Prediction of hypertension using traditional regression and machine learning models: A systematic review and meta-analysis.

ABSTRACT:

Objective

We aimed to identify existing hypertension risk prediction models developed using traditional regression-based or machine learning approaches and compare their predictive performance.

Methods

We systematically searched MEDLINE, EMBASE, Web of Science, Scopus, and the grey literature for studies predicting the risk of hypertension among the general adult population. Summary statistics from the individual studies were the C-statistic, and a random-effects meta-analysis was used to obtain pooled estimates. The predictive performance of pooled estimates was compared between traditional regression-based models and machine learning-based models. The potential sources of heterogeneity were assessed using meta-regression, and study quality was assessed using the PROBAST (P

SUBMITTER: Chowdhury MZI 

PROVIDER: S-EPMC8989291 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature