Comparative assessment of LDL-C and VLDL-C estimation in familial combined hyperlipidemia using Sampson's, Martin's and Friedewald's equations

Assessing Performance of Martins's and Sampson's Formulae for Calculation of LDL-C in Indian Population: A Single Center Retrospective Study

Various formulae had been derived to calculate the LDL-C from other lipid profile parameters to supplant the need for direct estimation. Martin's, Sampson's, and Cordova's formulae are recently derived formulae for calculating LDL-C. However, no study has been undertaken till now to verify the newer formulae viz. Martins's and Sampson's in Indian population. The retrospective cross-sectional study was carried out after obtaining approval from the Institutional Ethics Committee on human subject research. The lipid profile data were collected for a period of 17 months from January 2020 to May 2021. The formulae proposed by Friedewald, Cordova, Anandaraja, Martin, and Sampson were used to assess calculated LDL-C. Intraclass correlations were performed to assess the effectiveness of each formula when compared with direct estimation. In our study, we observed that LDL-C calculated using Martin was observed to be closer to that of direct estimation. The bias observed was lowest for Martin's formulae, followed by Sampson's. Intraclass correlation analysis for absolute agreement demonstrated Cordova, Martin, and Sampson to have an average ICC > 0.9, with Martin, and Sampson having a p value < 0.05. Martin fared superior to other formulae in intraclass correlation in patients with LDL > 70. In patients with TG below 200 mg/dL, Martin, and Sampson had a significant correlation with comparable average ICC. However, in patients with TG > 300 mg/dL, Cordova appears to fare better than all other formulae. Our study demonstrated a distinctly superior performance of Martin's formula over Friedewald's formula in the Indian patient population.

Concordance between LDL-C estimated by various formulas and directly measured LDL-C

BACKGROUND

Although direct measurement of LDL cholesterol (LDL-C) in blood is possible, there are several formulas for its estimation. The performance and concordance of these formulas have not been evaluated in Colombia.

OBJECTIVE

To determine the concordance between LDL-C directly measured using the enzymatic technique and existing methods to calculate it.

METHODS

Study of diagnostic tests, and concordance. We analyzed complete lipid profile samples, which included direct measurement of LDL-C, from 2014 to 2022 at Hospital Universitario San Ignacio (Bogotá, Colombia). The direct LDL-C measurements were compared with estimations using the DeLong, Sampson, Friedewald, extended Martin/Hopkins, Anandaraja, and Cordova methods. Lin's concordance correlation coefficient (CCC) and Bland-Altman plots were employed, conducting subgroup analyses based on triglycerides (TG), and LDL-C levels. Kappa coefficients assessed agreement in LDL-C risk categories according to dyslipidemia guidelines.

RESULTS

A total of 2144 samples were evaluated. The formulas with the best CCC were DeLong (0.971) and Sampson (0.969), with no relevant differences. The extended Martin/Hopkins formula (0.964) and the Friedewald formula (0.964) also performed well. The Anandaraja (0.921) and Cordova (0.881) equations exhibited inferior performance. For all formulas, a decrease in concordance was observed when triglycerides were ≥400 mg/dL or when LDL-C was <100 mg/dL. Most formulas demonstrated optimal agreement when assessed using risk categories according to dyslipidemia guidelines, except for Anandaraja and Cordova.

CONCLUSIONS

The DeLong, Sampson, extended Martin/Hopkins, and Friedewald formulas show the best concordance with directly measured LDL-C, so in most cases the results can be considered interchangeable. However, the Anandaraja and Cordova formulas are not recommended.

Insulin resistance potentiates the effect of remnant cholesterol on cardiovascular mortality in individuals without diabetes

BACKGROUND AND AIMS

Remnant cholesterol (RC) and insulin resistance (IR) have been independently associated with cardiovascular risk. Here, we evaluated the role of IR and RC on cardiovascular disease (CVD) mortality.

METHODS

We conducted an analysis of 16,113 individuals ≥20 years without diabetes from the National Health and Nutrition Examination Survey (NHANES-III/IV). RC levels were calculated using total cholesterol, non-HDL-c, and LDL-c; IR was defined as HOMA2-IR≥2.5 and CVD mortality as a composite of cardiovascular and cerebrovascular mortality. Multiple linear regression was used to assess the relationship between HOMA2-IR and RC and Cox regression models to assess their joint role in CVD mortality. Causally ordered mediation models were used to explore the mediating role of IR in RC-associated CVD mortality.

RESULTS

We identified an association between higher HOMA2-IR and higher RC levels. The effect of IR on CVD mortality was predominant (HR 1.32, 95%CI 1.18-1.48) and decreased at older ages (HR 0.934, 95%CI 0.918-0.959) compared to RC (HR 0.983, 95%CI 0.952-1.014). Higher risk of CVD mortality was observed in individuals with IR but normal RC (HR 1.37, 95%CI 1.25-1.50) and subjects with IR and high RC (HR 1.24, 95%CI 1.13-1.37), but not in subjects without IR but high RC. In mediation models, HOMA2-IR accounted for 78.2% (95%CI 28.11-98.89) of the effect of RC levels on CVD mortality.

CONCLUSIONS

Our findings suggest that RC potentiates the risk of CVD mortality through its effect on whole-body insulin sensitivity, particularly among younger individuals.

Explainable artificial intelligence for LDL cholesterol prediction and classification

INTRODUCTION

Monitoring LDL-C levels is essential in clinical practice because there is a direct relation between low-density lipoprotein cholesterol (LDL-C) levels and atherosclerotic heart disease risk. Therefore, measurement or estimate of LDL-C is critical. The present study aims to evaluate Artificial Intelligence (AI) and Explainable AI (XAI) methodologies in predicting LDL-C levels while emphasizing the interpretability of these predictions.

MATERIALS AND METHODS

We retrospectively reviewed data from the Laboratory Information System (LIS) of Ankara Etlik City Hospital (AECH). We included 60.217 patients with standard lipid profiles (total cholesterol [TC], high-density lipoprotein cholesterol, and triglycerides) paired with same-day direct LDL-C results. AI methodologies, such as Gradient Boosting (GB), Random Forests (RF), Support Vector Machines (SVM), and Decision Trees (DT), were used to predict LDL-C and compared directly measured and calculated LDL-C with formulas. XAI techniques such as Shapley additive annotation (SHAP) and locally interpretable model-agnostic explanation (LIME) were used to interpret AI models and improve their explainability.

RESULTS

Predicted LDL-C values using AI, especially RF or GB, showed a stronger correlation with direct measurement LDL-C values than calculated LDL-C values with formulas. TC was shown to be the most influential factor in LDL-C prediction using SHAP and LIME. The agreement between the treatment groups based on NCEP ATPIII guidelines according to measured LDL-C and the LDL-C groups obtained with AI was higher than that obtained with formulas.

CONCLUSIONS

It can be concluded that AI is not only a reliable method but also an explainable method for LDL-C estimation and classification.

Comparison between the Friedewald, Martin and Sampson Equations and LDL-C Quantification by Ultracentrifugation in a Mexican Population

Low-density lipoprotein cholesterol (LDL-C), which makes up about 70% of the cholesterol in the blood, is critical in the formation of arteriosclerotic plaques, increasing the risk of heart disease. LDL-C levels are estimated using Friedewald, Martin and Sampson equations, though they have limitations with high triglycerides. Our aim is to compare the effectiveness of these equations versus the ultracentrifugation technique in individuals with and without dyslipidemia and identify precision. There were 113 participants, 59 healthy controls and 54 dyslipidemic patients. Samples were collected after fasting. LDL-C was estimated using the Friedewald, Martin and Sampson equations. The purified LDL-C, ultracentrifugated and dialysized control group without dyslipidemia vs. patients with coronary artery disease (CAD) showed differences in age, HDL-C, triglycerides and glucose non-HDL-C (p = 0.001 in all). There were correlations in CGWD between ultracentrifugation and Sampson R-squared (R2) = 0.791. In the dyslipidemia control group, ultracentrifugation and Friedewald R2 = 0.911. In patients with CAD, correlation between ultracentrifugation and Sampson R2 = 0.892; Bland-Altman confirmed agreement in controls without dyslipidemia. The Martin and Sampson equations are interchangeable with ultracentrifugation. Conclusion: The role of LDL analysis using precise techniques is necessary to obtain better control of disease outcomes after the use of precise therapies and suggests verifying its importance through clinical trials.

Performance of the enhanced Sampson-NIH equation for VLDL-C and LDL-C in a population with familial combined hyperlipidemia

INTRODUCTION

Low-density cholesterol (LDL-C) has long been estimated by the Friedewald formula (F-LDL-C); however, this method underestimates LDL-C in patients with hypertriglyceridemia (HTG) or low LDL-C levels. The Martin (M-LDL-C) and Sampson (S-LDL-C) formulas partially resolve these limitations. Recently, Sampson et al. developed a new equation (eS-VLDL-C) that includes ApoB. This new equation could be particularly useful in FCHL, which is characterized by the predominance of triglyceride-rich VLDL and a discordance between LDL-C and ApoB.

METHODS

Very low-density lipoproteins (VLDL-C) was measured in 336 patients with FCHL by sequential ultracentrifugation. LDL-C was estimated by subtracting VLDL-C, estimated by the different equations, from non-HDL cholesterol. Spearman correlations, R2, mean squared error (RMSE), and bias were used to compare the accuracy of the different equations. Concordance of the estimated LDL-C values with LDL-C thresholds and ApoB was also assessed by their kappa coefficients and ROC analysis.

RESULTS

Overall population had a mean age of 47 years, and 61.5% were women. 19.5% had type 2 diabetes, hypertension was present in 20.8%, and only 12.2% were on statin treatment. Both S-LDL-C and eS-LDL-C performed similarly, and better than M-LDL-C and F-LDL-C. In Bland-Altman analysis, eS-LDL-C showed the lowest bias, better performance in HTG, and better concordance with LDL-C treatment goals compared to other formulas (e.g. ρ: 0.87, 95% CI 0.84-0.89).

