Key result
CV risk scores perform well in matched populations, while adding novel markers mainly aids borderline reclassification.
Why the study?
What is the value and limitation of existing cardiovascular risk estimation systems?
What is the value and limitation of existing cardiovascular risk estimation systems?
Cardiovascular risk estimation systems are useful for guiding management, though they require calibration for different populations and further research is needed for young and old patients.
Atherosclerotic cardiovascular diseases (CVDs) are the biggest causes of death worldwide. In most people, CVD is the product of a number of causal risk factors. Several seemingly modest risk factors may, in combination, result in a much higher risk than an impressively raised single factor. For this reason, risk estimation systems have been developed to assist clinicians to assess the effects of risk factor combinations in planning management strategies. In this article, the performances of the major risk estimation systems are reviewed. Most perform usably well in populations that are similar to the one used to derive the system, and in other populations if calibrated to allow for different CVD mortality rates and different risk factor distributions. The effect of adding "new" risk factors to age, sex, smoking, lipid status, and blood pressure is usually small, but may help to appropriately reclassify some of those patients who are close to a treatment threshold to a more correct "treat/do not treat" category. Risk estimation in the young and old needs more research. Quantification of the hoped-for benefits of the multiple risk estimation approach in terms of improved outcomes is still needed. But, it is likely that the widespread use of such an approach will help to address the issues of both undertreatment and overtreatment.
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Cooney et al. (2009) conducted a review in Atherosclerotic cardiovascular diseases. Cardiovascular risk estimation systems was evaluated. Cardiovascular risk estimation systems perform well in similar populations, though adding new risk factors to traditional ones yields small effects that may help reclassify borderline patients.