Low-density Lipoprotein Cholesterol Measurement Research Articles

Correlation between Serum CD36 Level and Lipid Profile in Patients with Type 2 Diabetes Mellitus, Khartoum State, Sudan

Background: Diabetes mellitus (DM) is a chronic metabolic disorder characterized by hyperglycemia. DM-related dyslipidemia are associated with complications resulting from progressive damage of various organs. CD36 is 88-kD, class B scavenger receptor, expressed on different types of cells. In diabetic patients, LDL particles are glycated with strong level; this increases CD36 expression, initiates foam cell formation and accelerates atherosclerosis. Objective: This study aimed to determine the correlation between serum CD36 level and lipid profile among patients with type 2 diabetes mellitus in Zeenam Specialized center, Khartoum State, Sudan, in a period between 2019 and 2022. Methodology: Hundred participants at different ages were included in this study; 70 were type 2 diabetic patients (cases) and 30 apparently healthy individual (control). 3 ml of venous blood were collected from the participants by using a sterile needle and syringe into a labeled plain container. Each sample was stood until complete clot occurs. Clotted blood sample was then centrifuged to obtain the serum. Then they were used for measurement of total cholesterol, LDL cholesterol, HDL cholesterol, triglyceride and soluble CD36 levels. Total cholesterol, LDL cholesterol, HDL cholesterol and triglycerides were measured using Biosystem chemistry analyzer BTS-302. Serum CD36 was measured using Microplate Reader (URIT-660). Results: The results revealed that serum total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels were significantly higher in patients with type 2 diabetes mellitus compared with control (P = 0.03, P = 0.031, P = 0.000, P = 0.000) respectively, while there is no statistically significant differences in serum CD36 level between cases and control (P = 0.129). Also this study showed that there is no statistically significant correlation between serum CD36 level and total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, age and body mass index. Conclusion: This study concluded that there is no statistically significant difference in serum CD36 level between cases and control. And sCD36 level was not correlated with total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, body mass index, and age.

The healthful plant-based diet index as a tool for obesity prevention-The healthy lifestyle community program cohort 3 study.

World-wide the prevalence of obesity is high, and promoting a shift toward more healthful and more plant-based dietary patterns appears to be one promising strategy to address this issue. A dietary score to assess adherence to a healthy plant-based diet is the healthful plant-based diet index. While there is evidence from cohort studies that an increased healthful plant-based diet index is associated with improved risk markers, evidence from intervention studies is still lacking. A lifestyle intervention was conducted with mostly middle-aged and elderly participants from the general population (n=115). The intervention consisted of a 16-month lifestyle program focusing on a healthy plant-based diet, physical activity, stress management, and community support. After 10weeks, significant improvements were seen in dietary quality, body weight, body mass index, waist circumference, total cholesterol, measured and calculated low-density lipoprotein (LDL) cholesterol, oxidized LDL particles, non-high-density lipoprotein cholesterol, remnant cholesterol, glucose, insulin, blood pressure, and pulse pressure. After 16months, significant decreases were seen in body weight (-1.8kg), body mass index (-0.6kg/m2), and measured LDL cholesterol (-12mg/dl). Increases in the healthful plant-based diet index were associated with risk marker improvements. The recommendation of moving toward a plant-based diet appears acceptable and actionable and may improve body weight. The healthful plant-based diet index can be a useful parameter for intervention studies.

