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Pilot implementation of first trimester pre-eclampsia screening.

Description 
Pre-eclampsia is a significant cause of maternal and perinatal morbidity and mortality around the world. Prediction of pre-eclampsia has been traditionally done using risk-factor-based checklists. While simple, this approach only identifies 30% of the individuals who will later develop pre-eclampsia. A better approach is to use a multimarker algorithm that combines maternal characteristics, medical history, blood pressure measurement, ultrasound parameters, and serum biomarkers at 11-14 weeks of pregnancy (at the time of the routine 11-14 weeks ultrasound). This approach, using the widely validated Fetal Medicine Foundation algorithm, allows for individual risk calculation and detects about 80% of pregnancies that will need delivery before 37 weeks because of pre-eclampsia (https://fetalmedicine.org/research/assess/preeclampsia/first-trimester). Accurate risk stratification is important because, among high-risk patients, aspirin is highly effective, preventing >65% of cases of preterm pre-eclampsia and 90% of the very early cases (<32 weeks). This test is offered by many private clinics, but is not routinely done in public hospitals in Victoria. We are in the process of implementing combined early pre-eclampsia screening at 11-14 weeks at Monash Health, with plans to expand it to a statewide program. This project will involve auditing the implementation/feasibility and the outcomes of first-trimester screening program for pre-eclampsia at Monash Health and in Victoria.
Essential criteria: 
Minimum entry requirements can be found here: https://www.monash.edu/admissions/entry-requirements/minimum
Keywords 
Pre-eclampsia, prediction, screening, early pregnancy, personalised medicine.
School 
School of Clinical Sciences at Monash Health / Hudson Institute of Medical Research » Obstetrics and Gynaceology
Available options 
PhD/Doctorate
Time commitment 
Full-time
Part-time
Top-up scholarship funding available 
No
Physical location 
Monash Clayton Campus
Co-supervisors 
Prof 
Zhong Lu
Prof 
Beena Kumar

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