Uterine Rupture Gravid clinical trials

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Phase 2: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase 3: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase 4: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.

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NCT ID: NCT03576950 Not yet recruiting - Clinical trials for Uterine Rupture Gravid

Uterine Rupture International Data Acquisition

URIDA

Start date: September 2021
Phase:
Study type: Observational

Uterine rupture represents an uncommon event: it is is a life-threatening obstetric complication with high maternal and perinatal morbidity and mortality. Indeed, uterine rupture may cause catastrophic maternal and fetal complications (uterine hemorrhage, hysterectomy with consequent fertility loss, maternal and fetal death or cerebral palsy) which are hardly acceptable within the context of a natural event such as birth. Uterine rupture can occur during pregnancy, early in labor or following a prolonged labor, most frequently near or at term and, rarely, during early to mid-pregnancy. Its prevalence ranges between 0.006% for women without previous cesarean section (CS) in the western countries, to 25% for women with obstructed labor in African countries. Pregnancy after myomectomy or CS, vaginal delivery after cesarean sections (VBACs) and vaginal delivery after myomectomy are potentially "at risk" of uterine rupture. Despite uterine rupture is widely considered a life-threatening condition, so far most of published data refer to case reports or very small case series. In this scenario, the "Uterine Rupture International Data Acquisition" study group would like to collect a large number of events, in order to identify the potential risk factors among different populations through a multivariate analysis.