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Utilizing machine learning to predict unplanned cesarean delivery in parturients with labor analgesia

Utilizing machine learning to predict unplanned cesarean delivery in parturients with labor analgesia

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400083359
Enrollment
Unknown
Registered
2024-04-22
Start date
2024-05-01
Completion date
Unknown
Last updated
2024-04-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

unplanned cesarean

Interventions

Sponsors

Shenzhen Hospital of Southern Medical University
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to 45 Years

Inclusion criteria

Inclusion criteria: 1. primigravid women who voluntarily requested epidural labor analgesia treatment, aged 18-45 years old, with a single fetus, and whose fetal position was confirmed to be cephalic by the last obstetric ultrasound before delivery. 2. No contraindications to transvaginal delivery as assessed by the obstetrician and the mother voluntarily accepts a trial of transvaginal delivery. 3. No complications from intrathecal anesthesia operation

Exclusion criteria

Exclusion criteria: 1. Incomplete case information greater than 50% of the cases 2. Allergy to induction of labor or anesthesia drugs 3. Obvious cephalopelvic disproportion, genital tract deformity or combined genital tract infection and other contraindications to vaginal delivery.

Design outcomes

Primary

MeasureTime frame
age;height;BMI Pre-pregnancy;BMI at admission to labor;weight gain in pregnancy;pregestational diabetes mellitus;chronic hypertension;adjusted estimated fetal weight;adjusted head circumference;adjusted biparietal diameter;adjusted femur length;amniotic fluid index;Type of combined gestational hypertension;gestational diabetes mellitus;fetal gender;gestational age at adimission to labor;fetal head station at admission to labor;spontaneous onset of labor;cervical ripening;

Countries

China

Contacts

Public ContactQin Yangyang

Shenzhen Hospital of Southern Medical University

492175745@qq.com+86 180 3812 4624

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026