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Abstract Background Universal lipid screening in childhood for early detection and treatment of familial hypercholesterolemia is under discussion, but will also detect children with multifactorial dyslipidemia. Results from population-based studies can support the design of public health strategies. As few previous studies considered pubertal changes in serum lipid levels, we examined tracking of serum lipids from prepuberty to young adulthood in a population-based cohort. Methods This longitudinal study includes 692 children from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS; baseline: 2003–2006, follow-up: 2014–2017) who were 6–8 years old at baseline, at least 18 years old at follow-up, and had measurements of serum total cholesterol (TC), high-density and non-high-density lipoprotein cholesterol (HDL-C; non-HDL-C) at both time points. We calculated proportions of participants by life stage-specific risk categories applying cut points for young children and young adults. We used correlation coefficients to estimate serum lipid tracking from childhood to young adulthood. The association between follow-up and baseline lipid levels was examined in sex-specific multivariable linear regression models including body mass index (BMI), health-related behaviors and medication use as covariables. Results The correlation coefficient between baseline and follow-up was 0.60 for non-HDL-C, 0.56 for TC, and 0.43 for HDL-C and was higher in males than in females. 67% of participants had acceptable and 9% had borderline/elevated non-HDL-C levels at both time points. Of participants with borderline/elevated non-HDL-C levels at baseline 32% remained in this category and 68% improved. Non-HDL-C levels at baseline explained 53% of the variance in levels at follow-up in males and 28% in females. After adjustment for covariables, the explained variance increased to 62% in males and 45% in females. An increase in BMI z-scores from childhood to young adulthood in all sexes and oral contraceptive use in females was positively associated with higher levels at follow-up. Conclusions Non-HDL-C levels in prepuberty are moderate predictors of levels in young adulthood, along with increasing BMI from childhood to young adulthood, and oral contraceptive use among women. Comprehensive strategies including public health interventions targeting elevated lipid levels and obesity in combination, are essential to prevent premature cardiovascular events.

Background: Universal lipid screening in childhood for early detection and treatment of familial hypercholesterolemia is under discussion, but will also detect children with multifactorial dyslipidemia. Results from population-based studies can support the design of public health strategies. As few previous studies considered pubertal changes in serum lipid levels, we examined tracking of serum lipids from prepuberty to young adulthood in a population-based cohort. Methods: This longitudinal study includes 692 children from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS; baseline: 2003–2006, follow-up: 2014–2017) who were 6–8 years old at baseline, at least 18 years old at follow-up, and had measurements of serum total cholesterol (TC), high-density and non-high-density lipoprotein cholesterol (HDL-C; non-HDL-C) at both time points. We calculated proportions of participants by life stage-specific risk categories applying cut points for young children and young adults. We used correlation coefficients to estimate serum lipid tracking from childhood to young adulthood. The association between follow-up and baseline lipid levels was examined in sex-specific multivariable linear regression models including body mass index (BMI), health-related behaviors and medication use as covariables. Results: The correlation coefficient between baseline and follow-up was 0.60 for non-HDL-C, 0.56 for TC, and 0.43 for HDL-C and was higher in males than in females. 67% of participants had acceptable and 9% had borderline/elevated non-HDL-C levels at both time points. Of participants with borderline/elevated non-HDL-C levels at baseline 32% remained in this category and 68% improved. Non-HDL-C levels at baseline explained 53% of the variance in levels at follow-up in males and 28% in females. After adjustment for covariables, the explained variance increased to 62% in males and 45% in females. An increase in BMI z-scores from childhood to young adulthood in all sexes and oral contraceptive use in females was positively associated with higher levels at follow-up. Conclusions: Non-HDL-C levels in prepuberty are moderate predictors of levels in young adulthood, along with increasing BMI from childhood to young adulthood, and oral contraceptive use among women. Comprehensive strategies including public health interventions targeting elevated lipid levels and obesity in combination, are essential to prevent premature cardiovascular events. [ABSTRACT FROM AUTHOR]

