NCT05399979

Fetal Heart Rate Changes and Labor Neuraxial Analgesia: a Machine Learning Approach

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 1,077 (actual)
• Sponsor: Augusta University · Academic / Other
• Sex: Female
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

This study aims to perform statistical inference and prediction of changes in fetal heart rate during active labor in healthy pregnant women by comparing three different machine learning methods

Detailed description

Purpose: This study aims to perform statistical inference and prediction of changes in fetal heart rate during active labor in healthy pregnant women by comparing three different machine learning methods. Methods: A retrospective analysis of 1077 healthy laboring parturients receiving neuraxial analgesia was conducted. We compared a principal components regression model with treebased random forest, ridge regression, multiple regression, a general additive model, and elastic net in terms of prediction accuracy and interpretability for inference purposes.

Conditions

• Fetal Bradycardia

Interventions

Type	Name	Description
PROCEDURE	Labor Neuraxial Analgesia	Labor Neuraxial Analgesia

Timeline

• Start date: 2021-06-09
• Primary completion: 2022-05-05
• Completion: 2022-05-05
• First posted: 2022-06-01
• Last updated: 2022-06-03

Locations

1 site across 1 country: United States