RT Journal
A1 Lloyd-Jones DM, Tian L
T1 Predicting cardiovascular risk: So what do we do now?
JF Archives of Internal Medicine
JO Archives of Internal Medicine
YR 2006
FD July 10
VO 166
IS 13
SP 1342
OP 1344
DO 10.1001/archinte.166.13.1342
UL http://dx.doi.org/10.1001/archinte.166.13.1342
AB 
Clinicians who see patients for primary care or for primary prevention of cardiovascular disease (CVD) are fortunate to have multivariable models1- 2 that can predict, with reasonable reliability, the absolute risk for future CVD events in large segments of the population.3- 4 Even in 2006, the absolute risk for future development of disease can be predicted for very few diseases, much less with the precision afforded by current CVD risk prediction models. These “risk scores” are a major advance over clinical risk prediction using relative risk estimates, and CVD prevention is one of the few areas in clinical practice to incorporate the use of absolute risk prediction into clinical practice guidelines.2 However, it has been widely recognized that CVD risk prediction models are imperfect. Appropriately, many investigators are attempting to improve CVD risk prediction to refine our ability to estimate absolute risk and to find those individuals who appear to be at low risk but are actually at high risk and merit preventive therapies. There is intense ongoing debate about which factors, if any, should be considered for addition to existing CVD risk prediction algorithms.