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Based on machine learning algorithm established ultrasound evaluation model for the cardiac function of high-risk pregnant fetuses

Based on machine learning algorithm established ultrasound evaluation model for the cardiac function of high-risk pregnant fetuses

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000034182
Enrollment
Unknown
Registered
2020-06-27
Start date
2020-07-01
Completion date
Unknown
Last updated
2020-06-29

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

Conditions

high-risk pregnant

Interventions

Gold Standard:Neonatal pregnancy outcome
Index test:Ultrasound&#32
evaluation&#32
model&#32
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fetuses.

Sponsors

The Obstetrics and Gynecology Hospital of Fudan University
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
16 Years to 50 Years

Inclusion criteria

Inclusion criteria: 1. Prospective collection of single pregnancy pregnant women and live births within 24 hours after delivery from July 2020 to July 2023 in obstetrics and Gynecology Hospital affiliated to Fudan University; 2. The length of head and buttock measured by ultrasound during the last menstrual period or early pregnancy; 3. Complete prenatal ultrasound data (including growth ultrasound measurement, fetal echocardiography and neonatal echocardiography).

Exclusion criteria

Exclusion criteria: 1. The fetus has obvious structural malformations, chromosomal abnormalities or genetic syndromes, and decides not to continue the pregnancy; 2. A history of smoking, alcohol abuse or drug abuse in the first half of pregnancy or the first trimester; 3. A history of viral infection or teratogenic drug use in early pregnancy; 4. A history of exposure to toxic or harmful substances or large doses of radiation in the first half of pregnancy or the first trimester; 5. Pregnancy outcomes were not followed up for delivery outside the hospital.

Design outcomes

Primary

MeasureTime frame
ultrasound parameters;SEN, SPE, ACC, AUC of ROC;

Countries

China

Contacts

Public ContactChen Zhu

The Obstetrics and Gynecology Hospital of Fudan University

shallyzhuchen@163.com+86 021-33189900

Outcome results

None listed

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