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PeerJ. 2016 Feb 15;4:e1673. doi: 10.7717/peerj.1673. eCollection 2016.

A method to construct a points system to predict cardiovascular disease considering repeated measures of risk factors.

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Department of Clinical Medicine, Miguel Hernández University , San Juan de Alicante, Alicante , Spain.
Chair of Cardiovascular Risk, San Antonio Catholic University , Murcia, Murcia , Spain.
Department of Applied Mathematics, University of Alicante , San Vicente del Raspeig, Alicante , Spain.


Current predictive models for cardiovascular disease based on points systems use the baseline situation of the risk factors as independent variables. These models do not take into account the variability of the risk factors over time. Predictive models for other types of disease also exist that do consider the temporal variability of a single biological marker in addition to the baseline variables. However, due to their complexity these other models are not used in daily clinical practice. Bearing in mind the clinical relevance of these issues and that cardiovascular diseases are the leading cause of death worldwide we show the properties and viability of a new methodological alternative for constructing cardiovascular risk scores to make predictions of cardiovascular disease with repeated measures of the risk factors and retaining the simplicity of the points systems so often used in clinical practice (construction, statistical validation by simulation and explanation of potential utilization). We have also applied the system clinically upon a set of simulated data solely to help readers understand the procedure constructed.


Cardiovascular diseases; Cardiovascular models; Cohort studies; Risk factors

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