotic CVD. Replacement of Friedewald’s equation by Novel’s equation would enable for the improved accuracy of LDL-c estimation especially at higher levels of TC, TG and lower levels of HDL-c.

Comparison of the effectiveness of Martin\u2019s equation, Friedewald\u2019s equation, and a Novel equation in low-density lipoprotein cholesterol estimation

Low-density-lipoprotein cholesterol (LDL-C) is the main target in atherosclerotic cardiovascular disease (ASCVD). We aimed to validate and compare a new LDL-C estimation equation with other well-known equations. 177,111 samples were analysed from two contemporary population-based cohorts comprising asymptomatic Korean adults who underwent medical examinations. Performances of the Friedewald (FLDL), Martin (MLDL), and Sampson (SLDL) equations in estimating direct LDL-C by homogenous assay were assessed by measures of concordance (R2, RMSE, and mean absolute difference). Analyses were performed according to various triglyceride (TG) and/or LDL-C strata. Secondary analyses were conducted within dyslipidaemia populations of each database. MLDL was superior or at least similar to other equations regardless of TG/LDL-C, in both the general and dyslipidaemia populations (RMSE = 11.45/9.20 mg/dL; R2 = 0.88/0.91; vs FLDL: RMSE = 13.66/10.42 mg/dL; R2 = 0.82/0.89; vs SLDL: RMSE = 12.36/9.39 mg/dL; R2 = 0.85/0.91, per Gangnam Severance Hospital Check-up/Korea Initiatives on Coronary Artery Calcification data). MLDL had a slight advantage over SLDL with the lowest MADs across the full spectrum of TG levels, whether divided into severe hyper/non-hyper to moderate hypertriglyceridaemia samples or stratified by 100-mg/dL TG intervals, even up to TG values of 500–600 mg/dL. MLDL may be a readily adoptable and cost-effective alternative to direct LDL-C measurement, irrespective of dyslipidaemia status. In populations with relatively high prevalence of mild-to-moderate hypertriglyceridaemia, Martin’s equation may be optimal for LDL-C and ASCVD risk estimation.

Why Should We Measure Low-Density Lipoprotein Cholesterol Directly? Comparison of Low-Density Lipoprotein Cholesterol Assessment by Friedewald Estimation, and Direct Measurement

Intorduction: Plasma levels of low-density lipoprotein cholesterol (LDL-C) are an important biomarker for coronary artery disease. In clinical and research settings worldwide, levels LDL-C are often not measured and are estimated using the Friedewald equation (total cholesterol - HDL cholesterol - triglycerides)/5). Bias of either over or underestimation of LDL-C can be corrected by direct measurement of LDL-C. We assessed the precision of the Friedewald equation in a heterogonous patients population within a wide range of lipid levels. Methods: A sample of consecutive fasting lipid profiles was obtained from ambulatory and hospitalized patients at the Chaim Sheba Medical Center, Tel-Hashomer. LDL-C concentrations were directly measured (dir LDL-C) (Olympus, Ireland) and correspondingly calculated at by the Friedewald equation (calc LDL-C). Results: 32,245 samples were analyzed. In 93% of the samples, underestimation of plasma levels of LDL-C was observed using the Friedewald equation. In 11,054 patients (34.3%), the difference between dir LDL and calc LDL were over 10mg/dl. In 7,693 patients (23.8%), the difference between dir LDL and calc LDL were over 20mg/dl. The difference between dir LDL and calc LDL correlated with plasma TG levels, including TG levels within the normal range. The difference between cal LDL and dir LDL levels is inversely correlated to cholesterol plasma levels. Conclusions: Direct measurement of LDL-C is more precise than Friedewald’s formula and overcomes the inaccurateness, due to elevated TG levels or relatively low LDL-C levels, in the setting of a heterogeneous Israeli population. In the era of extremely low LDL-C treatment goals, our findings require consideration due to their clinical importance and direct measurement of plasma LDL-C should be implemented as underestimation of LDL levels may lead to inappropriate therapeutic decisions.

Abstract MP72: Using Non-HDL-C/Triglyceride Ratio To Screen For Direct LDL-C Testing: Improving LDL-C Estimates At A Cost

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.

