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

PeerJ

article

Antonio Palazón-Bru¹  Julio Antonio Carbayo-Herencia²  Maria Isabel Vigo³  Vicente Francisco Gil-Guillén¹ 

[1] Department of Clinical Medicine, Miguel Hernández University;Chair of Cardiovascular Risk, San Antonio Catholic University;Department of Applied Mathematics, University of Alicante

关键词: Cardiovascular diseases;    Cardiovascular models;    Risk factors;    Cohort studies;   

DOI  :  10.7717/peerj.1673

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

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.

【 授权许可】

CC BY