Cardiovascular Risk Scores: Great Tools... When Used by Good Physicians

Risk scores or risk scales are equations designed to determine the likelihood of an event occurring. In cardiology, cardiovascular risk scales are intended to calculate the probability of an individual’s experiencing a cardiovascular event over a period. Because of their widespread use, when we refer to risk scales, we are generally talking about scores that predict the occurrence of cardiovascular events related to atherosclerosis. But we must not forget that there are other scores dealing with other types of heart diseases. As the article in question states, (1) these scales are merely mathematical equations based on a series of variables that define risk much better than those same variables separately, as they consider the interactions that exist between their presence and intensity. The variables usually used should be accessible, pragmatic and, at the same time, valid for prediction. The accuracy of a risk equation in predicting the probability of an event occurring is usually calculated using a mathematical index called Harrell’s C-index. (2) Risk scores are very useful clinical tools, but we must be aware of their limitations before using them. Firstly, many important variables are not considered when designing a risk equation; therefore, they will have no effect in determining greater or lower risk. A clear example is seen in equations that include systolic blood pressure but not diastolic blood pressure for risk assessment. (3) What about a patient who has elevated diastolic pressure and controlled systolic pressure? Is his/her risk not increased? We believe this may be an example as easy to understand as the fact that body mass index is not yet included in many risk estimation scores. (3) Secondly, we must bear in mind that risk equations determine probability of experiencing a cardiovascular event in a population and not in a specific subject. Therefore, we can state that a certain probability will be fulfilled in a population of, for example, 1000 subjects, but we will most likely not be able to determine the exact probability of suffering a cardiovascular event in a specific subject. Further-