Correlation between Very Low-Density Lipoprotein and Trygliseride with Glycated Hemoglobin Levels in Type 2 Diabetes Mellitus Patients

Patients with Type 2 Diabetes Mellitus (T2DM) have an increased prevalence of dyslipidemia, which contributes to ahigher risk of dyslipidemia- related complications in T2DM such as cardiovascular disease and stroke. This study aimed todetermine the correlation between TG and VLDL-C towards HbA1c levels in a person with T2DM. A retrospective study of 74outpatients with T2DM at Sanglah General Hospital, Denpasar, who examined serum HbA1c and lipid profiles were tracedfor serum TG. From the obtained TG profile, a secondary calculation of VLDL was carried out using the Friedewald equation(TG/5). A correlation test was used to determine the relationship between TG and VLDL-C towards HbA1c levels. Serum TG(212.95±147.46 mg/dL) and VLDL (36.69±23.54 mg/dL) were found to be higher in the group with poor glycemic control(HbA1c > 7 mg/dL) compared to serum TG (111.00±39.56 mg/dL) and VLDL (21.05±6.13 mg/dL) in the group with goodglycemic control (HbA1c ≤ 7 mg/dL) (p < 0.05). A positive correlation between serum TG (r=0.512; p < 0.001) and VLDL(r=0.18; p <0.001) towards HbA1c levels in T2DM patient was found. Insulin resistance increases the production of VLDL andApoC-III in the liver and increased chylomicron absorption in the gastrointestinal tract, causing prolonged postprandiallipemia and disruption of VLDL and TG clearance, thereby resulting in increased TG and VLDL in circulation. There is asignificant positive correlation between serum TG and VLDL towards HbA1c levels in a patient with T2DM.

Expanding The Use Of Friedewald Equation In Lipid Profile Testing Among HIV Positive And Negative Elderly Persons

Hypercholesterolemia and hypocholesterolemia are associated with mortality which warrants routine lipid profile testing. This financially burdens the already overwhelmed health sector especially in developing countries. Additionally, lipid profile test reagent stock-out or failure to afford all tests affects result interpretation. In 1972, James Friedewald published a statistical model to calculate low density lipo-protein. The study aim was to determine the percentage error of the James Friedewald equation in calculating all lipid profile test parameters. A retrospective study from 2018 was performed at Mildmay Uganda involving lipid profile results of 103 persons (48 HIV-positive and 55 HIV-negative) 50 years and older enrolled in a previous cross-sectional study. The Friedewald equation was used to calculate total cholesterol, high density lipoprotein, triglycerides and low density lipo-protein. The percentage error of calculated values in reference to measured values was ascertained. Pearson correlation between measured and calculated results was determined among all persons and classified by HIV status. The total error of calculated analytes was 7% (low density lipo protein), 17% (high density lipo-protein), 39% (triglycerides) and 4% (total cholesterol). Pearson correlations were 0.98 (all persons), 0.98 (HIV-negative) and 0.98 (HIV-positive) for low density lipo-protein, 0.89 (all persons), 0.90 (HIV positive) and 0.88 (HIV-negative) for high density lipo-protein, 0.75 (all persons), 0.76 (HIV-negative) and 0.77 (HIV-positive) for triglycerides, 0.99 (all persons), 0.98 (HIV-negative) and 0.99 (HIV-positive) for total cholesterol. In conclusion, Friedewald equation reliably calculated low density lipoprotein, total cholesterol (most accurate) and high density lipo-protein while triglycerides calculation was erroneous among persons aged ≥ 50 years.

