Fetal Bradycardia
Conditions
Brief 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.
Interventions
PROCEDURELabor Neuraxial Analgesia
Labor Neuraxial Analgesia
Sponsors
Augusta University
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| fetal bradycardia | 15 minutes | fetal heart rate under 120 lpm for more than 10 minutes |
Countries
United States
Outcome results
None listed