30 EVOLOCUMAB USE IN CLINICAL PRACTICE IN ITALY: FINAL DATA OF THE HEYMANS STUDY.

Abstract Background Controlling lipid levels, in particular low-density lipoprotein cholesterol (LDL-C), is a proven therapeutic approach to reducing cardiovascular (CV) risk. Greater use of combination lipid-lowering therapies (LLTs) may be required to achieve the LDL-C goals recommended by the guidelines. A better understanding of the characteristics of patients receiving PCSK9is in Europe could offer the medical community an opportunity to redefine existing care pathways to better implement European guidelines, thus potentially reducing modifiable residual CV risk further. Purpose Using data from the HEYMANS registry (NCT02770131), the objective of this analysis is to describe the Italian cohort of evolocumab patients and the long-term effectiveness and safety of the treatment. Methods HEYMANS was a prospective registry including adults initiating evolocumab treatment in 12 European countries as part of their routine clinical management, based on local reimbursement criteria, between August 2015 and June 2020. Patient data were collected for ≤6 months before evolocumab initiation (baseline) and ≤30 months post initiation. LDL-C measurements were collected per clinical practice. At each 3-month time point in the study, we analysed median (and 95% CI) reductions in LDL-C, and the proportion of patients achieving ≥50% reductions in LDL-C from baseline. Results Data from 311 patients from Italy were included in this final analysis (67% male, median baseline LDL-C 146 [Q1-Q3 120-177] mg/dL). Most patients (84%) were receiving evolocumab for secondary prevention, with 24% not on oral LLT, of whom the majority reported a history of statin intolerance. Within 3 months of initiating evolocumab treatment, LDL-C levels had reduced by a median of 61% and this reduction was maintained over 30 months (Figure 1). Among patients with an LDL-C value, between 66 and 76% achieved a ≥50% reduction at each visit (Figure 2). Moreover, 65% of patients receiving LLT at baseline reached an LDL-C level <55 mg/dL at any time post baseline, whilst among patients not receiving a background therapy this percentage was 48%. At the 12-month follow up, more than 97% of patients were still receiving evolocumab, with just 8 patients discontinuing the treatment (and 2 more patients leaving the study but keeping on with the treatment). That was confirmed at the 30-month follow up: almost 98% of patients still in the study beyond month 12 were receiving the drug at month 30. Moreover, at each timeframe, more than 99% had no missed dose. There were very few adverse drug reactions reported and no evolocumab-related adverse events were serious. Conclusions In Italian clinical practice, evolocumab treatment was associated with early and sustained reductions in LDL-C, maintained over 30 months. Within 3 months of treatment, patients demonstrated a reduction in LDL-C levels greater than 60% and maintained throughout the study. These data demonstrate that meaningful, consistent additional reductions in LDL-C can be achieved with use of evolocumab. Moreover, the therapy was well tolerated by patients, with a very low discontinuation and very few missed doses.

Comparison of measured LDL cholesterol with calculated LDL-cholesterol using the Friedewald and Martin-Hopkins formulae in diabetic adults at Charlotte Maxeke Johannesburg Academic Hospital/NHLS Laboratory.

The National Cholesterol Education Programme Adult Treatment Panel III (NCEP ATP III) and the European Society of Cardiology recommend using low-density lipoprotein cholesterol (LDL-C) as a treatment target for cholesterol lowering therapy. The Friedewald formula underestimates LDL-C in non-fasted and hypertriglyceridemia patients. This study aimed to compare measured LDL-C to calculated LDL-C in diabetic patients using the Friedewald and Martin-Hopkins formulae. The data of 1 247 adult diabetes patients were retrospectively evaluated, and included triglycerides (TG), LDL-C, total cholesterol, and high-density lipoprotein cholesterol that were measured on the Roche Cobas® c702. Passing-Bablok regression analysis was used to determine the degree of agreement between measured LDL-C and calculated LDL-C using both formulae. The Bland-Altman plots were used to assess the bias at medical decision limits based on the 2021 European Society of Cardiology (ESC) guidelines on cardiovascular disease prevention in clinical practice. Both formulae showed a good linear relationship against measured LDL-C. However, the Martin-Hopkins formula outperformed the Friedewald formula at LDL-C treatment target <1.4mmol/L. The Friedewald formula and the Martin-Hopkins formula had 14.9% and 10.9% mean positive bias, respectively. At TG-C ≥1.7 mmol/L, the Martin-Hopkins formula had a lower mean positive bias of 4.2% (95% CI 3.0-5.5) compared to the Friedewald formula, which had a mean positive bias of 21.8% (95% CI 19.9-23), which was higher than the NCEP ATP III recommended total allowable limit of 12%. The Martin-Hopkins formula performed better than the Friedewald formula at LDL-C of 1.4 mmol/L and showed the least positive bias in patients with hypertriglyceridemia.