Comparability of 11 different equations for estimating LDL cholesterol on different analysers

Objectives Low-density lipoprotein cholesterol (LDL-C) estimation is critical for risk classification, prevention and treatment of atherosclerotic cardiovascular disease (ASCVD). Predictive equations and direct LDL-C are used. We investigated the comparability between the Martin/Hopkins, Sampson, Friedewald and eight other predictive equations on two analysers, to determine whether the equation or analyser influences predicted LDL-C result. Methods In two unpaired datasets, 9,995 lipid profiles were analysed by the Abbott Architect and 4,782 by the Roche Cobas analysers. Non-parametric statistics and Bland Altman plots were used to compare LDL-C. Results On the Abbott analyser; the Martin/Hopkins, Sampson and Friedewald LDL-C were comparable (median bias ≤1.8%) over a range of 1–4.9 mmol/L. On the Roche platform, Martin/Hopkins LDL-C was comparable to Friedewald (median bias 0.3%) but not to Sampson LDL-C (median bias 25%). In patients with LDL-C <1.8 mmol/L and triglycerides (TG) ≤1.7 mmol/L, predicted LDL-C using Abbott reagents was similar between Martin/Hopkins, Sampson and Friedewald equations but not comparable using Roche reagents. Abbott reagents classified 10–20% of patients in the 1.0–1.8 mmol/L range (Martin/Hopkins 13.4%; Sampson 14.5%; Friedewald 16%; direct LDL-C 13.2%). Roche reagents classified 11–30% in the 1.0–1.8 mmol/L range (Martin/Hopkins 23%; Sampson 11%; Friedewald 25%; direct LDL-C 17%). Conclusions Performance of predictive equations is influenced by the choice of analyser for total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and TG. Replacement of the Friedewald equation with Martin/Hopkins estimation to improve quality of LDL-C results can be safely implemented across analysers, whereas caution is advised regarding the Sampson equation.

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.

Usefulness of novel martin/hopkins and sampson equations over friedewald equation in cardiology outpatient: CVSCORE-TR substudy

Funding Acknowledgements Type of funding sources: None. OnBehalf CVSCORE-TR study group Background Friedewald equation (LDL-Cf) is known to produce inaccurate estimations of low-density lipoprotein cholesterol (LDL-C) when triglycerides are high (&gt;400 mg/dl) or LDL-C is low (&lt;70 mg/dl). Martin/Hopkins (LDL-Cmh) and Sampson (LDL-Cs) equations were developed to overcome these limitations, but few data are available whether these equations offer incremental usefulness over LDL-Cf. Purpose In this pragmatic study, we aimed to evaluate the agreement between LDL-C calculated using LDL-Cmh, LDL-Cs and LDL-Cf equations and to understand whether using LDL-Cmh or LDL-Cs instead of LDL-Cf leads to significant changes on the clinical decision-making Methods 4196 cardiology outpatient cases that were included in a multicenter registry database were analyzed. Each case was assigned into a cardiovascular risk class using web-based SCORE (Systematic COronary Risk Evaluation) algorithm calibrated for high-risk European countries, and relevant European guidelines were used to assess LDL-C targets. LDL-Cf, LDL-Cs and LDL-Cmh were calculated as previously described. Results Compared to LDL-Cmh and LDL-Cs, LDL-Cf was able to correctly identify 96.9%-98.08% of cases as within or out of LDL-C target, respectively, while 1.95%-2.8% of cases were falsely identified as within LDL-C target. Kappa coefficients for agreement between LDL-Cf vs. LDL-Cmh and LDL-Cf vs. LDL-Cs were 0.868 and 0.918 (p &lt; 0.001 for both). For patients not on anticholesterolemic drugs, decision to initiate treatment would be different in 1.2%-1.8% of cases if LDL-Cs or LDL-Cmh were used, respectively. For those already on anticholesterolemic drugs, decisions regarding to treatment intensification would be different in 1.5%-2.4% of cases if LDL-Cs or LDL-Cmh were used. Conclusions Friedewald equation had an excellent degree of agreement with the novel Martin/Hopkins and Sampson formulas in most cardiology outpatients, especially those within the lower end of the cardiovascular risk spectrum. In selected patients, especially those with high or very high risk in whom LDL-Cf &lt; 70 mg/dl or those with a TG &gt; 400 mg/dl, agreement was far worse and thus novel equations might have an incremental usefulness for clinical decision making. Table 1 Reference Comparison Correct estimation Underestimation Overestimation Kappa (p value) All patients that were not on cholesterol-lowering treatment LDL-Cmh LDL-Cf 2785 (98.1%) 51 (1.8%) 3 (0.1%) 0.962 (&lt;0.001) LDL-Cs LDL-Cf 2804 (98.8%) 35 (1.2%) 0 (0.0%) 0.975 (&lt;0.001) Agreement for the indication of cholesterol-lowering treatment for patients not already on cholesterol-lowering drugs. Leftmost column shows the reference method, and the second row shows equation which is compared to the reference method. Abstract Figure

