Prediction of Maternal Hemorrhage Using Machine Learning: Retrospective Cohort Study.

ABSTRACT:

Background

Postpartum hemorrhage remains one of the largest causes of maternal morbidity and mortality in the United States.

Objective

The aim of this paper is to use machine learning techniques to identify patients at risk for postpartum hemorrhage at obstetric delivery.

Methods

Women aged 18 to 55 years delivering at a major academic center from July 2013 to October 2018 were included for analysis (N=30,867). A total of 497 variables were collected from the electronic medical record including the following: demographic information; obstetric, medical, surgical, and family history; vital signs; laboratory results; labor medication exposures; and delivery outcomes. Postpartum hemorrhage was defined as a blood loss of ≥1000 mL at the time of delivery, regardless of del

SUBMITTER: Westcott JM 

PROVIDER: S-EPMC9345059 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature