Identification of ultrasound and genetic variables for the development of algorithms able to optimize the outcome of assisted conception pregnancies and to manage the correlated obstetric risk

This PhD thesis takes in account the complex work already done in Fetal Medicine field in terms of personalized approach to the patient and tries to apply this model to Reproductive Medicine field in order to obtain a standardized flowchart of procedure. The overall framework is laided out in three different research lines. The first research line has been focused on the estimation of assisted conception's impact on pregnancies outcome at the time of first trimester screening ; in particular, it has been studied the impact of assisted reproduction technologies (ART) on the early pre-eclampsia risk . The second research line has been focused on ART population's features, in particular, on the estimation of genetic variables' impact on ovarian response within controlled ovarian stimulation (COS) protocols. The third line focused on two topics: on Reproductive Medicine side, the research aims to explore the potential role of some genetic and ultrasound information in a combined algorithm which can be used as a objective tool for personalizing the management of COS. protocols. On Prenatal Care side, it time to move from personalized risk prediction to prevention: it is here reported the preliminary phase of a double- blind placebo controlled III phase study named ASPRE study, one of the biggest multicentre trial ever thought in Obstetrics which is currently on going (and the candidate is working on) and aims to prevent pre-eclampsia in high risk pregnancies through the prophylactic use of low dose aspirin before 16 weeks