Cardiovascular risk assessment - From individual risk prediction to estimation of global risk and change in risk in the population

被引:46
作者
Batsis, John A. [2 ,3 ]
Lopez-Jimenez, Francisco [1 ]
机构
[1] Mayo Clin, Coll Med, Dept Med, Div Cardiovasc Dis, Rochester, MN 55905 USA
[2] Dartmouth Med Sch, Hanover, NH 03755 USA
[3] Dartmouth Hitchcock Med Ctr, Dept Med, Gen Internal Med Sect, Lebanon, NH 03756 USA
关键词
CORONARY-HEART-DISEASE; C-REACTIVE PROTEIN; FOLLOW-UP; MYOCARDIAL-INFARCTION; BARIATRIC SURGERY; FRAMINGHAM SCORE; 10-YEAR RISK; LARGE COHORT; TRENDS; MORTALITY;
D O I
10.1186/1741-7015-8-29
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
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页数:6
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