CONCLUSIONS

LDL-S and LDL-eS equations estimate the concentration of LDL-C with greater accuracy than other formulas. The LDL-eS has best performance in estimating LDL-C with lower RMSE than other formulas.

Remnant cholesterol, but not low-density lipoprotein cholesterol, is associated with intra-pancreatic fat deposition

AIM

To investigate the associations of components of the lipid panel (and its derivatives) with intra-pancreatic fat deposition (IPFD).

METHODS

All participants underwent abdominal magnetic resonance imaging on the same 3.0-Tesla scanner and IPFD was quantified. Blood samples were collected in the fasted state for analysis of lipid panel components. A series of linear regression analyses was conducted, adjusting for age, sex, ethnicity, body mass index, fasting plasma glucose, homeostatic model assessment of insulin resistance, and liver fat deposition.

RESULTS

A total of 348 participants were included. Remnant cholesterol (P = 0.010) and triglyceride levels (P = 0.008) were positively, and high-density lipoprotein cholesterol level (P = 0.001) was negatively, associated with total IPFD in the most adjusted model. Low-density lipoprotein cholesterol and total cholesterol were not significantly associated with total IPFD. Of the lipid panel components investigated, remnant cholesterol explained the greatest proportion (9.9%) of the variance in total IPFD.

CONCLUSION

Components of the lipid panel have different associations with IPFD. This may open up new opportunities for improving outcomes in people at high risk for cardiovascular diseases (who have normal low-density lipoprotein cholesterol) by reducing IPFD.

Comprehensive analysis of dyslipidemia states associated with fat in the pancreas

BACKGROUND

The global burden of cardiovascular diseases continues to rise, and it is increasingly acknowledged that guidelines based on traditional risk factors fail to identify a substantial fraction of people who develop cardiovascular diseases. Fat in the pancreas could be one of the unappreciated risk factors. This study aimed to investigate the associations of dyslipidemia states with fat in the pancreas.

METHODS

All participants underwent magnetic resonance imaging on the same 3.0 T scanner for quantification of fat in the pancreas, analyzed as both binary (i.e., fatty change of the pancreas) and continuous (i.e., intra-pancreatic fat deposition) variables. Statistical analyses were adjusted for body mass index, glycated hemoglobin, fasting insulin, ethnicity, age, and sex.

RESULTS

There were 346 participants studied. On most adjusted analyses, high-density lipoprotein cholesterol dyslipidemia was significantly associated with both fatty change of the pancreas (p = 0.010) and intra-pancreatic fat deposition (p = 0.008). Neither low-density lipoprotein cholesterol dyslipidemia nor triglyceride dyslipidemia were significantly associated with fatty change of the pancreas and intra-pancreatic fat deposition. The absence of any dyslipidemia was inversely associated with both fatty change of the pancreas (p = 0.016) and intra-pancreatic fat deposition (p < 0.001).

CONCLUSIONS

Dyslipidemias are uncoupled when it comes to the relationship with fat in the pancreas, with only high-density lipoprotein cholesterol dyslipidemia having a consistent and strong link with it. The residual cardiovascular diseases risk may be attributed to fatty change of the pancreas.

Serum lipid profile levels and semen quality: new insights and clinical perspectives for male infertility and men's health

PURPOSE

Several clinical scenarios regulate the final ejaculated semen, which is pivotal to reproductive success. Sperm motility and plasma membrane fusogenic activity primarily rely on the peculiar sperm lipid composition, influenced by the patient's metabolism, genetics, nutritional, environmental status, and concomitant clinical entities such as varicocele. This study aimed to determine the relationship between serum lipid profile and testicular function (semen quality and testosterone levels).

METHODS

This retrospective study uses medical charts of 278 infertile men who attended andrological care between 2000 and 2019. Seminal analysis data, lipid profile, and total serum testosterone were collected. A multiple linear regression analysis was performed to evaluate the influence of the lipid parameters on the seminal variables. Statistical analyses were carried out with p ≤ 0.05 considered statistically significant.

RESULTS

Seminal creatine kinase activity (p = 0.024) is negatively related to HDL (p = 0.032) and triglycerides (p = 0.037), while total testosterone (p < 0.0001) and seminal volume (p = 0.046) appeared both to be negatively related to triglycerides (p = 0.030 and p = 0.033, respectively).

CONCLUSION

Medical advice commonly advocated to prevent endothelial dysfunction and cardiovascular disease and improve HDL-cholesterol and triglyceride levels in dyslipidemic patients should also be given to infertile men. Physicians should give patients a thorough assessment, including the blood lipid profile, hormonal status, and routine seminal examinations. We propose a more comprehensive men´s health check-up for the infertile male population, not limited to a simple evaluation of basic sperm parameters.

Evaluation of low-density lipoprotein cholesterol equations by cross-platform assessment of accuracy-based EQA data against SI-traceable reference value

OBJECTIVES

Low-density lipoprotein cholesterol (LDLC) is the primary cholesterol target for the diagnosis and treatment of cardiovascular disease (CVD). Although beta-quantitation (BQ) is the gold standard to determine LDLC levels accurately, many clinical laboratories apply the Friedewald equation to calculate LDLC. As LDLC is an important risk factor for CVD, we evaluated the accuracy of Friedewald and alternative equations (Martin/Hopkins and Sampson) for LDLC.

