Fetal Heart Rate Changes and Labor Neuraxial Analgesia: a Machine Learning Approach
Study Details
Study Description
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
Condition or Disease | Intervention/Treatment | Phase |
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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.
Study Design
Outcome Measures
Primary Outcome Measures
- fetal bradycardia [15 minutes]
fetal heart rate under 120 lpm for more than 10 minutes
Eligibility Criteria
Criteria
Inclusion Criteria:
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Older than 18 years
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Pregnancy requiring labor analgesia
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Active labor
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Request of neuraxial analgesia per patient and/or obstetrician
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Received combined spinal-epidural technique
Exclusion Criteria:
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Uterine tachysystole before neuraxial analgesia.
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Baseline blood pressure <90/60 mmHg.
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Third trimester hemorrhage
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Eclampsia
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Allergies to local anesthetics or fentanyl.
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Maternal fever.
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Pruritus before performance of neuraxial analgesia
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | Augusta University Medical Center | Augusta | Georgia | United States | 30907 |
Sponsors and Collaborators
- Augusta University
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- 1567908