A Prediction Model of Essential Hypertension Based on Genetic and Environmental Risk Factors in Northern Han Chinese.

ABSTRACT: Background: Essential hypertension (EH) is a chronic disease of universal high prevalence and a well-established independent risk factor for cardiovascular and cerebrovascular events. The regulation of blood pressure is crucial for improving life quality and prognoses in patients with EH. Therefore, it is of important clinical significance to develop prediction models to recognize individuals with high risk for EH. Methods: In total, 965 subjects were recruited. Clinical parameters and genetic information, namely EH related SNPs were collected for each individual. Traditional statistic methods such as t-test, chi-square test and multi-variable logistic regression were applied to analyze baseline information. A machine learning method, mainly support vector machine (SVM), was

SUBMITTER: Li C 

PROVIDER: S-EPMC6643104 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature