Predicting Admission to Neonatal Care Unit at Mid-Pregnancy and Delivery Using Data from a General Obstetric Population.

Objectives: Development and validation of risk prediction models at mid-pregnancy and delivery to predict admission to the neonatal care unit.

Methods: We used data from all singleton deliveries at Cork University Maternity Hospital (CUMH), Ireland during 2019. Admission to the neonatal care unit was assumed if length of stay in the unit was > 24 h.

Bimetallic catalyst system for the degradation of PCBs in sediments.

In this paper, we report the successful application of a patent-pending reduced bimetallic nanoparticle catalytic system developed for the remediation of polychlorinated biphenyl (PCB)-contaminated sediment and aquatic media. The formation of bimetallic nanoparticles associated with the granular activated carbon (GAC) were confirmed by high-resolution transmission electron microscopy. X-ray photoelectron spectroscopy showed the presence of the bimetallic matrix in reduced, albeit mixed, states.

Identifying the needs of women following a severe postpartum hemorrhage.

Introduction: Childbirth is a unique experience for women. In Ireland, major obstetric hemorrhage (MOH) is the most frequently reported severe maternal morbidity (SMM) with an incidence of 3.27 per 1000 maternities.

Predicting perineal trauma during childbirth using data from a general obstetric population.

Background: Perineal trauma is a common complication of childbirth and can have serious impacts on long-term health. Few studies have examined the combined effect of multiple risk factors. We developed and internally validated a risk prediction model to predict third and fourth degree perineal tears using data from a general obstetric population.