| Project Detail |
Early-onset foetal growth restriction <32 weeks’ gestation is a severe pregnancy disorder that affects an estimated 15,000 European pregnancies annually and puts the babies at risk of severe morbidity and mortality. The underlying mechanism of the disorder is placental insufficiency leading to failure to meet the foetal metabolic and respiratory demands (the first leading to the growth disorder, the latter leading to fetal demise). Birth of the foetus prevents further damage from the intrauterine environment, but exposes the neonate to the challenges of severe prematurity. When women are admitted to the hospital with this complication of pregnancy, the obstetrician monitors the progressive signs of placental insufficiency and decides to expedite birth when the risks of foetal demise outweigh the risks of prematurity. Currently, there is lacking evidence how to weigh all prognosticators in this balance, therefore it takes place in the black box of the obstetricians mind.
In FGR PODS (Fetal Growth Restriction Perinatal Outcome Decision Support), I aim to develop and validate a ground-breaking decision support tool that will aid the obstetrician with objectively determining the optimal timing of birth. The decision support tool will integrate a combination of foetal and maternal prognosticators, and can be implemented in electronic patient charts. Provided as freeware, centres that have implemented the tool will feed back pseudonymized patient data in order to continuously refine the model. Also, within FGR PODS, I will perform innovative analysis (including machine learning) of fetal heart rate signals and of serially measured biomarkers to pick up placental respiratory failure. These studies will further our understanding of the foetal pathophysiological mechanisms resulting from placental insufficiency and will potentially identify targets for therapeutic interventions. |
