Fixed risk factors at baseline versus variability of risk factors in predicting cardiovascular outcome

In our daily medical practice, we try to predict the risk of cardiovascular events for our patients. We recommend lifestyle changes and, if necessary, medication, based on the anticipated risk. However, some patients remain at risk, due to factors such as inadequate implementation of guideline-based recommendations, genetic susceptibility, or other issues. The concept of residual risk is still important in cardiology. The usual approach to predicting future risk is focused on the presence or absence of risk factors (such as smoking) or on the baseline magnitude of these factors (such as blood pressure or lipid level). The available prediction models usually ignore fluctuation or visit-to-visit variability of risk factors, probably as a result of a simplistic (and more applicable) approach, or difficulty obtaining data and defining variability