METHODS

We calculated LDLC based on three equations (Friedewald, Martin/Hopkins and Sampson) using the total cholesterol (TC), triglycerides (TG), and high-density lipoprotein cholesterol (HDLC) in commutable serum samples measured by clinical laboratories participating in the Health Sciences Authority (HSA) external quality assessment (EQA) programme over a 5 years period (number of datasets, n=345). LDLC calculated from the equations were comparatively evaluated against the reference values, determined from BQ-isotope dilution mass spectrometry (IDMS) with traceability to the International System of Units (SI).

RESULTS

Among the three equations, Martin/Hopkins equation derived LDLC had the best linearity against direct measured (y=1.141x - 14.403; R2=0.8626) and traceable LDLC (y=1.1692x - 22.137; R2=0.9638). Martin/Hopkins equation (R2=0.9638) had the strongest R2 in association with traceable LDLC compared with the Friedewald (R2=0.9262) and Sampson (R2=0.9447) equation. The discordance with traceable LDLC was the lowest in Martin/Hopkins (median=-0.725%, IQR=6.914%) as compared to Friedewald (median=-4.094%, IQR=10.305%) and Sampson equation (median=-1.389%, IQR=9.972%). Martin/Hopkins was found to result in the lowest number of misclassifications, whereas Friedewald had the most numbers of misclassification. Samples with high TG, low HDLC and high LDLC had no misclassification by Martin/Hopkins equation, but Friedewald equation resulted in ∼50% misclassification in these samples.

CONCLUSIONS

The Martin/Hopkins equation was found to achieve better agreement with the LDLC reference values as compared to Friedewald and Sampson equations, especially in samples with high TG and low HDLC. Martin/Hopkins derived LDLC also enabled a more accurate classification of LDLC levels.

Azilsartan Ameliorates Skeletal Muscle Wasting in High Fat Diet (HFD)-induced Sarcopenic Obesity in Rats via Activating Akt Signalling Pathway

An association between the loss of skeletal muscle mass and obesity in the geriatric population has been identified as a disease known as sarcopenic obesity. Therefore, therapeutic/preventive interventions are needed to ameliorate sarcopenia. The present study investigates the effect of azilsartan (AZL) on skeletal muscle loss in High-Fat Diet (HFD)-induced sarcopenic obese (SO) rats. Four- and fourteen-months male Sprague Dawley rats were used and randomized in control and azilsartan treatment. 14 months animals were fed with HFD for four months and labeled as HFD-fed SO rats. Young & old rats received 0.5% carboxymethyl cellulose as a vehicle/AZL (8 mg/kg, per oral) treatment for six weeks. Grip strength and body composition analysis were performed after the last dose of AZL. Serum and gastrocnemius (GN)muscles were collected after animal sacrifice. AZL treatment significantly increased lean muscle mass, grip strength, myofibrillar protein, and antioxidant (superoxide dismutase & nitric oxide) levels in SO rats. AZL also restored the muscle biomarkers (creatine kinase, myostatin & testosterone), and insulin levels. AZL improves cellular, and ultracellular muscle structure and prevents type I to type II myofiber transitions in SO rats. Further, immunohistochemistry results showed increased expressions of pAkt and reduced expression of MuRF-1 and TNF-α exhibiting that AZL intervention could decrease protein degradation in SO rats. In conclusion, present results showed that AZL significantly increased lean mass, and restored muscle biomarkers, and muscle architecture. Taken together, the aforementioned findings suggest that azilsartan could be a possible therapeutic approach to reduce muscle wasting in sarcopenic obesity.

Comparative performance of equations to estimate low-density lipoprotein cholesterol levels and cardiovascular disease incidence: The ATTICA study (2002-2022)

Accurate estimation of low-density lipoprotein cholesterol (LDL-C) is important for monitoring cardiovascular disease (CVD) risk and guiding lipid-lowering therapy. This study aimed to evaluate the magnitude of discordance of LDL-C levels calculated by different equations and its effect on CVD incidence. The study sample consisted of 2354 CVD-free individuals (49% males, mean age 45 ± 14 years); 1600 were re-evaluated at 10 years and 1570 at 20 years. LDL-C was estimated using the Friedewald, Martin/Hopkins, and Sampson equations. Participants were categorized as discordant if estimated LDL-C was below the CVD-risk specific cut-off for one equation and equal/above for its comparator. The Friedewald and Martin/Hopkins equations presented a similar performance in estimating LDL-C; however, both yielded lower values compared to the Sampson. In all pairwise comparisons, differences were more pronounced at lower LDL-C levels, while the Friedewald equation significantly underestimated LDL-C in hypertriglyceridemic participants. Discordance was evident in 11% of the study population, and more specifically 6%, 22%, and 20% for Friedewald versus Martin/Hopkins, Friedewald versus Sampson and Martin/Hopkins versus Sampson equations, respectively. Among discordant participants, median (1st, 3rd quartile) difference in LDL-C was -4.35 (-10.1, 1.95), -10.6 (-12.3, -9.53) and -11.3 (-11.9, -10.6) mg/dL for Friedewald versus Martin/Hopkins, Friedewald versus Sampson and Martin/Hopkins versus Sampson equations, respectively. The 10- and 20-year CVD survival model that included LDL-C values of the Martin-Hopkins equation outperformed the predictive ability of those based on the Friedewald or Sampson equations. Significant differences in estimated LDL-C exist among equations, which may result in LDL-C underestimation and undertreatment.

