Interpretation of CVD risk predictions in clinical practice: Mission impossible?

摘要

BackgroundCardiovascular disease (CVD) risk prediction models are often used to identify individuals at high risk of CVD events. Providing preventive treatment to these individuals may then reduce the CVD burden at population level. However, different prediction models may predict different (sets of) CVD outcomes which may lead to variation in selection of high risk individuals. Here, it is investigated if the use of different prediction models may actually lead to different treatment recommendations in clinical practice.