Prof Shaun Brennecke
University of Melbourne
Prof Brennecke occupies the University of Melbourne Dunbar Hooper Chair of Obstetrics and Gynaecology at the Royal Women’s Hospital.  He is also the Director of the Department of Maternal-Fetal Medicine and Head of the Pregnancy Research Centre at the Hospital. 

Prof Brennecke’s research interests focus on Maternal-Fetal Medicine, especially pre-eclampsia, fetal growth restriction, placental function, preterm labour, reproductive tissue stem cells, miscarriage, the endocrinology of human pregnancy and parturition, the assessment of fetal welfare, and factors influencing maternal and perinatal morbidity and mortality.  To date, he has published over 230 research papers on these topics.

ABSTRACT

THE PREDICTION OF PREECLAMPSIA
Prof Shaun Brennecke

Preeclampsia, which affects 3-5% of pregnant women, is the most common serious medical disorder of human pregnancy.  It is a major cause of maternal and perinatal morbidity and mortality throughout the world.  Its prediction (either before, or in the early months of pregnancy, or at a pre-clinical stage in later pregnancy) offers the possibility of significant improvement in both the maternal and perinatal clinical outcomes in pregnancies complicated by this disorder.  To date, however, partly because the precise aetiology and pathogenesis of preeclampsia remains uncertain, no single predictive test (e.g. clinical, biophysical, biochemical, genetic) has proven sufficiently effective for it to have gained widespread acceptance into clinical practice.  Instead, thus far, the most promising predictive models have involved the use of a combination of variables such as maternal risk factors, mean arterial blood pressure, uterine artery Doppler and various biomarkers.  Recent studies have also increasingly supported the stand-alone clinical utility of especially angiogenic biomarkers as predictive and diagnostic aids for preeclampsia. However, further prospective studies are required to detail the predictive characteristics of both multi-parametric models and biomarker approaches and to definitively determine their cost effectiveness in terms of improved maternal and perinatal outcomes.