Literature review on prediction models for atherosclerotic cardiovascular diseases

Abstract

Introduction

Atherosclerotic Cardiovascular Diseases (ASCVD) is a major cause of death worldwide. The Framingham study has overestimated ASCVD risk in some populations, which has led to the concern that scores may be inappropriate for other populations. Thus, the development of prediction models for ASCVD has been meticulously studied.

Objectives

Past to modern predictive models were analyzed based on their general characteristics, models and outcomes of general characteristics, risk factors, and predictors through a systematic review of literature.

Methods

The literature searches were carried out with the literature databases PubMed and Google Scholar. This study reviewed the general characteristics, models and outcomes of the general characteristics, and general risk factors of the prediction models, and grouped the characteristics of the variable factors into the following three categories: those in the USA, those in other countries, and those in validation and calibration studies.

Results

The statistical analysis showed a trend from the logistic regression model to the Cox proportional hazards model in the USA, in other countries, and in the validation and calibration study.

The definition of the outcomes was expanded from CHD and not CHD to Hard CHD or CVD in the USA. In the studies on other countries, the outcomes were defined as ICD codes and the incidence of CVD or the death probabilities, and whether they were Hard CHD or CVD. In the validation and calibration study, the definition of the outcomes was expanded to ASCVD.

For the general risk factors of the prediction model, the simple cholesterol, was combined with the expanding variables such as DM, smoking, the family history, the HTN medication, statin therapy, and exercise.

Conclusion

The results of this study provide important baseline information for prediction models for ASCVD.