Adapting cardiovascular risk prediction models to different populations: the need for recalibration.

The article discusses a study comparing different cardiovascular disease (CVD) risk prediction models and their implications for treatment recommendations. The study found that individuals with the same risk factor profile can receive different risk estimates depending on the algorithm used. The authors argue that this lack of concordance is a limitation of current risk prediction models and treatment approaches. They also highlight the importance of considering the background level of risk in different populations and the need for country-specific decisions and recommendations regarding screening strategies and treatment thresholds. [Extracted from the article]