Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT05399979 |
Other study ID # |
1567908 |
Secondary ID |
|
Status |
Completed |
Phase |
|
First received |
|
Last updated |
|
Start date |
June 9, 2021 |
Est. completion date |
May 5, 2022 |
Study information
Verified date |
June 2022 |
Source |
Augusta University |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial 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
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.