Maternal preterm birth prediction in the United States: a case-control database study.

ABSTRACT:

Background

Preterm birth is serious public health worldwide, and early prediction of preterm birth in pregnant women may provide assistance for timely intervention and reduction of preterm birth. This study aimed to develop a preterm birth prediction model that is readily available and convenient for clinical application.

Methods

Data used in this case-control study were extracted from the National Vital Statistics System (NVSS) database between 2018 and 2019. Univariate and multivariate logistic regression analyses were utilized to find factors associated with preterm birth. Odds ratio (OR) and 95% confidence interval (CI) were used as effect measures. The area under the curve (AUC), accuracy, sensitivity, and specificity were utilized as model performance evaluation metric

SUBMITTER: Li Y 

PROVIDER: S-EPMC9472432 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature