Importance of Optimization of Cardiovascular Risk Factors and Lifestyle Behaviours

Using data mining technology to explore homocysteine at low levels

A high homocysteine level is known to be an independent risk factor for cardiovascular diseases; however, whether or not low homocysteine level contributes to any damage to the body has not been extensively studied. Furthermore, acquiring healthy subject databases from domestic studies on homocysteine is not trivial. Therefore, we aimed to investigate the causality between serum homocysteine levels and health status and lifestyle factors, particularly with a focus on low serum homocysteine levels. Additionally, we discussed a systematic methodical platform for data collection and statistical analysis, using the descriptive analysis of the chi-square test, t test, multivariate analysis of variance, and logistic regression.This study was a cross-sectional analysis of 5864 subjects (i.e., clients of a health examination clinic) in Taipei, Taiwan during a general health check-up in 2017. The patients' personal information and associated links were excluded. A sample group was selected as per the health criteria defined for this research whose data were processed using SPSS for descriptive statistical analysis using chi-square test, t test, multivariate analysis of variance, and logistic regression analysis.Those working for >12 hours/day had a higher homocysteine level than those working for <12 hours/day (P < .001). The average serum homocysteine level was 7.9 and 8.6 mol/L for people with poor sleep quality and good sleep quality, respectively (P = .003). The homocysteine value of people known to have cancer was analyzed using the logistic regression analysis, revealing a Δodds value of 0.898. The percentage of subjects with a homocysteine value of ≤6.3 μmol/L, who perceived their health status as "not very good" or "very bad," was higher than those with a higher homocysteine level. The number of subjects who perceived their health as poor was higher than expected.The results suggest that the homocysteine level could be an effective health management indicator. We conclude that normal homocysteine level should not be ≤6.3 μmol/L. Moreover, homocysteine should not be considered as harmful and its fluctuations from the normal range could be utilized to infer a person's physical status for health management.

Lifetime risk of cardiometabolic mortality according to vitamin D status of middle and older-aged adults: NHANES III mortality follow-up

The predictive value of total 25-hydroxyvitamin D (25(OH)D, a biomarker of vitamin D status) in relation to lifetime risk of cardiometabolic mortality is not known. The purpose of this study was to determine the association between standardized and annualized total 25(OH)D levels and lifetime risk for cardiometabolic mortality in middle- to older-aged adults. In this study, we followed up 7958 participants in the Third National Health and Nutrition Examination Survey from 1988 to 1994 (NHANES III) until the occurrence of cardiometabolic death or attainment of 95 years of age (median follow-up 17.9 years, 1371 cardiometabolic-deaths). Lifetime risks were estimated according to recommended total 25(OH)D cutoffs by national guidelines, and a combination of total 25(OH)D status and traditional risk factor burden. We also explored variation in lifetime risk estimates by levels of body mass index (BMI). The results of this study showed that annualized total 25(OH)D <30 nmol/L was associated with high lifetime risk of cardiometabolic mortality (40%). Lifetime risks of cardiometabolic mortality were similar for annualized levels between 30-< 50 nmol/L, 50-< 75 nmol/L and ≥75 nmol/L (31-33%). Lifetime risk was highest among participants with annualized total 25(OH)D <30 nmol/L and ≥2 major traditional risk factors (45%), whereas lifetime risk was lowest among participants with annualized 25(OH)D ≥30 nmol/L and low-intermediate risk factors (28%). Lifetime risk estimates were similar across BMI categories. In conclusion, a single measurement of vitamin D deficiency (annualized levels <30 nmol/L) in middle- to older-aged adults is a strong predictor of high lifetime risk for cardiometabolic mortality, particularly among those with high burden of traditional risk factors.

Optimisation of lipids for prevention of cardiovascular disease in a primary care

The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guidelines focus on atherosclerotic cardiovascular disease (ASCVD) risk reduction, using a Pooled Cohort Equation to calculate a patient’s 10-year risk score, which is used to guide initiation of statin therapy. We identified a gap of evidence-based treatment for hyperlipidaemia in the Internal Medicine Clinic. Therefore, the aim of this study was to increase calculation of ASCVD risk scores in patients between the ages of 40 and 75 years from a baseline rate of less than 1% to 10%, within 12 months, for primary prevention of ASCVD. Root cause analysis was performed to identify materials/methods, provider and patient-related barriers. Plan-Do-Study-Act cycles included: (1) creation of customised workflow in electronic health records for documentation of calculated ASCVD risk score; (2) physician education regarding guidelines and electronic health record workflow; (3) refresher training for residents and a chart alert and (4) patient education and physician reminders. The outcome measures were ASCVD risk score completion rate and percentage of new prescriptions for statin therapy. Process measures included lipid profile order and completion rates. Increase in patient wait time, and blood test and medications costs were the balanced measures. We used weekly statistical process control charts for data analysis. The average ASCVD risk completion rate was 14.2%. The mean ASCVD risk completion rate was 4.0%. In eligible patients, the average lipid profile completion rate was 18%. ASCVD risk score completion rate was 33% 1-year postproject period. A team-based approach led to a sustainable increase in ASCVD risk score completion rate. Lack of automation in ASCVD risk score calculation and physician prompts in electronic health records were identified as major barriers. Furthermore, the team identified multiple barriers to lipid blood tests and treatment of increased ASCVD risk based on ACC/AHA guidelines.