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Uterine Rupture clinical trials

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NCT ID: NCT05510310 Not yet recruiting - Clinical trials for Labor Onset and Length Abnormalities

Breast Stimulation vs. Low Dose Oxytocin Augmentation for Labor Induction

Start date: October 2022
Phase: Phase 1/Phase 2
Study type: Interventional

To find the preferred method of labor induction (birth augmentation) for women with a history of one prior cesarean section scar and in grandmultiparas, the difference in time interval from augmentation to delivery will be measured between breast stimulation vs. low-dose oxytocin administration in this prospective single-center randomized controlled trial.

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.