One of the leading causes of death and morbidity in the globe is cardiovascular disease (CAD). According to the WHO statistics from the year, 17.9 million individuals die worldwide every year from cardiovascular diseases. One of the simplest alternatives to computed LDL levels is to make use of non-HDL lipoprotein. Comparing non-HDL cholesterol to LDL cholesterol has shown that multiple research studies have demonstrated non-HDL cholesterol's superior ability to identify risks for CAD. In order to compare and contrast LDL and non-HDL cholesterol levels in individuals with CAD, the present investigation will compare and contrast these two measurements. Fifty healthy people between the ages of thirty and seventy-five were included in the study as controls, whereas 130 patients with CAD diagnoses were included as cases. The study was conducted among 180 patients who were diagnosed with cardiovascular disease. The positive relationship between non-HDL-cholesterol and LDL cholesterol levels is seen by the Pearson correlation. Using non-HDL cholesterol, an independent T-test yields a positive result of <0.001. The study's conclusion is that non-HDL cholesterol yields results that are similar to Friedwald's well-established LDL-C. Non-HDL-C can be used as a marker for CAD deduction and also for diagnostic and therapeutic markers for CAD. [ABSTRACT FROM AUTHOR]

• For this study data from a randomized trial performed in 28 patients with FD were used. • Friedewald, Martin-Hopkins, direct assay and gels to determine LDL-C were compared to UC. • All methods over- or underestimated LDL-C concentrations compared to UC. • UC probably overestimates LDL-C concentrations as well. • Non-HDL-C measured by standard assays performed well compared to non-HDL-C by UC. To compare LDL-C concentrations using the Friedewald formula, the Martin-Hopkins formula, a direct assay and polyacrylamide gradient gel electrophoresis (PGGE) to the reference standard density gradient ultracentrifugation in patients with Familial Dysbetalipoproteinemia (FD) patients. We also compared non-HDL-cholesterol concentrations by two methods. For this study data from 28 patients with genetically confirmed FD from the placebo arm of the EVOLVE-FD trial were used. Four different methods for determining LDL-C were compared with ultracentrifugation. Non-HDL-C was measured with standard assays and compared to ultracentrifugation. Correlation coefficients and Bland-Altman plots were used to compare the methods. Mean age of the 28 FD patients was 62 ± 9 years, 43 % were female and 93 % had an ɛ2ɛ2 genotype. LDL-C determined by Friedewald (R2 = 0.62, p <0.01), Martin-Hopkins (R2 = 0.50, p = 0.01) and the direct assay (R2 = 0.41, p = 0.03) correlated with density gradient ultracentrifugation. However, Bland-Altman plots showed considerable over- or underestimation by the four methods compared to ultracentrifugation. Non-HDL-C showed good correlation and agreement. In patients with FD, all four methods investigated over- or underestimated LDL-C concentrations compared with ultracentrifugation. In contrast, standard non-HDL-C assays performed well, emphasizing the use of non-HDL-C in patients with FD. [ABSTRACT FROM AUTHOR]

Background: Patients are treated with statins for the control of cholesterol; but statins control only low-density lipoprotein (LDL) and not non-high-density lipoprotein (non-HDL). Also, LDL is not a good coronary risk predictor. That creates the necessity to find a better biomarker for future coronary risk prediction. Hence, biomarkers under this territory such as total cholesterol (TC)/HDL, LDL/HDL, triglyceride (TG)/HDL ratios, non-HDL, apolipoprotein-B (apo-B), and high-sensitivity C-reactive protein (hs-CRP) were to be assessed and correlated with LDL to find the better biomarker in Indian patients. Objective: The objective was to study non-HDL, apo-B, TC/HDL, TG/HDL, LDL/HDL ratios, and hs-CRP in patients under statin therapy; and to correlate them with their LDL; to predict the risk of future coronary events; and to identify which biomarker among them is better at detecting the same. Materials and Methods: This is a cross-sectional observational study performed by systematic random sampling among 87 patients under statin therapy, and the levels of LDL, TC/HDL, LDL/HDL, TG/HDL ratios, non-HDL, apo-B, and hs-CRP were measured in such patients, and their correlation with optimized and unoptimized LDL groups were done. Continuous data were represented as mean and standard deviation, andP value was calculated using independent t-test or z-test. Results: Non-HDL, TC/HDL, and LDL/HDL ratios were found to be statistically significant – all three parameters withP < 0.0001 in predicting the coronary artery disease attacks in the future. Conclusion: Even though all patients in our study were under statin therapy, they are still under the risk of developing coronary events. This can be solved by targeting the control of non-HDL or TC/HDL or LDL/HDL ratios, as they are found be better biomarkers for future coronary risk prediction.

