cardiovascular disease

This review aims at summarizing updated evidence on cardiovascular disease (CVD) risk associated with consumption of specific food items to substantiate dietary strategies for atherosclerosis prevention. A systematic search on PubMed was performed to identify meta-analyses of cohort studies and RCTs with CVD outcomes. The evidence is highly concordant in showing that, for the healthy adult population, low consumption of salt and foods of animal origin, and increased intake of plant-based foods—whole grains, fruits, vegetables, legumes, and nuts—are linked with reduced atherosclerosis risk. The same applies for the replacement of butter and other animal/tropical fats with olive oil and other unsaturated-fat-rich oil. Although the literature reviewed overall endorses scientific society dietary recommendations, some relevant novelties emerge. With regard to meat, new evidence differentiates processed and red meat—both associated with increased CVD risk—from poultry, showing a neutral relationship with CVD for moderate intakes. Moreover, the preferential use of low-fat dairies in the healthy population is not supported by recent data, since both full-fat and low-fat dairies, in moderate amounts and in the context of a balanced diet, are not associated with increased CVD risk; furthermore, small quantities of cheese and regular yogurt consumption are even linked with a protective effect. Among other animal protein sources, moderate fish consumption is also supported by the latest evidence, although there might be sustainability concerns. New data endorse the replacement of most high glycemic index (GI) foods with both whole grain and low GI cereal foods. As for beverages, low consumption not only of alcohol, but also of coffee and tea is associated with a reduced atherosclerosis risk while soft drinks show a direct relationship with CVD risk. This review provides evidence-based support for promoting appropriate food choices for atherosclerosis prevention in the general population.

Atherosclerotic CVD remains the leading cause of death for people of most racial/ethnic groups. In 2010, the AHA suggested metrics of ideal cardiovascular health in 7 domains (blood pressure, physical activity, cholesterol, diet, weight, smoking, and blood glucose). There have since been multiple related guideline updates and scientific statements. In 2017, the ACC/AHA Task Force on Clinical Practice Guidelines commissioned an updated guideline integrating existing and new recommendations into a unified and “user-friendly” document on primary prevention of ASCVD.

Description:

In November 2018, the American Heart Association and American College of Cardiology (AHA/ACC) released a new clinical practice guideline on cholesterol management. It was accompanied by a risk assessment report on primary prevention of atherosclerotic cardiovascular disease (ASCVD).

Methods:

A panel of experts free of recent and relevant industry-related conflicts was chosen to carry out systematic reviews and meta-analyses of randomized controlled trials (RCTs) that examined cardiovascular outcomes. High-quality observational studies were used for estimation of ASCVD risk. An independent panel systematically reviewed RCT evidence about the benefits and risks of adding nonstatin medications to statin therapy compared with receiving statin therapy alone in persons who have or are at high risk for ASCVD.

Recommendation:

The guideline endorses a heart-healthy lifestyle beginning in childhood to reduce lifetime risk for ASCVD. It contains several new features compared with the 2013 guideline. For secondary prevention, patients at very high risk may be candidates for adding nonstatin medications (ezetimibe or proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitors) to statin therapy. In primary prevention, a clinician–patient risk discussion is still strongly recommended before a decision is made about statin treatment. The AHA/ACC risk calculator first triages patients into 4 risk categories. Those at intermediate risk deserve a focused clinician–patient discussion before initiation of statin therapy. Among intermediate-risk patients, identification of risk-enhancing factors and coronary artery calcium testing can assist in the decision to use a statin. Compared with the 2013 guideline, the new guideline gives more attention to percentage reduction in low-density lipoprotein cholesterol as a treatment goal and to long-term monitoring of therapeutic efficacy. To simplify monitoring, nonfasting lipid measurements are allowed.

AIMS:

Although group-level effectiveness of lipid, blood pressure, glucose, and aspirin treatment for prevention of cardiovascular disease (CVD) has been proven by trials, important differences in absolute effectiveness exist between individuals. We aim to develop and validate a prediction tool for individualizing lifelong CVD prevention in people with Type 2 diabetes mellitus (T2DM) predicting life-years gained without myocardial infarction or stroke.

METHODS AND RESULTS:

We developed and validated the Diabetes Lifetime-perspective prediction (DIAL) model, consisting of two complementary competing risk adjusted Cox proportional hazards functions using data from people with T2DM registered in the Swedish National Diabetes Registry (n = 389 366). Competing outcomes were (i) CVD events (vascular mortality, myocardial infarction, or stroke) and (ii) non-vascular mortality. Predictors were age, sex, smoking, systolic blood pressure, body mass index, haemoglobin A1c, estimated glomerular filtration rate, non- high-density lipoprotein cholesterol, albuminuria, T2DM duration, insulin treatment, and history of CVD. External validation was performed using data from the ADVANCE, ACCORD, ASCOT and ALLHAT-LLT-trials, the SMART and EPIC-NL cohorts, and the Scottish diabetes register (total n = 197 785). Predicted and observed CVD-free survival showed good agreement in all validation sets. C-statistics for prediction of CVD were 0.83 (95% confidence interval: 0.83-0.84) and 0.64-0.65 for internal and external validation, respectively. We provide an interactive calculator at www.U-Prevent.com that combines model predictions with relative treatment effects from trials to predict individual benefit from preventive treatment.

CONCLUSION:

Cardiovascular disease-free life expectancy and effects of lifelong prevention in terms of CVD-free life-years gained can be estimated for people with T2DM using readily available clinical characteristics. Predictions of individual-level treatment effects facilitate translation of trial results to individual patients.