Lipoprotein(a) levels in children with suspected familial hypercholesterolaemia: a cross-sectional study.

Familial hypercholesterolaemia (FH) predisposes children to the early initiation of atherosclerosis and is preferably diagnosed by DNA analysis. Yet, in many children with a clinical presentation of FH, no mutation is found. Adult data show that high levels of lipoprotein(a) [Lp(a)] may underlie a clinical presentation of FH, as the cholesterol content of Lp(a) is included in conventional LDL cholesterol measurements. As this is limited to adult data, Lp(a) levels in children with and without (clinical) FH were evaluated. Children were eligible if they visited the paediatric lipid clinic (1989-2020) and if Lp(a) measurement and DNA analysis were performed. In total, 2721 children (mean age: 10.3 years) were included and divided into four groups: 1931 children with definite FH (mutation detected), 290 unaffected siblings/normolipidaemic controls (mutation excluded), 108 children with probable FH (clinical presentation, mutation not detected), and 392 children with probable non-FH (no clinical presentation, mutation not excluded). In children with probable FH, 32% were found to have high Lp(a) [geometric mean (95% confidence interval) of 15.9 (12.3-20.6) mg/dL] compared with 10 and 10% [geometric means (95% confidence interval) of 11.5 (10.9-12.1) mg/dL and 9.8 (8.4-11.3) mg/dL] in children with definite FH (P = 0.017) and unaffected siblings (P = 0.002), respectively. Lp(a) was significantly higher and more frequently elevated in children with probable FH compared with children with definite FH and unaffected siblings, suggesting that high Lp(a) may underlie the clinical presentation of FH when no FH-causing mutation is found. Performing both DNA analysis and measuring Lp(a) in all children suspected of FH is recommended to assess possible LDL cholesterol overestimation related to increased Lp(a).

Abstract 10103: Polygenic Scores and Longitudinal Trajectories of Cardiometabolic Phenotypes

Introduction: Genetic predisposition via polygenic scores (PGS) is strongly associated with single measurements of systolic blood pressure (SBP) and low-density lipoprotein cholesterol (LDL-C), but it is unclear how PGS are associated with their longitudinal trajectories and how these trajectories are associated with risk of coronary heart disease (CHD). Hypothesis: PGS are associated with classes of longitudinal trajectories, and these trajectories are associated with CHD. Methods: Analyses were conducted in 8,453 white participants from the Atherosclerosis Risk in Communities study. SBP and LDL-C measurements were adjusted for medication use. Latent class models were used to group participants into longitudinal trajectory classes based on SBP and LDL-C values from 3-5 visits over up to 27 years. PGS were created by multiplying publicly available weights with participant genotype dosages. The association between PGS and trajectory classes for SBP and LDL-C was examined using logistic regression. We then examined the association of trajectory classes with incident myocardial infarction (MI) and CHD using cox proportional hazard models. Results: Participants were assigned to 4 classes of SBP and 2 classes of LDL-C trajectories ( Figure ). The SBP PGS was significantly associated with SBP classes 2 (OR = 1.28 per standard deviation change in the PGS, P = 4.8E-7) and 4 (OR = 1.7, P &lt; 2E-16) relative to class 3, and with class 4 relative to class 2 (OR= 1.3, P = 2.0E-6). The LDL-C PGS was significantly associated with class 2 (OR = 1.63, P &lt; 2E-16). There were 147 CHD and 102 MI events during 7 additional years of follow up. SBP class 2 and LDL-C class 2 were significantly associated with greater risk of incident MI. Conclusions: Our results highlight longitudinal trajectory classes as a tool for contextualizing the genomics of cardiometabolic phenotypes and the association of these phenotypes with CHD.

Effect of lipoprotein (a) on the analytical determination of low-density lipoprotein cholesterol (LDLc) and its influence on pharmacological treatment with atorvastatin

Lipoprotein(a) (Lp(a)) and Low-density lipoprotein cholesterol (LDLc) is an important risk factor for atherosclerotic cardiovascular disease. The objective of this study was to determine the impact of Lp(a) concentration both on the indirect analytical measurement of LDLc and on the efficacy of dyslipidaemia treatment using the atorvastatin statin. Two retrospective studies were conducted, one with 340 patients and another with 107 patients treated with atorvastatin. Lp(a) concentrations were measured by turbidimetry with an assay independent of the size of the apo(a) isoform. LDLc was calculated using the Friedewald equation and the corrected LDLc was calculated using the Dahlén equation. A strong positive correlation was observed between the serum Lp(a) concentration and the LDLc-overestimation percentage (r = 0.960, p < .001). It was also observed that as the Lp(a) concentration rose there was no significant variation in the percentage decrease in corrected LDLc during atorvastatin treatment (r = 0.186, p > .05). The concentration of LDLc obtained by using the Friedewald equation included Lp(a) cholesterol. The lowering of LDLc in patients treated with atorvastatin depended solely on accessible LDL cholesterol and not on Lp(a) cholesterol.

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 &lt; 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 &lt; 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 &lt; 0.001. At a triglyceride (TG) level of &lt;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 &gt;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.

Indirect calculation of LDL using thirteen equations in Pakistani population

BackgroundOwing to the atherogenic properties, low density lipoprotein cholesterol (LDL-C) is the primary target for treatment and diagnosis of cardiovascular diseases (CVDs), hence accurate measurement of LDL-C is critical. Despite the availability of direct measurement assays for LDL-C, it is routinely calculated by Friedewald equation in clinical settings in Pakistan mostly due to financial constraints. However, the validity of this equation is impacted by several factors, therefore several other equations have been developed for the calculation of LDL-C. Materials and methodsLDL-C of 39,385 individuals measured directly by homogenous assays (dLDL) was compared with LDL-C calculated by thirteen equations (cLDL-C). Stratifications based on different lipids i.e., triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL) were made to check the validity of these equations across all ranges of lipid profile. The correlation and median difference between dLDL and cLDL-C was statistically analyzed. ResultsOverall Teerakanchana equation displayed a strong positive correlation (ρ = 0.967) and least median difference (-8.81) with dLDL, followed by Martin equation (ρ = 0.967). For higher TG ranges (>500 mg/dL), Teerakanchana equation had the least median difference (1.31) and a strong correlation (ρ = 0.800). ConclusionOur data suggest that Teerakanchana equation may be employed as an alternative to Friedewald equation for Pakistani population.

Low-density lipoprotein cholesterol goal attainment in Germany: Results from the DA VINCI study

Background and aimsCardiovascular mortality is high in Germany. For patients with high or very high cardiovascular risk, the European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) guidelines recommend intensive lipid lowering therapy (LLT). This study aimed to assess dyslipidaemia management and achievement of the ESC/EAS guideline-recommended low-density lipoprotein cholesterol (LDL-C) goals. MethodsThis European 18-country, cross-sectional, observational DA VINCI study (EUPAS22075) collected data during a single visit between June 2017 and November 2018 and included LLT in the preceding 12 months and the patients' most recent LDL-C measurement. Achievement of the risk-based 2016 and 2019 ESC/EAS LDL-C goals while receiving stabilized LLT was assessed. Data from the German cohort are presented here. ResultsSeven German sites enrolled a total of 421 primary and secondary prevention patients, 327 were receiving stabilized LLT at the time of LDL-C measurement, i.e. statin monotherapy of high (16%; n = 53), moderate (49%; n = 160) or low (7%; n = 24) intensity, ezetimibe combination (18%; n = 58), proprotein convertase subtilisin/kexin type 9 antibody combination (3%; n = 9), and other LLT (7%; n = 23). The 2016 and 2019 risk-based LDL-C goals were attained by 46% (n = 149) and 28% (n = 92) of patients, respectively. ConclusionsThere is a large gap between ESC/EAS recommendations and LDL-C goal achievement in routine clinical practice in high and very high-risk patients in Germany. Low-to-moderate-intensity statin monotherapy was the most frequently used LLT; use of high-intensity statins and combination therapy was limited. In addition to optimizing statin intensity, combination with non-statin LLT may be needed in most of these patients.