Background There is accumulating evidence that serum levels of non–high‐density lipoprotein cholesterol (non–HDL‐C) are a more accurate predictor of cardiovascular outcomes when compared with low‐density lipoprotein cholesterol. However, we recently found that higher serum concentrations of triglycerides are associated with better outcomes in patients undergoing hemodialysis. Therefore, we hypothesized that the association of serum levels of non–HDL‐C (which includes triglyceride‐rich lipoproteins) with outcomes may also be different in patients undergoing hemodialysis when compared with other patient populations. Methods and Results We studied the association of baseline and time‐dependent serum levels of non–HDL‐C with all‐cause and cardiovascular mortality using Cox proportional hazard regression models in a nationally representative cohort of 50 118 patients undergoing incident hemodialysis from January 1, 2007, to December 31, 2011. In time‐dependent models adjusted for case mix and surrogates of malnutrition and inflammation, a graded inverse association between non–HDL‐C level and mortality was demonstrated with hazard ratios (95% confidence intervals) of the lowest (

Background: Turner syndrome (TS) is associated with an increased risk of cardiovascular disease. Non-high-density lipoprotein cholesterol (non-HDL-C) is a convenient measure of atherogenicity (normal concentration <120 mg/dL) but has not been investigated in TS. We aim to evaluate non- HDL-C patterns in a cohort of pediatric and young adult females with TS. Methods: A retrospective chart review was used to obtain demographics, body composition, genetic reports and lipid profiles in females with TS. Results: Lipid profiles were assessed in 158 females (mean age 13.6 years). Mean non-HDL-C was 118.9 mg/dL (±32.0); the prevalence of high non-HDL-C (⩾144 mg/dL) was 17.7% (n = 28). In TS females aged 8-17 years (n = 46), the prevalence of high non-HDL-C was 23.9% (95% CI 11.1-36.7; n = 11) between 2011 and 2012, compared to 9.2% (95% CI 5.6-14.1) in females of the same age in the general population reported in the National Health and Nutrition Examination Survey (NHANES) dataset (p < 0.005). Body mass index (BMI) accounted for only 6% of variance in non-HDL-C values (β coefficient = 1.31, p < 0.05). Conclusions: Children and adolescents aged 8-17 years with TS appear to have a greater prevalence of adverse non-HDL-C levels compared to the general adolescent population. The prevalence of high non- HDL-C was not fully explained by BMI. [ABSTRACT FROM AUTHOR]

Background: One in every six adults (16.3% of the U.S. adult population) has high total cholesterol levels, and they are at double the risk of heart disease compared with people with optimal levels. Objective: To evaluate compliance of internal medicine residents with the latest National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) guidelines in treating patients with hyperlipidemia. Design: Retrospective observational study. Setting: Ambulatory Clinic, Saint Vincent Hospital, Worcester, Massachusetts. Patients: Patients with a diagnosis of hyperlipidemia who attended the clinic during a 1-ear period, from December 2009 to November 2010. Measurements: A review of medical records was conducted to evaluate residents’ compliance with the NCEP-ATP III guidelines for LDL cholesterol and non-HDL cholesterol management. Results: Seven hundred seventy charts were reviewed. Only 212 (27.5%) met the inclusion criteria. Analysis of data revealed better compliance with drug therapy (44%−77%) and therapeutic lifestyle changes (44%−83%) when compared with follow-up recommendations (22%−31%). An increase in compliance also was noted in all areas of intervention when patients had an abnormal lipid profile. Limitations: Compliance was assessed on the basis of electronic medical record documentation alone and hence we may be underestimating compliance with therapeutic lifestyle changes and follow-up recommendations. Conclusion: Compliance among internal medicine residents in the diagnosis, treatment and follow-up of patients with hyperlipidemia according to NCEP-ATP III guidelines was suboptimal and needs improvement. [ABSTRACT FROM AUTHOR]