Treatment target re-classification of subjects comparing estimation of low-density lipoprotein cholesterol by the Friedewald equation and direct measurement of LDL-cholesterol

Aims: To compare low-density lipoprotein cholesterol (LDL-C) values calculated by the Friedewald equation with direct LDL-C in patient samples and assess the possible impact on re-classification of LDL-C target values for primary prevention or high cardiovascular disease (CVD) risk (<2.5 mmol/L) and secondary prevention or very high CVD risk (<1.8 mmol/L). LDL-C is an important CVD risk factor. Over the last decade, there has been a change in laboratory methodology from indirectly calculated LDL-C with the Friedewald equation to direct LDL-C measurements (dLDL-C).Methods: Reported results for plasma triglycerides, total cholesterol, high-density lipoprotein-cholesterol, and dLDL-C from 34,981 samples analyzed in year 2014 were extracted from the laboratory information system, Uppsala University Hospital, Uppsala, Sweden.Results: dLDL-C was approximately 10% lower than the corresponding LDL-C results calculated by the Friedewald equation in both men and women. In subjects with triglyceride concentrations above 4 mmol/L (n = 1250) the same discordant pattern was seen as for the entire study population. Altogether 5469 out of 18,051 men (30.3%) and 4604 out of 16,928 women (27.2%) were down-classified at least one CVD risk category. A very small number of subject was up-classified, in total 37 out of 18,051 men (0.2%) and 28 out of 16,928 women (0.2%).Conclusions: The two LDL-C methods had a high concordance, but the direct LDL-C measurement consistently gave approx. 10% lower values, and this caused one-third of subjects to be re-classified as having a lower cardiovascular disease risk in relation to recommended LDL-C target values and decision limits.

Validation of the Friedewald formula for the estimation of low density lipoprotein cholesterol in a sub-Saharan African population

Introduction : low density lipoprotein cholesterol (LDL-C) levels are used to estimate cardiovascular disease (CVD) risk and to guide prescriptions. To circumvent the challenges of direct LDL-C measurement, guidelines recommend the use of Friedewald formula derived LDL-C levels. Despite reported limitations of this formula, its validity in sub-Saharan Africans has not been adequately investigated. The objective was to assess the validity of the Friedewald formula derived against directly measured LDL-C in adult Cameroonians. Methods : we reviewed the fasting lipid profiles of 2500 patients, performed between March 2012 and January 2016 using enzymatic colorimetric method (reference), at the Douala General Hospital laboratory. The Friedewald formula was used to calculate LDL-C from total cholesterol, high density lipoprotein cholesterol and triglyceride levels. Calculated LDL-C values were compared to the reference values and clinical significance of differences between the two methods was assessed using total error allowable (TEa). Results : the difference between means of Friedewald-calculated and the reference LDL-C values was neither statistically nor clinically significant (3.33±1.51 vs. 3.33 ± 1.25 mmol/l; p = 0.704). The calculated LDL-C correlated positively with the measured LDL-C value (r = 0.749) and both methods showed a good agreement on Bland-Altman plot. Conversely, there was only moderate agreement (kappa=0.478, 95% CI: 0.455-0.502) between the two values in the stratification of cardiovascular risk according to the National Cholesterol Education Programme/Adult Treatment Panel III. Consequently, 40.6% of the participants were misclassified. Conclusion : Friedewald formula is technically accurate but has a modest clinical accuracy which can translate into a substantial misclassification of patients’ cardiovascular risk and subsequent inappropriate therapeutic decisions.

Underestimation of Low Density Lipoprotein-Cholesterol With the Friedewald Equation Versus a Direct Homogenous Low Density Lipoprotein-Cholesterol Assay.

Low-density lipoprotein cholesterol (LDL-C) concentrations are the primary therapeutic target in patients with atherosclerotic cardiovascular disease (ASCVD). However, at low LDL-C concentrations, there is a significant underestimation using the Friedewald equation compared with ultracentrifugation. In this pilot study, we compared LDL-C concentrations obtained using the Friedewald equation (LDL-F) vs those concentrations from a direct LDL-C (LDL-D) assay in 152 consecutive specimens from patients with triglyceride levels between 200-399 mg/dL and LDL-F <100 mg/dL. Also, we compared LDL-F and LDL-D results to the novel formula (LDL-N). The LDL-F value was significantly lower than that of LDL-D when LDL concentrations were 70-99 mg/dL (P <.001, 14% negative bias), and this decrease was accentuated in specimens with LDL <70 mg/dL, (P <.001, 27% negative bias). When compared with the LDL-N value, LDL-F and LDL-D values showed a 17% and 2% negative bias for specimens with LDL-C values of 70-99 mg/dL and 36% and 1% negative bias, respectively, at LDL-C <70 mg/dL (P <.001 for comparisons of LDL-F and LDL-N values). To provide accurate LDL-C levels in patients at high risk for ASCVD, if beta quantification by ultracentrifugation is unavailable and if LDL-C is <100 mg/dL and triglycerides are 200-399 mg/dL, laboratories should revert to direct LDL-C measurements or use the novel formula. Although LDL-N is more cost-effective, LDL-D can be run on most platforms, does not require a specimen from a fasting individual, is standardized, and has the advantage of being validated in large trials such as the Heart Protection Study.

