MATERIALS AND METHODS: This was a retrospective descriptive study. We identified 1041 patients (810 Chinese, 139 Malays, 92 Indians) without previous history of cardiovascular disease who underwent cardiac computed tomography for atypical chest pain evaluation. A cardiologist, who was blinded to the patients' clinical demographics, reviewed all scans. We retrospectively analysed all their case records.
RESULTS: Overall, Malays were most likely to be active smokers (P = 0.02), Indians had the highest prevalence of diabetes mellitus (P = 0.01) and Chinese had the highest mean age (P <0.0001). The overall prevalence of patients with non-calcified plaques as the only manifestation of sub-clinical coronary artery disease was 2.1%. There was no significant difference in the prevalence of CAC, mean CAC score or prevalence of non-calcified plaques among the 3 ethnic groups. Active smoking, age and hypertension were independent predictors of CAC. Non-calcified plaques were positively associated with male gender, age, dyslipidaemia and diabetes mellitus.
CONCLUSION: The higher MI rates in Malays and Indians in Singapore cannot be explained by any difference in CAC or non-calcified plaque. More research with prospective follow-up of larger patient populations is necessary to establish if ethnic-specific calibration of CAC measures is needed to adjust for differences among ethnic groups.
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.
DESIGN: Cross sectional study.
SETTING: Postgraduate primary care trainees in Malaysia.
PARTICIPANTS: 759 postgraduate primary care trainees were approached through email or hard copy, of whom 466 responded.
METHOD: A self-administered questionnaire was used to assess their awareness, knowledge and practice of dyslipidaemia management. The total cumulative score derived from the knowledge section was categorised into good or poor knowledge based on the median score, where a score of less than the median score was categorised as poor and a score equal to or more than the median score was categorised as good. We further examined the association between knowledge score and sociodemographic data. Associations were considered significant when p<0.05.
RESULTS: The response rate achieved was 61.4%. The majority (98.1%) were aware of the national lipid guideline, and 95.6% reported that they used the lipid guideline in their practice. The median knowledge score was 7 out of 10; 70.2% of respondents scored 7 or more which was considered as good knowledge. Despite the majority (95.6%) reporting use of guidelines, there was wide variation in their clinical practice whereby some did not practise based on the guidelines. There was a positive significant association between awareness and the use of the guideline with knowledge score (p<0.001). However there was no significant association between knowledge score and sociodemographic data (p>0.05).
CONCLUSIONS: The level of awareness and use of the lipid guideline among postgraduate primary care trainees was good. However, there were still gaps in their knowledge and practice which are not in accordance with standard guidelines.
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.
CONCLUSION: The risk factors that are reviewed here are hypertension, dyslipidemia, smoking, obesity, lack of exercise, hyperglycemia and diabetic nephropathy. We highlight the importance of early identification, and interventions, which include optimizing glycemic control, pharmacotherapy, regular physical activity and dietary changes.
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.
AIMS: To systematically identify and summarize the available literature on whether the modifiable risk factors associated with prediabetes displays similar relationship in both the genders.
METHODS: A systematic search was performed on electronic databases i.e. PubMed, EBSCOhost, and Scopus using "sex", "gender", "modifiable risk factors" and "prediabetes" as keywords. Reference list from identified studies was used to augment the search strategy. Methodological quality and results from individual studies were summarized in tables.
RESULTS: Gender differences in the risk factor association were observed among reviewed studies. Overall, reported association between risk factors and prediabetes apparently stronger among men. In particular, abdominal obesity, dyslipidemia, smoking and alcohol drinking habits were risk factors that showed prominent association among men. Hypertension and poor diet quality may appear to be stronger among women. General obesity showed stringent hold, while physical activity not significantly associated with the risk of prediabetes in both the genders.
CONCLUSIONS: Evidence suggests the existence of gender differences in risk factors associated with prediabetes, demands future researchers to analyze data separately based on gender. The consideration and the implementation of gender differences in health policies and in diabetes prevention programs may improve the quality of care and reduce number of diabetes prevalence among prediabetic subjects.