Comparison of Two Nuclear Magnetic Resonance Spectroscopy Methods for the Measurement of Lipoprotein Particle Concentrations.

Background: Measuring lipoprotein particle concentrations may help to improve cardiovascular risk stratification. Both the lipofit (Numares) and lipoprofile (LabCorp) NMR methods are widely used for the quantification of lipoprotein particle concentrations. Objective: The aim of the present work was to perform a method comparison between the lipofit and lipoprofile NMR methods. In addition, there was the objective to compare lipofit and lipoprofile measurements of standard lipids with clinical chemistry-based results. Methods: Total, LDL, and HDL cholesterol and triglycerides were measured with ß-quantification in serum samples from 150 individuals. NMR measurements of standard lipids and lipoprotein particle concentrations were performed by Numares and LabCorp. Results: For both NMR methods, differences of mean concentrations compared to ß-quantification-derived measurements were ≤5.5% for all standard lipids. There was a strong correlation between ß-quantification- and NMR-derived measurements of total and LDL cholesterol and triglycerides (all r > 0.93). For both, the lipofit (r = 0.81) and lipoprofile (r = 0.84) methods, correlation coefficients were lower for HDL cholesterol. There was a reasonable correlation between LDL and HDL lipoprotein particle concentrations measured with both NMR methods (both r > 0.9). However, mean concentrations of major and subclass lipoprotein particle concentrations were not as strong. Conclusions: The present analysis suggests that reliable measurement of standard lipids is possible with these two NMR methods. Harmonization efforts would be needed for better comparability of particle concentration data.

Association of Hyper-Low-Density Lipoprotein and Hypo-High-Density Lipoprotein Cholesterolemia with Low Saliva Flow Rates in Japanese Community-Dwelling Elders.

Introduction The associations of low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein (HDL-C) with reduced saliva flow rates have not been previously reported. Objective The present study aimed to assess the association of cholesterolemia with reduced saliva flow rates in community-dwelling elderly subjects. Methods The present study analyzed 342 participants (170 males and 172 females aged between 78 and 79 years old). Unstimulated salivary flow rate (USFR) was assessed using a cotton roll method. Low-USFR was defined as 0.10 g/30 seconds. Stimulated salivary flow rate (SSFR) was assessed by having the participants chew tasteless gum for 3 minutes. Low-SSFR was defined as 1.0 mL/minute. Blood samples were collected for the measurement of LDL-C, HDL-C, rheumatoid factor, hemoglobin A1c, and creatinine. To assess depression, the General Health Questionnaire 30 was used. A standardized questionnaire was completed, covering the current and previous medications of the participants and smoking status. We stratified the serum LDL-C levels of the participants as normal, moderate or severe hyper-LDL cholesterolemia and serum HDL-C levels as normal or hypo-HDL cholesterolemia. Multivariate logistic regression models were established and low-USFR or low-SSFR were set as dependent variables in the aforementioned models. Results After controlling for the effects of the other variables, the odds ratios (ORs) (95% confidence intervals [CIs]) for low-USFR were 2.25 (1.10-4.61) for moderate and 5.69 (1.55-20.8) for severe hyper-LDL cholesterolemia, while that of hypo-HDL cholesterolemia was 3.40 (1.33-8.69). Severe hyper-LDL cholesterolemia was also associated with low-SSFR with an OR of 3.89 (1.39-10.88). Conclusion Elderly patients with cholesterolemia have a risk of reduced salivary flow rate.

Visual Coronary and Aortic Calcium Scoring on Chest Computed Tomography Predict Mortality in Patients With Low-Density Lipoprotein-Cholesterol ≥190 mg/dL.

Current guidelines recommend coronary artery calcium (CAC) scoring for stratification of atherosclerotic cardiovascular disease risk only in patients with borderline to intermediate risk score by the pooled cohort equation with low-density lipoprotein-cholesterol (LDL-C) of 70 to 190 mg/dL. It remains unknown if CAC or thoracic aorta calcification (TAC), detected on routine chest computed tomography, can provide further risk stratification in patients with LDL-C≥190 mg/dL. From a multisite medical center, we retrospectively identified all patients from March 2005 to June 2021 age ≥40 years, without established atherosclerotic cardiovascular disease and LDL-C≥190 mg/dL who had non-gated non-contrast chest computed tomography within 3 years of LDL-C measurement. Ordinal CAC and TAC scores were measured by visual inspection. Kaplan-Meier curves and multivariable Cox-regression models were built to ascertain the association of CAC and TAC scores with all-cause mortality. We included 811 patients with median age 59 (53-68) years, 262 (32.3%) were male, and LDL-C median level was 203 (194-217) mg/dL. Patients were followed for 6.2 (3.29-9.81) years, and 109 (13.4%) died. Overall, 376 (46.4%) of patients had CAC=0 and 226 (27.9%) had TAC=0. All-cause mortality increased with any CAC and moderate to severe TAC. In a multivariate model, patients with CAC had a significantly higher mortality compared with those without CAC: mild hazard ratio (HR), 1.71 (1.03-2.83), moderate HR, 2.12 (1.14-3.94), and severe HR, 3.49 (1.94-6.27). Patients with moderate TAC (HR, 2.34 [1.19-4.59]) and those with severe TAC (HR, 3.02 [1.36-6.74]) had higher mortality than those without TAC. In patients without history of atherosclerotic cardiovascular disease and LDL-C≥190 mg/dL, the presence and severity of CAC and TAC are independently associated with all-cause mortality.

Lipid-lowering therapy and risk-based LDL-C goal attainment in Belgium: DA VINCI observational study

Background Cardiovascular disease (CVD) is one of the leading causes of death in Belgium. Current strategies for the prevention and management of CVD focus on reducing low-density lipoprotein cholesterol (LDL-C) levels. This analysis assessed whether LDL-C goals, recommended by the European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) guidelines, were being achieved in a Belgian study population. Methods The cross-sectional, observational, DA VINCI study enrolled patients prescribed lipid-lowering therapy (LLT) between 21 June 2017 and 20 November 2018. Data for patients from Belgium were extracted for this country-specific analysis. Primary endpoint was the proportion of patients who achieved 2016 ESC/EAS risk-based LDL-C goals; attainment of 2019 risk-based LDL-C goals was evaluated post hoc. Results Of 497 enrolled patients, 41% were female and mean age was 68 years. Among subjects with an LDL-C measurement on stabilised LLT, moderate-intensity statin monotherapy was the most prescribed LLT regimen (59%). Overall, 63% of patients achieved their risk-based LDL-C goals according to the 2016 ESC/EAS guidelines. Among patients with established ASCVD, risk-based LDL-C goal attainment was higher in patients with peripheral arterial disease (53%) than patients with coronary (37%) and cerebrovascular disease (42%). According to the updated 2019 ESC/EAS guidelines, less than half (41%) of patients achieved their risk-based LDL-C goal. The proportion of primary and secondary prevention patients who achieved 2019 risk-based LDL-C goals was 59% and 18%, respectively. Conclusion These findings reveal a large gap between the LDL-C goals advocated by the ESC/EAS and the levels achieved in routine clinical practice in Belgium.

Pharmacokinetic/pharmacodynamic modeling of roxadustat's effect on LDL cholesterol in patients in Japan with dialysis-dependent chronic kidney disease and anemia

AimsThe objective of this analysis was to develop and evaluate a pharmacokinetic/pharmacodynamic (PK/PD) model of the effect of roxadustat on low-density lipoprotein cholesterol (LDL-C) in Japanese patients with anemia of dialysis-dependent chronic kidney disease while considering the impact of covariates on model parameters. MethodsA total of 2330 LDL-C measurements from 275 patients in 3 clinical studies were analyzed using a nonlinear-mixed effects modeling approach in NONMEM software. ResultsThe PK/PD relationship between roxadustat exposure and LDL-C was well described by a kinetic-pharmacodynamic model with a physiological indirect response model as the PD component. Co-administered statin usage, sevelamer usage, type of dialysis (hemodialysis or peritoneal dialysis), and sex were selected as covariates for LDLbaseline. Weight was selected as a covariate for ID50. Imax and ID50 were estimated as 0.661 and 1.51 mg/h, respectively. ConclusionRoxadustat can decrease LDL-C independent of statins and sevelamer. Further study of the ability of roxadustat to lower LDL-C and any potential effects on outcomes is needed.

Lipid treatment status and goal attainment among patients with atherosclerotic cardiovascular disease in the United States: A 2019 update

ObjectiveTo update the prevalence of atherosclerotic cardiovascular disease (ASCVD) in the United States (US) and re-evaluate lipid-lowering therapies (LLT) utilization and low-density lipoprotein cholesterol (LDL-C) goal attainment among ASCVD patients after proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors have become available using data from 2019. MethodsASCVD patients with at least 1 valid LDL-C measurement from the 2019 Truven MarketScan Research Database were included and stratified into hierarchical cardiovascular risk groups. The number of patients in each group was extrapolated to approximate national figures based on national demographic and ASCVD prevalence numbers. Descriptive statistics on demographic and clinical characteristics, treatment status and LDL-C for each hierarchical category were reported. ResultsThe overall prevalence of ASCVD in the US in 2019 was 24.0 million, approximately 10% of the total US population above 21 years old. We found heavy comorbidity burden among ASCVD patients and 31.2% were at very high risk for recurrent events. The majority of ASCVD patients were not at guideline-recommended LDL-C goal. Although there was a significant increase in the use of LLTs (especially of high-intensity statins) in 2019 compared to 2014, overall LLT utilization remained low, with only 3.8% of ASCVD patients on ezetimibe, less than 1% on PCSK9 inhibitors and over 40% on no LLTs. We also found higher utilization of LLTs among patients who were at goal of < 70 or < 55 mg/dL vs. those not at goal. ConclusionDespite an increase in high-intensity statins use since 2014, there was still an underutilization of LLTs in spite of evidence of their efficacy in LDL-C lowering and ability to reduce the risk of coronary heart disease. Increased awareness of guidelines by healthcare providers and urgency to treat ASCVD is needed in order to improve LLT utilization and help more patients reach the LDL-C goal.

Low-Density Lipoprotein Cholesterol and the Risk of Rheumatoid Arthritis: A Prospective Study in a Chinese Cohort.

Objective: This study aimed to investigate whether low-density lipoprotein cholesterol (LDL-C) concentration was associated with the risk of rheumatoid arthritis (RA) in Chinese adults. Methods: The study included the 97,411 participants in the Kailuan Study without RA, with complete baseline LDL-C data, and who did not use lipid-lowering medications at baseline or during follow-up. We used Cox proportional hazards modeling to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) of RA according to baseline LDL-C tertiles, adjusting for age, sex, body mass index, HDL-C, triglycerides, diabetes, hypertension, alcohol consumption, and smoking. We also calculated the HR and 95% CI of RA using updated LDL-C measurements prior to the end of follow-up, adjusting for covariates. Results: We identified 97 incident RA cases between 2006 and 2018. After adjusting for potential confounders, updated LDL-C concentration—rather than baseline LDL-C—was inversely associated with RA risk. The adjusted HR of RA was 0.64 (95% CI: 0.38, 1.09; p-trend = 0.10) comparing the two extreme baseline LDL-C tertiles, and 0.38 (95% CI: 0.22, 0.64; p-trend < 0.01) comparing the two extreme tertiles of the updated LDL-C concentrations. Conclusions: In this prospective study, high LDL-C concentrations, when measured closest to RA diagnosis or the end of follow-up, were associated with a low risk of RA. These findings highlight the changes in LDL-C prior to RA diagnosis, and the importance of including lipid analyses into studies of the pathogenesis of RA.

Abstract P125: Change In Low-density Lipoprotein Cholesterol And Risk Of Subsequent Cardiovascular Events Among Patients With Myocardial Infarction

Background: Among patients who experience a myocardial infarction (MI), elevated low-density lipoprotein cholesterol (LDL-C) is a major risk factor for experiencing a subsequent cardiovascular (CV) event; however, real-world evidence is lacking in regard to how changes in LDL-C levels after a MI hospitalization are related to subsequent CV events. Methods: Adults with a hospitalized MI and an available baseline LDL-C (closest LDL-C within 2 years prior to hospital discharge) between 2012 and 2018 within a 27-county region across MN and WI were included for study. For each LDL-C measurement during follow-up (starting with the first LDL-C &gt;30 days after baseline and ≤1-year post-discharge), percent change from baseline LDL-C was calculated. Patients were followed for subsequent CV events (composite endpoint 1: MI, ischemic stroke [IS], coronary artery bypass grafting [CABG], percutaneous coronary intervention [PCI]; composite endpoint 2: MI, IS, CABG, PCI, CV death). Cox models were used to evaluate the association between time-dependent LDL-C percent change and CV events, stratified by baseline LDL-C (&lt;70, 70-99, ≥100 mg/dL). Results: Among 3,034 MI patients identified, 740 (24%), 940 (31%) and 1354 (45%) had a baseline LDL-C &lt;70, 70-99 and ≥100 mg/dL, respectively. After a mean follow-up of 3.4 years, 471 and 667 patients experienced the composite endpoint 1 and 2, respectively. After covariate adjustment, a trend towards a lower risk of CV events with decreasing LDL-C from baseline, compared to those with no change or an increase in LDL-C, was observed among those with a LDL-C &lt;70 and &gt; 100 mg/dl but not in those with a LDL-C 70-99 mg/dL (Table). Conclusions: In a population-based cohort of MI patients, there is evidence that patients with a decrease in LDL-C after MI may have a reduced risk of subsequent CV events. These results underscore the importance of lowering LDL-C after a MI and may help to identify subgroups at highest risk for additional CV events and those who may benefit from targeted LDL-C treatment recommendations.

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.

Population-based screening in children for early diagnosis and treatment of familial hypercholesterolemia: design of the VRONI study.

BackgroundHeterozygous familial hypercholesterolemia (FH) represents the most frequent monogenic disorder with an estimated prevalence of 1:250 in the general population. Diagnosis during childhood enables early initiation of preventive measures, reducing the risk of severe consecutive atherosclerotic manifestations. Nevertheless, population-based screening programs for FH are scarce.MethodsIn the VRONI study, children aged 5–14 years in Bavaria are invited to participate in an FH screening program during regular pediatric visits. The screening is based on low-density lipoprotein cholesterol measurements from capillary blood. If exceeding 130 mg/dl (3.34 mmol/l), i.e. the expected 95th percentile in this age group, subsequent molecular genetic analysis for FH is performed. Children with FH pathogenic variants enter a registry and are treated by specialized pediatricians. Furthermore, qualified training centers offer FH-focused training courses to affected families. For first-degree relatives, reverse cascade screening is recommended to identify and treat affected family members.ResultsImplementation of VRONI required intensive prearrangements for addressing ethical, educational, data safety, legal and organizational aspects, which will be outlined in this article. Recruitment started in early 2021, within the first months, more than 380 pediatricians screened over 5200 children. Approximately 50 000 children are expected to be enrolled in the VRONI study until 2024.ConclusionsVRONI aims to test the feasibility of a population-based screening for FH in children in Bavaria, intending to set the stage for a nationwide FH screening infrastructure. Furthermore, we aim to validate genetic variants of unclear significance, detect novel causative mutations and contribute to polygenic risk indices (DRKS00022140; August 2020).