Cardiovascular risk assessment - From individual risk prediction to estimation of global risk and change in risk in the
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Cardiovascular risk assessment - From individual risk prediction to estimation of global risk and change in risk in the population Debate
John A Batsis1,3 and Francisco Lopez-Jimenez*2
Abstract Background: Cardiovascular disease is the most common cause of death and risk prediction formulae such as the Framingham Risk Score have been developed to easily identify patients at high risk that may require therapeutic interventions. Discussion: Using cardiovascular risk formulae at a population level to estimate and compare average cardiovascular risk among groups has been recently proposed as a way to facilitate surveillance of net cardiovascular risk and target public health interventions. Risk prediction formulas may help to compare interventions that cause effects of different magnitudes and directions in several cardiovascular risk factors, because these formulas assess the net change in risk using easily obtainable clinical variables. Because of conflicting data estimates of the incidence and prevalence of cardiovascular disease, risk prediction formulae may be a useful tool to estimate such risk at a population level. Summary: Although risk prediction formulae were intended on guiding clinicians to individualized therapy, they also can be used to ascertain trends at a population-level, particularly in situations where changes in different cardiovascular risk factors over time have different magnitudes and directions. The efficacy of interventions that are proposed to reduce cardiovascular risk impacting more than one risk factor can be well assessed by these means. Background Prediction of CV risk
As cardiovascular (CV) disease corresponds to the most common cause of death in the United States with estimates exceeding one million deaths annually [1], estimates of individual and population-based CV risk are of paramount importance. CV risk prediction formulae and tables are decision tools that allow the identification of patients at high risk of CV disease. These tools allow early interventions by providers to recommend lifestyle modification or drugs to control modifiable CV risk factors, including hypertension, diabetes, smoking, dyslipidemia and obesity. Several CV risk prediction formulae are used in clinical practice worldwide. In the United States, the modified Framingham Risk Score (FRS) is the most commonly used tool [2], and has been adapted for use in diverse * Correspondence: [email protected] 2
Division of Cardiovascular Diseases, Department of Medicine, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
Full list of author information is available at the end of the article
populations in other parts of the world. Other tools include the Prospective Cardiovascular Munster Heart Study (PROCAM) [3], the Systematic Coronary Risk Evaluation system (SCORE) [4], United Kingdom Prospective Diabetes Study (UKPDS) [5] tool for diabetics, the Reynolds Risk Score [6,7] and more recently, one which includes obesity as a variable (NHANES) [8]. The variables include
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