Association of Gastroesophageal Reflux Disease with Preterm Birth: Machine Learning Analysis.

ABSTRACT:

Background

This study used machine learning and population data for testing the associations of preterm birth with gastroesophageal reflux disease (GERD) and periodontitis.

Methods

Retrospective cohort data came from Korea National Health Insurance Service claims data for all women who aged 25-40 years and gave births for the first time as singleton pregnancy during 2015-2017 (405,586 women). The dependent variable was preterm birth during 2015-2017 and the independent variables were GERD (coded as no vs. yes) for each of the years 2002-2014, periodontitis (coded as no vs. yes) for each of the years 2002-2014, age (year) in 2014, socioeconomic status in 2014 measured by an insurance fee, and region (city) (coded as no vs. yes) in 2014. Random forest variable importance was a

SUBMITTER: Lee KS 

PROVIDER: S-EPMC8575763 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature