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Comparison of Formulas for Calculating Low-density Lipoprotein Cholesterol in General Population and High-risk Patients with Cardiovascular Disease.

ABSTRACT: BACKGROUND AND OBJECTIVES:Low-density lipoprotein cholesterol (LDL-C), an established cardiovascular risk factor, can be generally determined by calculation from total cholesterol, high-density lipoprotein cholesterol, and triglyceride concentrations. The aim of this study was to compare LDL-C estimations using various formulas with directly measured LDL-C in a community-based group and hospital-based group among the Korean population. SUBJECTS AND METHODS:A total of 1498 participants were classified into four groups according to triglyceride concentrations as follows: <100, 100-199, 200-299, and ?300 mg/dL. LDL-C was calculated using the Friedewald, Chen, Vujovic, Hattori, de Cordova, and Anandaraja formulas and directly measured using a homogenous enzymatic method. Pearson's correlation coefficients, intraclass correlation coefficients (ICC), Passing & Bablok regression, and Bland-Altman plots were used to evaluate the performance of six formulas. RESULTS:The Friedewald formula had the highest accuracy (ICC=0.977; 95% confidence interval 0.974-0.979) of all the triglyceride ranges, while the Vujovic formula had the highest accuracy (ICC=0.876; 98.75% confidence interval 0.668-0.951) in people with triglycerides ?300 mg/dL. The mean difference was the lowest for the Friedewald formula (0.5 mg/dL) and the percentage error was the lowest for the Vujovic formula (30.2%). However, underestimation of the LDL-C formulas increased with triglyceride concentrations. CONCLUSION:The accuracy of the LDL-C formulas varied considerably with differences in triglyceride concentrations. The Friedewald formula outperformed other formulas for estimating LDL-C against a direct measurement and the Vujovic formula was suitable for hypertriglyceridemic samples; it could be used as an alternative cost-effective tool to measure LDL-C when the direct measurement cannot be afforded.

SUBMITTER: Choi H

PROVIDER: S-EPMC5054182 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Comparison of Formulas for Calculating Low-density Lipoprotein Cholesterol in General Population and High-risk Patients with Cardiovascular Disease.

Choi Hansol H Shim Jee-Seon JS Lee Myung Ha MH Yoon Young Mi YM Choi Dong Phil DP Kim Hyeon Chang HC

Korean circulation journal 20160928 5

<h4>Background and objectives</h4>Low-density lipoprotein cholesterol (LDL-C), an established cardiovascular risk factor, can be generally determined by calculation from total cholesterol, high-density lipoprotein cholesterol, and triglyceride concentrations. The aim of this study was to compare LDL-C estimations using various formulas with directly measured LDL-C in a community-based group and hospital-based group among the Korean population.<h4>Subjects and methods</h4>A total of 1498 particip ...[more]

PMID: 27721861

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Project description:Background Conventional "low-density lipoprotein cholesterol (LDL-C)" assays measure cholesterol content in both low-density lipoprotein and lipoprotein(a) particles. To clarify the consequences of this methodological limitation for clinical care, our study aimed to compare associations of "LDL-C" and corrected LDL-C with risk of cardiovascular disease and to assess the impact of this correction on the classification of patients into guideline-recommended LDL-C categories. Methods and Results Lipoprotein(a) cholesterol content was estimated as 30% of lipoprotein(a) mass and subtracted from "LDL-C" to obtain corrected LDL-C values (LDL-Ccorr30). Hazard ratios for cardiovascular disease (defined as coronary heart disease, stroke, or coronary revascularization) were quantified by individual-patient-data meta-analysis of 5 statin landmark trials from the Lipoprotein(a) Studies Collaboration (18 043 patients; 5390 events; 4.7 years median follow-up). When comparing top versus bottom quartiles, the multivariable-adjusted hazard ratio for cardiovascular disease was significant for "LDL-C" (1.17; 95% CI, 1.05-1.31; P=0.005) but not for LDL-Ccorr30 (1.07; 95% CI, 0.93-1.22; P=0.362). In a routine laboratory database involving 531 144 patients, reclassification of patients across guideline-recommended LDL-C categories when using LDL-Ccorr30 was assessed. In "LDL-C" categories of 70 to <100, 100 to <130, 130 to <190, and ?190 mg/dL, significant proportions (95% CI) of participants were reassigned to lower LDL-C categories when LDL-Ccorr30 was used: 30.2% (30.0%-30.4%), 35.1% (34.9%-35.4%), 32.9% (32.6%-33.1%), and 41.1% (40.0%-42.2%), respectively. Conclusions "LDL-C" was associated with incident cardiovascular disease only when lipoprotein(a) cholesterol content was included in its measurement. Refinement in techniques to accurately measure LDL-C, particularly in patients with elevated lipoprotein(a) levels, is warranted to assign risk to the responsible lipoproteins.

Project description:Background Epidemiological studies show that women are generally at lower risk for cardiovascular disease than men. Here, we investigated the sex-specific differential effect of genetically increased low-density lipoprotein cholesterol (LDL-C) on cardiovascular disease (CVD) and other lipid-associated diseases. Methods and Results This is a 2-sample Mendelian randomization study that uses individual participant data from 425 043 participants from the UK Biobank, including 229 279 female participants. An 80-variant LDL-C weighted genetic score was generated. Linear and logistic regression models with interactions were used to identify differences between sex-specific LDL-C effects on lipids, carotid-intima media thickness, and multiple cardiovascular outcomes such as CVD, ischemic heart disease, peripheral artery disease, heart failure, aortic valve disease, type 2 diabetes, atrial fibrillation, and aortic aneurysm and dissection. After correction for multiple testing, we observed that the genetically increased LDL-C effect on CVD events was sex specific: per SD genetically increased LDL-C, female participants had a higher LDL-C increase but an attenuated CVD risk increase compared with male participants (LDL-C: female participants 0.71 mmol/L, 95% CI, 0.70-0.72 and male participants 0.57 mmol/L, 95% CI, 0.56-0.59. P for interaction: 5.03×10-60; CVD: female participants: odds ratio [OR], 1.32; 95% CI 1.24-1.40 and male participants: OR, 1.52; 95% CI, 1.46-1.58. P for interaction: 9.88×10-5). We also observed attenuated risks for ischemic heart disease and (nominally for) heart failure in female participants, and genetically increased LDL-C results in higher risk for aortic valve disease in female participants compared with male participants. Genetically increased LDL-C was also associated with an attenuated carotid-intima media thickness increase in female participants. We did not observe other significant attenuations. Sensitivity analyses with an unweighted genetic score and sex-specific weighted genetic scores showed similar results. Conclusions We found that genetically increased LDL-C has a sex-specific differential effect on the risk for cardiovascular disease, ischemic heart disease, heart failure, and aortic valve stenosis. Our observations provide evidence that LDL-C might be a less important determinant of CVD in women compared with men, suggesting that male patients might benefit more from LDL-C targeted therapies for CVD management than female patients and warranting investigations into the sex-specific relative contribution of risk factors for CVD.

Project description:Levels of LDL (low-density lipoprotein) cholesterol in the population are declining, and increasing attention is being focused on residual lipid-related pathways of atherosclerotic cardiovascular disease risk beyond LDL cholesterol. Among individuals with low (<130 mg/dL) LDL cholesterol, we undertook detailed profiling of circulating atherogenic lipoproteins in relation to incident cardiovascular disease in 2 populations.We performed proton nuclear magnetic resonance spectroscopy to quantify concentrations of LDL and VLDL (very low-density lipoprotein) particle subclasses in 11 984 JUPITER trial participants (NCT00239681). Adjusted Cox models examined cardiovascular disease risk associated with lipoprotein measures according to treatment allocation. Risk (adjusted hazard ratio [95%CI] per SD increment) among placebo-allocated participants was associated with total LDL particles (1.19 [1.02, 1.38]) and total VLDL particles (1.21 [1.04, 1.41]), as well as apolipoprotein B, non-high-density lipoprotein cholesterol, and triglycerides, but not LDL-c. Rosuvastatin reduced LDL measures but had variable effects on triglyceride and VLDL measures. On-statin levels of the smallest VLDL particle subclass were associated with a 68% per-SD (adjusted hazard ratio 1.68 [1.28, 2.22]) increase in residual risk-this risk was related to VLDL cholesterol and not triglyceride or larger VLDL particles. There was evidence that residual risk prediction during statin therapy could be significantly improved through the inclusion of key VLDL measures (Harrell C-index 0.780 versus 0.712; P<0.0001). In an independent, prospective cohort of 4721 individuals referred for cardiac catheterization (CATHGEN), similar patterns of lipoprotein-related risk were observed.Atherogenic lipoprotein particle concentrations were associated with cardiovascular disease risk when LDL cholesterol was low. VLDL lipoproteins, particularly the smallest remnant subclass, may represent unused targets for risk prediction and potential therapeutic intervention for reducing residual risk.URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681.

Project description:This study aimed to evaluate the management of high cardiovascular risk (CVr) in the patients with diabetes by exploring the prescribing behavior in a setting of general practitioners (GPs). A retrospective cohort study was carried out using the data recorded between 2018 and 2020 in the clinical database of 10 GPs. Diabetes was defined using the International Classification of Diseases (ICD-9-CM) coding (250*) or using the laboratory parameters (hyperglycemia condition: ≥126 mg/dL). A cohort was described stratifying by demographic, clinical and therapeutic characteristics, and laboratory tests. Both the CVr and statin prescriptions were evaluated; adherence to statin therapy (medication possession ratio, MPR ≥ 80) was calculated in accordance with the low-density lipoprotein cholesterol (LDL-C) target. The multivariate logistic regression models with adjusted odds ratios (ORs) and the corresponding 95% Confidence Intervals (CIs) were calculated to identify the predictors of lipid modifying agents use and achieved target therapy; moreover, glucose-lowering drugs use was evaluated. Out of 13,206 people screened, 1,851 (14.0%) patients were affected by diabetes mellitus (DM), and 1,373 were identified at high/very high CVr. Of them, 1,158 (84.3%) had at least one measurement of LDL-C, and 808 (58.8%) received a prescription with at least one lipid-lowering drug (LLD). The patients at high/very high CVr treated or not treated with LLD, reached the LDL-C target in 24.0 and 10.3%, respectively (p < 0.001). Furthermore, 34.6% of patients treated with high intensity LLDs and adherent to therapy showed the LDL-C values below the therapeutic target. Out of 1,373 patients at high/very high CVr, 958 (69.8%) had at least one prescription of glucose-lowering drugs. Of them, 52.0% (n = 498) were prescribed not in agreement with the current guidelines. More specifically, 392 patients (40.9%) were treated with metformin only, while the remaining 106 (11.1%) were treated with metformin together with hypoglycemic agents other than glucagon-like peptide-1 receptor agonists (GLP1-RA) or sodium-glucose-transporter 2 (SGLT2) inhibitors. Our results suggest the urgent need to improve the management of patients with diabetes at high and very high CVr in the real life, to reduce the burden of diabetes on the health system.

Dataset Information

Comparison of Formulas for Calculating Low-density Lipoprotein Cholesterol in General Population and High-risk Patients with Cardiovascular Disease.

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Comparison of Formulas for Calculating Low-density Lipoprotein Cholesterol in General Population and High-risk Patients with Cardiovascular Disease.

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