Fetal Heart Rate Changes and Labor Neuraxial Analgesia: a Machine Learning Approach
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,077
- 试验地点
- 1
- 主要终点
- fetal bradycardia
研究概览
简要总结
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
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 是
入选标准
- •Older than 18 years
- •Pregnancy requiring labor analgesia
- •Active labor
- •Request of neuraxial analgesia per patient and/or obstetrician
- •Received combined spinal-epidural technique
排除标准
- •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
结局指标
主要结局
fetal bradycardia
时间窗: 15 minutes
fetal heart rate under 120 lpm for more than 10 minutes
次要结局
未报告次要终点
研究者
Efrain Riveros Perez, MD
Principal Investigator
Augusta University