Prevalence of familial hypercholesterolemia and its association with coronary artery disease: A Chinese cohort study

Background

Familial hypercholesterolemia (FH) is underrecognized, and its association with coronary artery disease (CAD) remains limited, especially in China. We aimed to investigate the prevalence of FH and its relationship with CAD in a large Chinese cohort.

Methods

FH was defined using the Make Early Diagnosis to Prevent Early Death (MEDPED) criteria. The crude and age-sex standardized prevalence of FH were calculated based on surveys of the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project during 2007-2008. The associations of FH with incident CAD and its major subtypes were estimated with the cohort-stratified multivariate Cox proportional hazard models based on the data from the baseline to the last follow-up (2018-2020).

Results

Among 98,885 included participants, 190 participants were defined as FH. Crude and age-sex standardized prevalence and 95% confidence interval (CI) of FH were 0.19% (0.17%-0.22%) and 0.13% (0.10%-0.16%), respectively. The prevalence varied across age groups and peaked in the group of 60-<70 years (0.28%), and the peak prevalence (0.18%) in males was earlier, yet lower than the peak crude prevalence in females (0.41%). During a mean follow-up of 10.7 years, 2493 cases of incident CAD were identified. After multivariate adjustment, FH patients had a 2.03-fold greater risk of developing CAD compared to non-FH participants.

Conclusions

The prevalence of FH was estimated to be 0.19% in the participants, and it was associated with an elevated risk of incident CAD. Our study suggests that early screening of FH has certain public health significance for the prevention of CAD.

Comparison of Three Methods for LDLC Calculation for Cardiovascular Disease Risk Categorisation in Three Distinct Patient Populations

BACKGROUND

Limitations of the Friedewald equation for low-density-lipoprotein cholesterol (F-LDLC) calculation led to the Martin-Hopkins (M-LDLC) and Sampson-National Institutes of Health (S-LDLC) equations. We studied these newer calculations of LDLC for correlation and discordance for stratification into the Canadian Cardiovascular Society (CCS) 2021 Dyslipidemia Guidelines' cardiovascular disease (CVD) risk categories.

METHODS

We performed analyses on lipid profiles from 3 populations: records of a hospital biochemistry laboratory (population 1), lipid clinic patients without select monogenic dyslipidemias (population 2A), and lipid clinic patients with familial hypercholesterolemia (FH; population 2B).

RESULTS

There was very strong correlation among the 3 calculated LDLC. In populations 1 and 2A, M-LDLC and S-LDLC were progressively higher than F-LDLC as triglyceride (TG) levels increased from normal to ∼ 5 mmol/L. In population 2B, M-LDLC was higher than F-LDLC, but S-LDLC was progressively lower than F-LDLC. Using the CCS 2021 guidelines' 4 CVD risk categories, 7.0% (population 2A) to 7.2% (population 1) of cases for M-LDLC vs F-LDLC and 3.9% (population 2A) to 4.4% (population 1) of cases for S-LDLC vs F-LDLC were reclassified to an adjacent CVD risk category, mostly from a lower to a higher risk category.

CONCLUSIONS

Switching from F-LDLC to S-LDLC or M-LDLC can reclassify up to ∼ 4.4% or 7.2% of patients, respectively, to another CCS CVD risk category. The difference between F-LDLC and M-LDLC or S-LDLC is greater with higher TG, and with lower LDLC. We recommend that clinical laboratories switch to reporting results from either M-LDLC or S-LDLC, but S-LDLC should not be used in FH patients, pending further studies.

Low-density lipoprotein cholesterol goal attainment in patients with clinical evidence of familial hypercholesterolemia and elevated Lp(a)

BACKGROUND

Although potent lipid-lowering therapies are available, patients commonly fall short of recommended low-density lipoprotein cholesterol (LDL-C) levels. The aim of this study was to examine the relationship between familial hypercholesterolemia (FH) and elevated lipoprotein(a) [Lp(a)] and LDL-C goal attainment, as well as the prevalence and severity of coronary artery disease (CAD). Moreover, we characterized patients failing to meet recommended LDL-C goals.

METHODS

We performed a cross-sectional analysis in a cohort of patients undergoing cardiac catheterization. Clinical FH was determined by the Dutch Clinical Lipid Network Score, and Lp(a) ≥ 50 mg/dL (≈ 107 nmol/L) was considered elevated.

RESULTS

A total of 838 participants were included. Overall, the prevalence of CAD was 72%, and 62% received lipid-lowering treatment. The prevalence of clinical FH (probable and definite FH) was 4%, and 19% had elevated Lp(a) levels. With 35%, LDL-C goal attainment was generally poor. Among the participants with clinical FH, none reached their LDL-C target. Among patients with elevated Lp(a), LDL-C target achievement was only 28%. The prevalence and severity of CAD were higher in participants with clinical FH (86% prevalence) and elevated Lp(a) (80% prevalence).

CONCLUSION

Most participants failed to meet their individual LDL-C goals according to the ESC 2016 and 2019 guidelines. In particular, high-risk patients with clinical FH or elevated Lp(a) rarely met their target for LDL-C. The identification of these patients and more intense treatment approaches are crucial for the improvement of CAD primary and secondary prevention.

The Impact of Low-Density Lipoprotein Equation Changes on Cholesterol Treatment in Canada

Background

In cardiovascular disease prevention, low-density lipoprotein cholesterol (LDL-C) values guide treatment for lowering cholesterol level. After 50 years of clinical laboratories using the Friedewald LDL-C equation, the Canadian Society of Clinical Chemists recently recommended adoption of the new and more accurate Sampson / U.S. National Institutes of Health (NIH) LDL-C equation. Here, we estimate the anticipated population-level impact of this equation change.

Methods

We compared lipid profiles from the Canadian Health Measures Survey (CHMS) year 2019 to those from the National Health and Nutrition Examination Survey (NHANES) years 2017 to 2020. Then, based on 10,828 participants in the latter, we calculated the impact of changing the LDL-C equation from the Friedewald to the Sampson.

Results

Sampson- and Friedewald-equation LDL-C values are strongly correlated (r = 0.99, P < 0.001), but differences between them increase with both higher triglyceride and lower LDL-C values. We evaluated the impact of these discordances using LDL-C treatment thresholds from the 2021 Canadian Cardiovascular Society lipid guidelines. Among patients who take cholesterol-lowering medications, the Sampson equation reclassifies 3.3% more patients (95% confidence interval 2.2% to 4.9%), or about 123,000 individuals, as meeting the criteria for treatment intensification.

Conclusion

Although changing the LDL-C equation used from the Friedewald to the Sampson affects only a small proportion of the population, an estimated 123,000 Canadians who are taking cholesterol-lowering medications may need to intensify treatment to lower their cholesterol level, due to small absolute changes around guideline threshold values of LDL-C.

A machine learning-based approach for low-density lipoprotein cholesterol calculation using age, and lipid parameters

BACKGROUND

Low-density lipoprotein cholesterol (LDL-C) is a critical biomarker for cardiovascular disease. However, no consensus exists on the best method for estimating LDL-C in Chinese laboratories. This study aimed to develop a machine learning (ML) method for LDL-C estimation.

METHODS

An extensive data set of 111,448 samples were randomized into five equal subsets. ML-based equations were developed using age, sex, and lipid parameters based on five-fold cross-validation. The trained ML equations were externally validated in three different data sets. The performance of the ML equations was compared with the Friedewald, Martin/Hopkins, and Sampson equations.

RESULTS

The selected ML equations showed less bias with direct LDL-C than other LDL-C equations in the Chinese population, including those with triglycerides (TG) ≥ 400 mg / dL and LDL-C < 40 mg / dL. The performance of the ML equations was less susceptible to age. External validation showed the generalization of the ML equations.

CONCLUSIONS

This study highlights the potential of integrating sex, age, and lipid parameters into the ML equations to obtain a more robust and reliable LDL-C calculation.

Estimated number and percentage of US adults with atherosclerotic cardiovascular disease recommended add-on lipid-lowering therapy by the 2018 AHA/ACC multi-society cholesterol guideline

Study objective

The 2018 American Heart Association/American College of Cardiology (AHA/ACC) cholesterol guideline recommends a maximally-tolerated statin with add-on lipid-lowering therapy, ezetimibe and/or proprotein convertase subtilisin/kexin type 9 (PCSK9) for adults with very-high atherosclerotic cardiovascular disease (ASCVD) risk to achieve a low-density lipoprotein cholesterol (LDL-C) <70 mg/dL. We estimated the percentage of US adults with ASCVD recommended, by the 2018 AHA/ACC cholesterol guideline, and receiving add-on lipid-lowering therapy.

Design setting and participants

Cross-sectional study including 805 participants from the US National Health and Nutrition Examination Survey (NHANES) 2013-2020 data. NHANES sampling weights were used to obtain estimates for the US adult population.

Main measures

Very-high ASCVD risk was defined as either: ≥2 ASCVD events, or one ASCVD event with ≥2 high-risk conditions. Being recommended add-on lipid-lowering therapy was defined as having very-high ASCVD risk and LDL-C ≥ 70 mg/dL, or LDL-C < 70 mg/dL while taking ezetimibe or a PCSK9 inhibitor.

Results

An estimated 18.7 (95%CI, 16.0-21.4) million US adults had ASCVD, of whom 81.6 % (95%CI, 76.7 %-86.4 %) had very-high ASCVD risk, and 60.1 % (95%CI, 54.5 %-65.7 %) had very-high ASCVD risk and LDL-C ≥ 70 mg/dL. Overall, 61.4 % (95%CI, 55.8 %-66.9 %) were recommended add-on lipid-lowering therapy and 3.2 % (95 % CI, 1.2 %-5.3 %) were taking it. Smokers, adults with diabetes, hypertension and chronic kidney disease were more likely, while those taking atorvastatin or rosuvastatin were less likely, to be recommended add-on lipid-lowering therapy.

Conclusion

The majority of US adults with ASCVD are recommended add-on lipid-lowering therapy by the 2018 AHA/ACC cholesterol guideline but few are receiving it.

How should low-density lipoprotein cholesterol be calculated in 2022?

PURPOSE OF REVIEW

The reference method for low-density lipoprotein-cholesterol (LDL-C) quantitation is β-quantification, a technically demanding method that is not convenient for routine use. Indirect calculation methods to estimate LDL-C, including the Friedewald equation, have been used since 1972. This calculation has several recognized limitations, especially inaccurate results for triglycerides (TG) >4.5 mmol/l (>400 mg/dl). In view of this, several other equations were developed across the world in different datasets.The purpose of this review was to analyze the best method to calculate LDL-C in clinical practice by reviewing studies that compared equations with measured LDL-C.

RECENT FINDINGS

We identified 45 studies that compared these formulae. The Martin/Hopkins equation uses an adjustable factor for TG:very low-density lipoprotein-cholesterol ratios, validated in a large dataset and demonstrated to provide more accurate LDL-C calculation, especially when LDL <1.81 mmol/l (<70 mg/dl) and with elevated TG. However, it is not in widespread international use because of the need for further validation and the use of the adjustable factor. The Sampson equation was developed for patients with TG up to 9 mmol/l (800 mg/dl) and was based on β-quantification and performs well on high TG, postprandial and low LDL-C samples similar to direct LDL-C.

SUMMARY

The choice of equation should take into the level of triglycerides. Further validation of different equations is required in different populations.

Validation of Friedewald, Martin-Hopkins and Sampson low-density lipoprotein cholesterol equations

Background

Low-density lipoprotein cholesterol (LDL-C) is an important biomarker for determining cardiovascular risk and regulating lipid lowering therapy. Therefore, the accurate estimation of LDL-C concentration is essential in cardiovascular disease diagnosis and prognosis. Sampson recently proposed a new formula for the estimation of LDL-C. However, little is known regarding the validation of this formula.

Objectives

This study aimed to validate this new formula with other well-known formulas in Turkish population, composed of adults.

Methods

A total of 88,943 participants above 18 years old at Sivas Cumhuriyet University Hospital (Sivas, Turkey) were included to this study. LDL-C was directly measured by homogeneous assays, i.e., Roche, Beckman and Siemens and estimated by Friedewald’s, Martin-Hopkins’, extended Martin-Hopkins’ and Sampson’s formulas. The concordances between the estimations obtained by the formulas and the direct measurements were evaluated both in general and separately for the LDL-C, TG and non-HDL-C sublevels. Linear regression analysis was applied and residual error plots were generated between each estimation and direct measurement method. Coefficient of determination (R²) and mean absolute deviations were also calculated.

Results

The results showed that the extended Martin-Hopkins approach provided the most concordant results with the direct assays for LDL-C estimation. The results also showed that the highest concordances were obtained between the direct assays with the extended Martin-Hopkins formula calculated with the median statistics obtained from our own population. On the other hand, it was observed that the results of the methods may differ in different assays. The extended Martin-Hopkins approach, calculated from the median statistics of our population, gave the most concordant results in patients with “low LDL-C level (LDL-C levels < 70 mg/dL) or hypertriglyceridemia (TG levels ≥ 400 mg/dL)”.

Conclusions

Although the results of the formulas in different assays may vary, the extended Martin-Hopkins approach was the best one with the highest overall concordances. The validity of the Martin Hopkins’ and Sampson’s formulas has to be further investigated in different populations.

A comparative evaluation of cardiac and neurological safety status of two commonly used oral hypoglycaemic agents in T2-DM Swiss albino mice model

Background

Diabetes mellitus (DM), along with its associated complications, including diabetic neuropathy and hyperlipidemia, has become a global concern in the last few decades. The main objective of our study is to evaluate the comparative neuro-safety status, serum plasma glucose, and lipid-lowering potential of two widely recognized antidiabetic drugs named metformin and glimepiride.

Methods

The neurological evaluation was done by open field test, hole board test, forced swimming test, dark and lighthouse test, and elevated plus maze test by employing diazepam as standard. Serum blood glucose level of streptozotocin (STZ)-induced diabetic mice was determined by glucose oxidizing method using a glucometer. Total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and very-low-density lipoprotein cholesterol (VLDL-C) levels were estimated by using the reference method where atorvastatin was used as standard.

Results

In neurological evaluation, both drugs produce almost the same anxiolytic activity in the open field test, hole board test, light and dark house test, and elevated plus maze test. However, in the forced swimming test, glimepiride produced more antidepressant activity than metformin. Glimepiride was found to remarkably reduce serum glucose and VLDL-C levels more than metformin, whereas, for other parameters, metformin takes over glimepiride sometimes took over the standard atorvastatin.

Conclusions

The results of our study indicate that both oral hypoglycaemic drugs alter the lipid index while producing some anxiolytic effects on the central nervous system. Thus, recommended to be carefully administered to patients with low BMI and might be beneficial to patients suffering from peripheral nerve function and anxiety.

Evaluation of Sampson equation for LDL-C in acute coronary syndrome patients: a Chinese population-based cohort study

OBJECTIVE

Low-density lipoprotein cholesterol (LDL-C) is an important cardiovascular disease marker that is used to estimate the risk of acute coronary syndrome in patients. The Sampson equation is an accurate LDL-C equation, but its application in Chinese patients is unclear.

METHODS

This study enrolled 12,989 consecutive Chinese patients with the acute coronary syndrome (ACS), LDL-C levels were determined by direct standard method and two indirect equations (Friedewald and Sampson). The detection accuracy and consistency of these two equations were compared in patients classified by triglyceride (TG). In addition, the efficiency of the Sampson equation was also evaluated in patients with different comorbidities.

RESULTS

Patients were divided into six groups according to TG level, and indicated that the Sampson formula was more accurate than the Friedewald formula in all TG spectrums (P < 0.001). The Friedewald formula may underestimate the risk in patients with TG > 400 mg/dL, especially in TG > 800 mg/dL group (r: 0.931 vs. 0.948, 0.666 vs. 0.898, respectively). Compared with the Friedewald equation, the Sampson equation showed more advantages in female, age ≥ 65, body index mass (BMI) < 25, non-smoker, and non-diabetes (0.954 vs. 0.937, 0.956 vs. 0.934, 0.951 vs. 0.939, 0.951 vs. 0.936, and 0.947 vs. 0.938, respectively) than those in male, age < 65, BMI ≥ 25, smoker, and diabetes.

CONCLUSIONS

Compared with the Friedewald equation, the Sampson equation is more accurate for LDL-C evaluation in Chinese patients diagnosed with ACS, especially in patients with hypertriglyceridemia even in those with TG > 800 mg/dL. Additionally, the Sampson equation demonstrates greater accuracy even in subgroups of various baseline characteristics and comorbidities.

A Tale of Two Approaches

OBJECTIVES

To summarize and assess the literature on the performances of methods beyond the Friedewald formula (FF) used in routine practice to determine low-density lipoprotein cholesterol (LDL-C).

METHODS

A literature review was performed by searching the PubMed database. Many peer-reviewed articles were assessed.

RESULTS

The examined methods included direct homogeneous LDL-C assays, the FF, mathematical equations derived from the FF, the Martin-Hopkins equation (MHE), and the Sampson equation. Direct homogeneous assays perform inconsistently across manufacturers and disease status, whereas most FF-derived methods exhibit variable levels of performance across populations. The MHE consistently outperforms the FF but cannot be applied in the setting of severe hypertriglyceridemia. The Sampson equation shows promise against both the FF and MHE, especially in severe hypertriglyceridemia, but data are still limited on its validation in various settings, including disease and therapeutic states.

CONCLUSIONS

There is still no consensus on a universal best method to estimate LDL-C in routine practice. Further studies are needed to assess the performance of the Sampson equation.

Remnants, LDL, and the Quantification of Lipoprotein-Associated Risk in Atherosclerotic Cardiovascular Disease

PURPOSE OF REVIEW

Implementation of intensive LDL cholesterol (LDL-C) lowering strategies and recognition of the role of triglyceride-rich lipoproteins (TRL) in atherosclerosis has prompted re-evaluation of the suitability of current lipid profile measurements for future clinical practice.

RECENT FINDINGS

At low concentrations of LDL-C (< 1.8 mmol/l/70 mg/dl), the Friedewald equation yields estimates with substantial negative bias. New equations provide a more accurate means of calculating LDL-C. Recent reports indicate that the increase in risk per unit increment in TRL/remnant cholesterol may be greater than that of LDL-C. Hence, specific measurement of TRL/remnant cholesterol may be of importance in determining risk. Non-HDL cholesterol and plasma apolipoprotein B have been shown in discordancy analyses to identify individuals at high risk even when LDL-C is low. There is a need to adopt updated methods for determining LDL-C and to develop better biomarkers that more accurately reflect the abundance of TRL remnant particles.

Egyptian practical guidance in hypertriglyceridemia management 2021

Hypertriglyceridemia (HTG) is a very common, yet underappreciated problem in clinical practice. Elevated triglyceride (TG) levels are independently associated with atherosclerotic cardiovascular disease (ASCVD) risk. Furthermore, severe HTG may lead to acute pancreatitis. Although LDL-guided statin therapy has improved ASCVD outcomes, residual risk remains. Recent trials have demonstrated that management of high TG levels, in patients already on statin therapy, reduces the rate of major vascular events. Few guidelines were issued, providing important recommendations for HTG management strategies. The goal of treatment is to reduce the risk of ASCVD and acute pancreatitis. The management stands on lifestyle modification, detection of secondary causes of HTG and pharmacological therapy, when indicated. In this guidance we review the causes and classification of HTG and summarize the current methods for risk estimation, diagnosis and treatment. The present guidance provides a focused update on the management of HTG, outlined in a simple user-friendly format, with an emphasis on the latest available data.