Cardiovascular Risk Prediction
Widening the Net
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Accurate assessment of cardiovascular risk in the clinical setting is important for appropriate management and counseling of patients and for identification of biological pathways. Classic models, including the Framingham risk score,1 have combined strong correlates of risk, such as age, with modifiable factors, such as blood pressure and lipids, into a single model. That structure has been retained by the most recent pooled cohort equations from the American College of Cardiology/American Heart Association guidelines.2 The article by Ambale-Venkatesh et al3 in the current issue uses a different framework for prediction and risk factor identification and results in an array of identified risk factors across multiple outcomes.
Article, see p 1092
Ambale-Venkatesh et al build on the strengths of MESA (Multi-Ethnic Study of Atherosclerosis), which collected extensive baseline and outcome data on the participants and included an ethnically diverse cohort by design. The MESA cohort has been a source of key insights in the use of markers, such as coronary calcium to predict risk,4 and the findings in MESA have been widely replicated in other cohorts. In this article, the authors took advantage of as much of the information as possible, examining 735 variables across a range of different domains, including …