Understanding the risks of atherosclerotic cardiovascular disease (CVD) allows for better patient education and management. Multiple risk models have been validated in large patient populations and provide insights into the risks associated with CVD. When assessing such risks, we suggest using a model that predicts myocardial infarction, cardiovascular death, and/or cerebrovascular events. In this review, we analyze several risk models and stratify the risks associated with CVD. We suggest that appropriate profiling of patients at-risk of CVD will lead to better physician recognition and treatment of modifiable risk factors, appropriate application of ATP III treatment for hyperlipidemia, and achieving optimal blood pressure control.
Understanding the risks of atherosclerotic cardiovascular disease (CVD) allows for better patient education and management. Multiple risk models have been validated in large patient populations and provide insights into the risks associated with CVD. When assessing such risks, we suggest using a model that predicts myocardial infarction, cardiovascular death, and/or cerebrovascular events. In this review, we analyze several risk models and stratify the risks associated with CVD. We suggest that appropriate profiling of patients at-risk of CVD will lead to better physician recognition and treatment of modifiable risk factors, appropriate application of ATP III treatment for hyperlipidemia, and achieving optimal blood pressure control.
Carbone, R., Algahim, M., Rizzo, S., Monselise, A., Dart, R., Almassi, G., et al. (2014). Cardiovascular risk in patients without known cardiovascular disease. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES, 18(3), 365-373.
Cardiovascular risk in patients without known cardiovascular disease
RIZZO, Sergio;
2014-01-01
Abstract
Understanding the risks of atherosclerotic cardiovascular disease (CVD) allows for better patient education and management. Multiple risk models have been validated in large patient populations and provide insights into the risks associated with CVD. When assessing such risks, we suggest using a model that predicts myocardial infarction, cardiovascular death, and/or cerebrovascular events. In this review, we analyze several risk models and stratify the risks associated with CVD. We suggest that appropriate profiling of patients at-risk of CVD will lead to better physician recognition and treatment of modifiable risk factors, appropriate application of ATP III treatment for hyperlipidemia, and achieving optimal blood pressure control.
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