Evaluating CMR
Assessing CVD Risk: Traditional Approaches
Limitations
- 1Key Points (1 page)
- 2Predicting CVD Risk (1 page)
- 3Applicability of Prediction Models to Different Populations (2 pages)
- 4Limited Risk Prediction Models in Women (1 page)
- 5Exclusion of Subjects With Type 2 Diabetes (2 pages)
- 6Exclusion of Potential Risk Factors in Prediction Equations (1 page)
- 7Endpoints Heterogeneity (1 page)
- 8References (1 page)
Predicting CVD Risk
Over the last few years, the estimation of global coronary and cardiovascular risk is a topic that has received considerable attention, with the focus being placed on prevention of cardiovascular disease (CVD). Numerous epidemiological studies (1, 2) have developed several risk prediction models to identify individuals at high risk of coronary heart disease (CHD) or CVD. Among these models, the Framingham Heart Study (1), the PROspective CArdiovascular Münster (PROCAM) study (2), the Systematic COronary Risk Evaluation (SCORE) project (3), the United Kingdom Prospective Diabetes Study (UKPDS) (4), and the Italian CUORE project (5) have generated well-known predictive equations derived from large American and European prospective studies. However, these risk prediction models differ significantly with regards to the ethnic background of populations studied, the limited availability of data in women, the risk factors incorporated into the model, and the CVD endpoints considered. In addition, while these risk prediction tools are useful for evaluating an individual’s CHD risk in clinical practice, they do have limitations that must be taken into account.

The Concept of CMR
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