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Abstract Background A distorted blood lipid profile is an important risk factor for ischemic heart disease (IHD) but the predictive ability of the different lipid measures has rarely been studied. Our aim was to examine and compare, in a large sample of women, the predictive ability of total cholesterol/HDL cholesterol ratio (TC/HDL-C) and non-HDL-C in relation to IHD, adjusted for age, exercise, smoking, waist-hip ratio, blood pressure, and diabetes mellitus. Methods Between 1995 and 2000, a total of 6537 women aged 50–59 years from the Women’s Health in Lund area (WHILA) study in southern Sweden were included and underwent a baseline examination. The women were followed through national registers for incidence of IHD during a mean follow-up of 17 years. The prediction accuracy was estimated through Harrell’s C and Akaike Information Criterion (AIC). Results Increasing TC/HDL-C as well as non-HDL-C showed strong associations with IHD, with the highest risk in the 5th quintile, where the HR was 2.30 (95% CI: 1.70–3.11) for TC/HDL-C and 1.67 (95% CI: 1.25–2.24) for non-HDL-C, after adjustments. Comparisons using Harrell’s C and AIC indicated that TC/HDL-C has a slightly higher predictive ability than that of non-HDL-C (Harrell’s C 0.62 and 0.59 respectively, p = 0.003 for difference, age-adjusted model; AIC for TC/HDL-C

Abstract Background Dyslipidemia contributes to the development of nephrolithiasis in adults; however its relationship to urolithiasis in children remains debatable, and will be clarified in the present work. Methods A case–control study was performed involving 58 pediatric patients diagnosed with upper urinary tract stones as well as 351 controls. Age, gender, body mass index (BMI), serum calcium, serum uric acid, blood glucose, blood lipids, and compositions of stones were compared. Results According to the univariate analysis, uric acid was higher (P

Abstract Background Lipid-lowering therapy is guided by Low-density-lipoprotein cholesterol (LDL-c) levels, although the cardiovascular disease (CVD) risk could be better reflected by other lipid parameters. This study aimed at comparing a comprehensive lipid profile between patients with type 2 diabetes mellitus (T2DM) with LDL-c concentration within and above target. Methods A comprehensive lipid profile was characterized in 96 T2DM patients. The European Society of Cardiology/European Atherosclerosis Society (ESC/EAS) 2016 and 2019 Guidelines for the Management of Dyslipidemias were used to define LDL-c targets. Results In this population, only 28.1 and 16.7% of patients had mean LDL-c levels within target, as defined by the 2016 and 2019 guidelines, respectively. Applying the 2016 guidelines criteria, in patients with LDL-c within target, 22, 25 and 44% presented non-high-density lipoprotein cholesterol (non-HDL-c), Apolipoprotein B (ApoB) and oxidized LDL-c levels above the recommended range, respectively, whereas according to the 2019 guidelines criteria, 50, 39 and 44% of the patients with LDL-c within target had elevated high-density lipoprotein cholesterol (HDL-c), ApoB and oxidized LDL-c levels, respectively. LDL-c was strongly correlated with non-HDL-c (r = 0.850), ApoB (r = 0.656) and oxidized LDL-c (r = 0.508). Similarly, there was a strong correlation between non-HDL-c with both ApoB (r = 0.808) and oxidized LDL-c (r = 0.588). Conclusions These findings emphasize the limitations of only considering LDL-c concentration for cardiovascular (CV) risk assessment. Targeting only LDL-c could result in missed opportunities for CV risk reduction in T2DM patients. These data suggest that non-HDL-c, ApoB and oxidized LDL-c levels could be considered as an important part of these patients’ evaluation allowing for a more accurate estimation of CV risk and hopefully better management of these high-risk patients.

Abstract Background Probiotics incorporated into dairy products have been shown to reduce total (TC) and LDL cholesterolemia (LDL-C) in subjects with moderate hypercholesterolemia. More specifically, probiotics with high biliary salt hydrolase activity, e.g. Bifidobacterium longum BB536, may decrease TC and LDL-C by lowering intestinal cholesterol reabsorption and, combined with other nutraceuticals, may be useful to manage hypercholesterolemia in subjects with low cardiovascular (CV) risk. This study was conducted to evaluate the efficacy and safety of a nutraceutical combination containing Bifidobacterium longum BB536, red yeast rice (RYR) extract (10 mg/day monacolin K), niacin, coenzyme Q10 (Lactoflorene Colesterolo®). The end-points were changes of lipid CV risk markers (LDL-C, TC, non-HDL-cholesterol (HDL-C), triglycerides (TG), apolipoprotein B (ApoB), HDL-C, apolipoprotein AI (ApoAI), lipoprotein(a) (Lp(a), proprotein convertase subtilisin/kexin type 9 (PCSK9)), and of markers of cholesterol synthesis/absorption. Methods A 12-week randomized, parallel, double-blind, placebo-controlled study. Thirty-three subjects (18–70 years) in primary CV prevention and low CV risk (SCORE: 0–1% in 24 and 2–4% in 9 subjects; LDL-C: 130–200 mg/dL) were randomly allocated to either nutraceutical (N = 16) or placebo (N = 17). Results Twelve-week treatment with the nutraceutical combination, compared to placebo, significantly reduced TC (− 16.7%), LDL-C (− 25.7%), non-HDL-C (− 24%) (all p

Abstract Background Excessive lipid depositing in liver cells could induce pathophysiological development of liver. Our study aimed to assess whether non-HDL cholesterol to HDL-cholesterol ratio (NonHDLc/HDLc) is an independent risk factor for liver function tests (LFTs) abnormalities in geriatric population. Methods We enrolled 1745 eligible subjects (714 males, 1031 females) with normal liver function tests at baseline who participated in annual health checkup for liver disease in 2015. Logistic regression models were used to examine the independent relationship between NonHDLc/HDLc ratio and LFTs abnormalities. Results After one year follow-up, there were 6.1% (n = 107) participants developed new-onset LFTs abnormalities in 2016. Equally dividing participants into tertiles according to their baseline NonHDLc/HDLc ratio levels, we found compared with tertile 1, the multivariable-adjusted ORs (95% CIs) for new-onset LFTs abnormalities of tertile 3 were 2.85 (1.18–6.93), P = 0.021. In stratified analysis, compared with controls, the correlation between NonHDLc/HDLc ratio and incidence of LFTs abnormalities was more remarkable in female individuals, BMI > 24 individuals and free of diabetes individuals. Conclusion Our study suggests that NonHDLc/HDLc ratio is an independent risk factor for LFTs abnormalities in geriatric population, and assessment of NonHDLc/HDLc ratio may help early identify high risk people of liver diseases. Trial registration Trial registration in the Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology (IORG No: IORG0003571). Registered 3 March 2015.

Abstract Background Serum total cholesterol (TC) and LDL cholesterol (LDL-C) have been used as major laboratory measures in clinical practice to assess cardiovascular risk in the general population and disease management as well as prognosis in patients. However, some studies have also reported the use of non-HDL cholesterol (non-HDL-C). As non-HDL-C can be calculated by subtracting HDL-C from TC, both of which do not require fasting blood sample in contrast to LDL-C which requires fasting blood sample, we aimed to compare non-HDL-C with LDL-C as a predictor of myocardial infarction (MI). Methods This hospital based cross sectional study was undertaken among 51 cases of MI and equal number of controls. MI was diagnosed based on the clinical history, ECG changes and biochemical parameters. 5 mL of fasting blood sample was collected from each research participant for the analysis of lipid profile. Non-HDL-C was calculated by using the equation; Non-HDL-C = TC – HDL-C. Statistical analysis was performed using SPSS 14.0. Results 42 MI cases were dyslipidemic in contrast to 20 dyslipidemic subjects under control group. The differences in the median values of each lipid parameter were statistically significant between MI cases and controls. The lipid risk factors most strongly associated with MI were HDL-C (OR 5.85, 95% CI 2.41-14.23, P value = 0.000) followed by non-HDL-C (OR 3.77, 95% CI 1.64-8.66, P value = 0.002), LDL-C/HDL-C (OR 3.38, 95% CI 1.44-7.89, P value = 0.005), TC/HDL-C (OR 2.93, 95% CI 1.36-7.56, P value = 0.026), LDL-C (OR 2.70, 95% CI 1.20-6.10, P value = 0.017), TC (OR 2.68, 95% CI 1.04-6.97, P value = 0.042) and Tg (OR 2.54, 95% CI 1.01-6.39, P value = 0.047). Area under the receiver operating curve was greater for non-HDL-C than for LDL-C. Non-HDL-C was also found to be more sensitive and specific than LDL-C for MI. Conclusions HDL-C and non-HDL-C are better discriminating parameters than LDL-C for MI. Thus, we can simply perform test for HDL-C and non-HDL-C both of which do not require fasting blood sample rather than waiting for fasting blood sample to measure LDL-C.