Comparison of Different estimated Formulas with Direct Estimation of Low-density Lipoprotein Cholesterol

ABSTRACT Introduction Recent recommendations of the Adult Treatment Panel and the Adolescents Treatment Panel of the National Cholesterol Education Program make the low-density lipoprotein cholesterol (LDL-C) levels in serum the basis of classification and management of hypercholesterolemia. This makes accurate reporting of LDL-C decisive in the management of coronary heart disease (CHD). Direct measurement of LDL by homogeneous method is accurate but reagent is costly. Therefore, we have to compare different calculated LDL values with direct LDL (D-LDL) values. Aim The aim of this study was (1) to decide if LDL-C level was underestimated/overestimated after it was calculated using the formulae compared with direct measurement of LDL-C and (2) to choose the best calculated method that compares maximum with the direct method. Materials and methods We measured total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), D-LDL by direct homogeneous method in 500 fasting samples. Simultaneously, Friedewald's (F-LDL-C), modified Friedewald's (MF-LDL-C), and Anandaraja's (A-LDL-C) formulas were also used for calculation of LDL-C. Results A good correlation was found between D-LDL-C as compared with F-LDL-C, MF-LDL-C, and A-LDL-C. Pearson's coefficient of correlation between MF-LDL-C and D-LDL-C was 0.94, which was moderately higher than other calculated methods. Pearson's coefficient of correlation between A-LDL-C and D-LDL-C was 0.92 and F-LDL-C and D-LDL was 0.93. Conclusion In conclusion, among the three LDL-C formulas, the Friedewald formula and Anandaraja' s formulas give a higher percentage of error compared with the modified Friedewald formula Therefore, modified Friedewald's formula is better than the other two formulae for calculating LDL-C in a more cost-effective manner and can be used in large population studies. How to cite this article Kanani DN, Mishra A. Comparison of Different Estimated Formulas with Direct Estimation of Low-density Lipoprotein Cholesterol. Indian J Med Biochem 2017;21(2):151-156.

Hematologic, Plasma Biochemical, and Lipid Panel Reference Intervals in Orange-winged Amazon Parrots ( Amazona amazonica ).

To establish reference intervals in orange-winged Amazon parrots ( Amazona amazonica ) for the complete blood count, plasma biochemical values, and lipid panel and to evaluate age- and sex-related variations, blood samples were obtained from 29 healthy juvenile and adult parrots. Concentrations of total protein, bile acids, phosphorus, total cholesterol, low-density-lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol were significantly higher in adult compared with juvenile birds, while uric acid concentration was significantly higher in juveniles. The white blood cell count, lymphocyte count, and phosphorus and potassium concentrations were significantly higher in females, while chloride concentration was significantly higher in males. In this species, direct measurement of LDL-C resulted in lower concentrations than LDL-C calculated with the Friedewald formula. Assessment of the agreement between the calculated and measured LDL-C concentrations indicated a systematic bias of 19.1 mg/dL and a proportional bias of 1.07. A correction factor of -19 mg/L could be applied to the Friedewald formula, to obtain a result closer to the measured LDL-C, providing clinically acceptable (<20% difference) agreement in 66% of the samples. Triglyceride concentrations within the range measured in healthy birds of the present study did not significantly affect the bias between calculated and directly measured LDL-C. Further studies are needed to investigate the impact of nutritional factors, genetics, and exercise on biochemistry and lipoprotein panel analytes in orange-winged Amazon parrots.

Clinical Significance of Low Density Lipoprotein Cholesterol Measurements: Direct Versus Indirect Method

Introduction: Estimation of low density lipoprotein cholesterol (LDL-C) is crucial in management of coronary artery disease patients. The management of dyslipidemia is largely based on the concentration of LDL-C. The objective of this study was to compare direct measurement of LDL-C determined by a homogenous method with LDL-C estimation done by Friedewald formula (FF) in heterogeneous populations. Methods: In this cross sectional study, we measured LDL-C by homogenous method (D-LDL-C) in 1,000 fasting samples &amp; compared with FF (F–LDL-C) used for calculation of LDL-C. The measurements of total cholesterol (TC) and triglycerides (TG) were performed using traditional enzymatic methods. The measurements of high density lipoprotein cholesterol (HDL-C) and LDL-C were performed using direct methods with precipitation, and the estimation of the LDL-C fraction was calculated using the FF. Results: Correlation analysis shows that the two methods had significant correlation (p&lt;0.0001). However the FF had positive bias in regard to direct method with TG levels ≤150 mg/dL. No bias was observed between the methods for TG levels from 151-200 mg/dL &amp; from 201-300 mg/dL. Whereas, TG levels from 301-400 mg/dL shows negative bias by FF. Conclusion: The Friedewald’s formula does not shows homogenous performance for estimating LDL-C levels in samples with different TG levels as compared with that of direct method.

Assessing the Validity of Friedewald's Formula and Anandraja's Formula For Serum LDL-Cholesterol Calculation.

An important aspect of the assessment of cardiovascular risk for a dyslipidemic subject is the estimation of serum Low-Density Lipoprotein Cholesterol (LDL-C). There are many homogenous assays currently available for the estimation of serum LDL-C. Most clinical laboratories determine LDL-C (mg/dL) by Friedewald's formula (FF), LDL-C = (TC) - (HDL-C) - (TG/5). Recently Anandaraja and colleagues have derived a new formula for calculating LDL-C, AR-LDL-C = 0.9 TC- (0.9 TG/5)-28. The aim of the study was: a) to determine if, and to what extent, LDL-C level was underestimated/overestimated when it was calculated using the formulae compared with direct measurement of LDL-C, and b) to determine which of the calculated formulae show maximum correlation with direct LDL cholesterol method at different TG levels. A cross-sectional study. Record analysis was done from the 370 (TG <400mg/dl) lipid profile reports of patients above 18 years. LDL-C estimation was done by homogenous assay and also calculated using the Friedewald's Formula and Anandaraja's Formula. The mean LDL-C levels were 105.17± 43.4, 102.98 ±42.5, and 98.20 ±43.7 mg/dl for D-LDL-C, F-LDL-C and AR-LDL-C, respectively. A good correlation was found between the calculated LDL-C methods and Direct Low-Density Lipoprotein Cholesterol method (D-LDL-C) assay, that is, F-LDL-C versus D-LDL-C (r = 0.937) and AR-LDL-C versus D-LDL-C (r= 0.918). Bland-Altman plot for FF-LDL-C & AR-LDL-C showed minimal negative bias. FF-LDL-C correlated maximally with D-LDL-C estimation at all levels of triglycerides except at TG < 100mg/dl. At TG < 100mg/dl, Anandaraja's Formula works better. FF-LDL-C can be used in place of D-LDL-C when the direct method cannot be afforded.

Validation of the Estimation of Low-density Lipoprotein Cholesterol by the Modified Friedewald Equation in Ethnic Chinese Adults Living in Taiwan.

The Friedewald equation has been used as the standard formula for the estimation of very low-density lipoprotein cholesterol (VLDL-C) to calculate the serum levels of low-density lipoprotein cholesterol (LDL-C). However, the usefulness of this formula in non-Caucasians has been challenged in recent years. The aim of this study was to assess the validity of the conventional and modified Friedewald equation in an ethnic Chinese adult population. We prospectively recruited 938 subjects from the Lipid Clinic of the National Taiwan University Hospital. The fasting lipids, including cholesterol, high-density lipoprotein cholesterol, LDL-C, VLDL-C, and triglycerides (TGs), of each participant were measured and we constructed a prediction model for the estimation of LDL-C by the modified Friedewald equation. The constant values, used to estimate the VLDL-C concentration, were different in the Friedewald equation in the subgroups exhibiting different cardiovascular characteristics, ranging from 4.45 to 6.63, if we calculated the equation by a direct LDL-C measurement. According to the results of a stepwise multiple linear regression analysis excluding the TG levels ≥400 mg/dL, an equation for the individual constant Y estimation was as follows: Constant Y = 4.39 + (-0.59) if the age ≥50 years + 0.98 if men + TG group (2.06 if the TG levels were between 150-399 mg/dL; 1.07 if the TG levels were between 100-149 mg/dL) + (-0.49) if the cholesterol levels ≥240 mg/dL + the body mass index (BMI) group (0.8 if BMI ≥27 kg/m(2); 0.48 if BMI =24-27 kg/m(2)). This modified Friedewald formula provides a new and simple equation for calculating the LDL-C levels in ethnic Chinese people.

Does friedewald formula underestimate the risk of ischemic heart disease?

Traditionally Friedewald formula has been used to calculate low density lipoprotein cholesterol (LDL-C) concentration though now direct homogenous methods for its measurement are also available. Clinical guidelines recommend the use of calculated LDL-C to guide therapy because the evidence base for cholesterol management is derived almost exclusively from trials that use calculated LDL, with direct measurement of LDL-C being reserved for those patients who are non fasting or with significant hypertriglyceridemia. In this study our aim was to compare calculated and direct LDL and their variation at different cholesterol and triglyceride levels. Fasting lipid profile estimation was done on 503 outpatients in a tertiary hospital. Both direct and calculated LDL were then compared. Mean fasting direct LDL was found to be higher than calculated LDL in 87.1% of subjects by 8.64±8.35mg/dl. This difference was seen a all levels of cholesterol and triglyceride. Using 130mg/dl LDL cholesterol as cut off fewer subjects were classified as high risk by calculated LDL than direct LDL. In conclusion, direct LDL is higher than calculated LDL. Compared with direct measurement, the Friedewald calculation underestimates the risk for ischemic heart disease.