The direct correlation between oxidative stress and LDL-C levels in adults is maintained by the Friedewald and Martin equations, but the methylation levels in the MTHFR and ADRB3 genes differ

Low-density lipoprotein (LDL-C) concentrations are a standard of care in the prevention of cardiovascular disease and are influenced by different factors. This study compared the LDL-C concentrations estimated by two different equations and determined their associations with inflammatory status, oxidative stress, anthropometric variables, food intake and DNA methylation levels in the LPL, ADRB3 and MTHFR genes. A cross-sectional population-based study was conducted with 236 adults (median age 37.5 years) of both sexes from the municipality of João Pessoa, Paraíba, Brazil. The LDL-C concentrations were estimated according to the Friedewald and Martin equations. LPL, ADRB3 and MTHFR gene methylation levels; malondialdehyde levels; total antioxidant capacity; ultra-sensitive C-reactive protein, alpha-1-acid glycoprotein, homocysteine, cobalamin, and folic acid levels; usual dietary intake; and epidemiological variables were also determined. For each unit increase in malondialdehyde concentration there was an increase in the LDL-C concentration from 6.25 to 10.29 mg/dL (p <0.000). Based on the Martin equation (≥70 mg/dL), there was a decrease in the DNA methylation levels in the ADRB3 gene and an increase in the DNA methylation levels in the MTHFR gene (p <0.05). There was a positive relation of homocysteine and cholesterol intake on LDL-C concentrations estimated according to the Friedewald equation and of waist circumference and age based on the two estimates. It is concluded the LDL-C concentrations estimated by the Friedewald and Martin equations were different, and the Friedewald equation values were significantly lower than those obtained by the Martin equation. MDA was the variable that was most positively associated with the estimated LDL-C levels in all multivariate models. Significant relationships were observed based on the two estimates and occurred for most variables. The methylation levels of the ADRB3 and MTHFR genes were different according to the Martin equation at low LDL-C concentrations (70 mg/dL).

Comparison between direct assay and popular equations for Low Density Lipoprotein-cholesterol estimation in Nepalese Population

Background: The aim of this study was to compare LDL-C estimations using various equations with directly measured LDL-C and to find the most accurate and reliable equation for measuring serum LDL-C at different triglycerides level. Materials and Methods: In this study, we performed a retrospective analysis on the database of our Laboratory Information System to retrieve results of lipid profile in patients visiting Dhulikhel Hospital during the period of 6 months. A total of 1420 participants were classified into three groups according to triglyceride (TG) concentrations as follows: <150, 150–199 and >199 mg/dL. LDL-C was calculated using the Friedewald, Chen, Vujovic, Hattori, Anandaraja and modified Friedewald equations and compared with directly measured LDL-C concentration (enzymatic method on Biosystems, BA-400). Results: In most of the instances, calculated LDL-C value was higher than the directly measured LDL-C values with negative mean difference with the exception of Hattori equation. The intraclass correlation coefficient (ICC) between the estimated and directly-measured LDL-C was higher with the Friedewald equation (ICC=0.917; 95% CI: 0.904-0.927) for all serum TG ranges compared with other equations. The reliability of all the equations was good with ICC being above 0.75 while that of the Friedewald equation was excellent in all the TG groups with ICC being above 0.9. Hattori equation was better in estimating LDL-C at normal TG range (ICC=0.927; 95% CI: 0.917-0.937) and borderline high TG (ICC= 0.933; 95% CI: 0.908-0.951). Conclusion: Calculated LDL-C using appropriate equations can be an alternative cost-effective tool to measure LDL-C when the direct measurement cannot be afforded.