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

ABSTRACT:

Background

Cardiovascular 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.

Method

The exact definition of and the event types included in the predicted outcomes of four widely used CVD risk prediction models (ATP-III, Framingham (FRS), Pooled Cohort Equations (PCE) and SCORE) was determined according to ICD-10 codes. The models w

SUBMITTER: Lagerweij GR 

PROVIDER: S-EPMC6326414 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature