Convergent validity of the ACC/AHA pooled cohort equations in associating with health-related quality of life among adults in the United States

Cardiovascular Risk Prediction Models and Scores in the Era of Personalized Medicine

Cardiovascular disease (CVD) is the leading cause of death worldwide. Management of cardiovascular risk factors, particularly hypertension and dyslipidemia, has been shown to reduce cardiovascular morbidity and mortality. However, current guidelines recommend adjusting the intensity of blood pressure- and lipid-lowering treatment according to the cardiovascular risk of the patient. Therefore, cardiovascular risk prediction is a sine qua non for optimizing cardiovascular prevention strategies, particularly in patients without established CVD or type 2 diabetes mellitus (T2DM). As a result, several cardiovascular risk prediction equations have been developed. Nevertheless, it is still unclear which is the optimal prediction risk equation. In the present review, we summarize the current knowledge regarding the accuracy of the most widely used cardiovascular risk prediction equations. Notably, most of these risk scores have not been validated in external cohorts or were shown to over- or underestimate risk in populations other than those in which they derive. Accordingly, country-specific risk scores, where available, should be preferred for cardiovascular risk stratification.

Cardiovascular Disease Risk Among Older Immigrants in the United States: A Comparison of Risk Measures

BACKGROUND

In the United States, 16 million immigrants are 50 years and older, but little is known about their cardiometabolic health and how to best assess their cardiovascular disease (CVD) risk. Aging immigrants may therefore not be benefitting from advances in CVD prevention.

OBJECTIVE

In this study, we estimate and compare CVD risk in a nationally representative sample of aging immigrants using 3 different measures.

METHODS

This was a cross-sectional analysis using National Health and Nutrition Examination Survey data. Immigrants 50 years and older with no history of CVD were eligible. The Framingham Risk Score (FRS), the American College of Cardiology/American Heart Association Pooled Cohort Risk Equation, and presence of metabolic syndrome (MetS) were used to estimate risk. Bivariate statistics were analyzed using SPSS version 23.0 Complex Survey module to account for National Health and Nutrition Examination Survey unique weighting scheme.

RESULTS

The mean age of the sample was 61.3 years; 40% had hypertension, 17% had diabetes, 10% were smokers, and 95% did not meet the recommended physical activity guidelines. Proportions at an elevated CVD risk were as follows: American College of Cardiology/American Heart Association, 42% female and 76% male; FRS, 17.4% female and 76% male; and MetS, 22% female and 24% male.

CONCLUSIONS

Immigrants had a lower overall risk using MetS and the American College of Cardiology/American Heart Association equation than has been found using these tools in similarly aged samples. The opposite was true for the FRS. The discrepancy between the proportion at risk and those being treated may reflect healthcare access gaps that warrant further investigation. A more holistic approach to risk measurement is needed that accounts for determinants of health that disproportionately affect immigrants, including language and socioeconomic status.

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.