Status:
UNKNOWN
Machine Learning From Fetal Flow Waveforms to Predict Adverse Perinatal Outcomes
Lead Sponsor:
Aga Khan University
Collaborating Sponsors:
Universitat Pompeu Fabra
Conditions:
Perinatal Mortality
Neonatal Morbidities
Eligibility:
FEMALE
Brief Summary
The aim of this study is to get a proof of concept for using a computational model of fetal haemodynamics, combined with machine learning based on Doppler patterns of the fetal cardiovascular, cerebra...
Detailed Description
Pakistan is one of the countries where stillbirth rate (43/1000 total births) and neonatal mortality rate (55/1000 live births) are among the highest in the world. The figures for perinatal mortality ...
Eligibility Criteria
Inclusion
- Pregnant woman coming to the ultrasound clinic between 22-34 weeks of gestation.
- Written informed consent
- Resident of the study area
Exclusion
- Multiple gestation
- Known congenital anomaly in the fetus or newborn
- Refusal for the ultrasound
- Poor echocardiographic images for Doppler acquisition
Key Trial Info
Start Date :
February 1 2018
Trial Type :
OBSERVATIONAL
Allocation :
ESTIMATED
End Date :
December 1 2018
Estimated Enrollment :
525 Patients enrolled
Trial Details
Trial ID
NCT03398551
Start Date
February 1 2018
End Date
December 1 2018
Last Update
January 12 2018
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