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The most recent version of this article was published on 1 December 2006

Heart. Published Online First: 6 June 2006. doi:10.1136/hrt.2006.092668
Copyright © 2006 BMJ Publishing Group Ltd & British Cardiovascular Society

Editorials

The value of risk scoring

Jan Steffen Jürgensen 1*

1 Dept. of Nephrology and Medical Intensive Care, Charité, Campus Virchow Klinikum, Germany

* To whom correspondence should be addressed. E-mail: jan_steffen.juergensen{at}charite.de.

Accepted 21 May 2006


Abstract

According to Nobel laureate Nils Bohr predictions are difficult - especially about the future. What holds true for weather forecasts and financial markets applies to medical science and in particular to cardiovascular risk prediction. However, during the last decade the perception has evolved that the intensity of measures taken to tackle risk factors should be adjusted by the severity of risk. The joint European societies and other organizations adopted this concept in their guidelines. But if clinical decision making should be based upon a quantifiable risk, doctors must be provided with robust tools that allow a prediction. The most widely used method to assess the "global risk" is based on equations from the Framingham heart study and includes classical risk factors. In a recent issue of Heart Peter Brindle and colleagues published a systematic review that assessed the predictive power of the Framingham risk score, the extent to which it is used and the impact of calculating these scores on practice patterns of physicians (1). In brief, this thorough study revealed an extremely variable performance of the risk scores with under- prediction of the risk in a high risk population and over-prediction in a lower risk population. Further, there was no clear evidence that risk assessment improved primary prevention or health outcomes. The regrettably poor predictive value of the risk scores raises the question weather the scores should be abolished or improved and how improvement could be achieved.

Keywords: cardiovascular disease, prediction, prevention, risk scores, socioeconomic status


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