METHODS AND RESULTS: We performed a systematic search of all available RCTs conducted up to 21 February 2019 in the following databases: PubMed, Scopus, and Cochrane. The choice of fixed- or random-effect model for analysis was determined according to the I2 statistic. Effect sizes were expressed as weighted mean difference (WMD) and 95% confidence interval (CI). Pooling of 12 effect sizes from seven articles revealed a significant reduction of Lp(a) levels following PS supplementation (MD: -0.025 mg/dl, 95% CI: -0.045, -0.004, p = 0.017) without significant heterogeneity among the studies (I2 = 0.0%, p = 0.599). Also, PS supplementation significantly lowered FFA (MD: -0.138 mg/dl, 95% CI: -0.195, -0.081, p = 0.000) without significant heterogeneity among the studies (I2 = 0.0%, p = 0.911). The results for meta-regression and sensitivity analysis were not significant.
CONCLUSION: The meta-analysis suggests that oral PS supplementation could cause a significant reduction in serum Lp(a) and FFA.
Methods: A questionnaire was distributed to adult Asian patients with dyslipidemia at two primary care clinics (polyclinics) in northeastern Singapore. The demographic and clinical data for this sub-population with both T2DM and dyslipidemia were collated with laboratory and treatment information retrieved from their electronic health records. The combined data was then analyzed to determine the proportion of patients who attained triple treatment goals, and logistic regression analysis was used to identify factors associated with this outcome.
Results: 665 eligible patients [60.5% female, 30.5% Chinese, 35% Malays, and 34.4% Indians] with a mean age of 60.6 years were recruited. Of these patients, 71% achieved LDL-C ≤2.6 mmol/L, 70.4% had BP
METHODS AND RESULTS: Blood pressures, fasting lipid profile and fasting glucose were measured, and DASH score was computed based on a 22-item food frequency questionnaire. Older individuals, women, those not consuming alcohol and those undertaking regular physical activity were more likely to have higher DASH scores. In the Malaysian cohort, while total DASH score was not significantly associated with cardio-metabolic risk factors after adjusting for confounders, significant associations were observed for intake of green vegetable [0.011, standard error (SE): 0.004], and red and processed meat (-0.009, SE: 0.004) with total cholesterol. In the Philippines cohort, a 5-unit increase in total DASH score was significantly and inversely associated with systolic blood pressure (-1.41, SE: 0.40), diastolic blood pressure (-1.09, SE: 0.28), total cholesterol (-0.015, SE: 0.005), low-density lipoprotein cholesterol (-0.025, SE: 0.008), and triglyceride (-0.034, SE: 0.012) after adjusting for socio-demographic and lifestyle groups. Intake of milk and dairy products, red and processed meat, and sugared drinks were found to significantly associated with most risk factors.
CONCLUSIONS: Differential associations of DASH diet and dietary components with cardio-metabolic risk factors by country suggest the need for country-specific tailoring of dietary interventions to improve cardio-metabolic risk profiles.
SETTING: Fifteen participating cardiology centres contributed to the Malaysian National Cardiovascular Disease Database-Percutaneous Coronary Intervention (NCVD-PCI) registry.
PARTICIPANTS: 28 742 patients from the NCVD-PCI registry who had their first PCI between January 2007 and December 2014 were included. Those without their BMI recorded or BMI <11 kg/m2 or >70 kg/m2 were excluded.
MAIN OUTCOME MEASURES: In-hospital death, major adverse cardiovascular events (MACEs), vascular complications between different BMI groups were examined. Multivariable-adjusted HRs for 1-year mortality after PCI among the BMI groups were also calculated.
RESULTS: The patients were divided into four groups; underweight (BMI <18.5 kg/m2), normal BMI (BMI 18.5 to <23 kg/m2), overweight (BMI 23 to <27.5 kg/m2) and obese (BMI ≥27.5 kg/m2). Comparison of their baseline characteristics showed that the obese group was younger, had lower prevalence of smoking but higher prevalence of diabetes, hypertension and dyslipidemia. There was no difference found in terms of in-hospital death, MACE and vascular complications after PCI. Multivariable Cox proportional hazard regression analysis showed that compared with normal BMI group the underweight group had a non-significant difference (HR 1.02, p=0.952), while the overweight group had significantly lower risk of 1-year mortality (HR 0.71, p=0.005). The obese group also showed lower HR but this was non-significant (HR 0.78, p=0.056).
CONCLUSIONS: Using Asian-specific BMI cut-off points, the overweight group in our study population was independently associated with lower risk of 1-year mortality after PCI compared with the normal BMI group.
RECENT FINDINGS: Genetic testing for familial hypercholesterolaemia is valuable to enhance diagnostic precision, cascade testing, risk prediction and the use of new medications. Hypertriglyceridaemia may be caused by rare recessive monogenic, or by polygenic, gene variants; genetic testing may be useful in the former, for which antisense therapy targeting apoC-III has been approved. Familial high-density lipoprotein deficiency is caused by specific genetic mutations, but there is no effective therapy. Familial combined hyperlipidaemia (FCHL) is caused by polygenic variants for which there is no specific gene testing panel. Familial dysbetalipoproteinaemia is less frequent and commonly caused by APOE ε2ε2 homozygosity; as with FCHL, it is responsive to lifestyle modifications and statins or/and fibrates. Elevated lipoprotein(a) is a quantitative genetic trait whose value in risk prediction over-rides genetic testing; treatment relies on RNA therapeutics.
SUMMARY: Genetic testing is not at present commonly available for managing dyslipidaemias. Rapidly advancing technology may presage wider use, but its worth will require demonstration of cost-effectiveness and a healthcare workforce trained in genomic medicine.
METHODS: REDISCOVER, a prospective study, enrolled 11,288 adults where sociodemographic data, anthropometric and blood pressure measurements, fasting lipid profile and glucose, and history of diabetes, hypertension, and smoking were obtained. The cross-sectional analytic sample presented in this article comprised 10,482 participants from baseline recruitment. The data was analysed by descriptive statistics and multivariable logistic regression.
RESULTS: The overall prevalence of elevated TC, elevated LDL-c, elevated TG, low HDL-c, and elevated non-HDL-c were 64.0% (95% CI 63.0-65.0), 56.7% (CI 55.7-57.7), 37.4% (CI 36.5-38.4), 36.2% (CI 35.2-37.1), and 56.2% (CI 55.3-57.2), respectively. Overweight, obesity, and central obesity were highly prevalent and significantly associated with elevated TC and all dyslipidaemia subtypes. Older age was associated with elevated TC, elevated LDL-c and elevated non-HDL-c. Hypertension was associated with elevated TC, elevated TG, and elevated non-HDL-c, while diabetes was associated with elevated TG and low HDL-c.
CONCLUSIONS: Elevated TC and all dyslipidaemia subtypes are highly prevalent in Malaysia where increased body mass seems the main driver. Differences in the prevalence and associated personal and clinical attributes may facilitate specific preventive and management strategies.