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

Augusta University

Status: Completed

Conditions: Fetal Bradycardia

Treatments: Procedure: Labor Neuraxial Analgesia

Study type: Observational

Funder types: Other

Identifiers

NCT05399979

1567908

Details and patient eligibility

About

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

Full 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.

Enrollment: 1,077 patients

Sex: Female

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Older than 18 years
• Pregnancy requiring labor analgesia
• Active labor
• Request of neuraxial analgesia per patient and/or obstetrician
• Received combined spinal-epidural technique

Exclusion criteria

• Uterine tachysystole before neuraxial analgesia.
• Baseline blood pressure <90/60 mmHg.
• Third trimester hemorrhage
• Eclampsia
• Allergies to local anesthetics or fentanyl.
• Maternal fever.
• Pruritus before performance of neuraxial analgesia