Researchers Develop New Tools to Predict Premature Birth, Neonatal Morbidity

Researchers Develop New Tools to Predict Premature Birth, Neonatal Morbidity Beth Smith Dr. Avinash Patil, a clinical assistant professor in the UArizona College of Medicine – Phoenix, led a research team that used progesterone metabolite levels combined with patient demographic and clinical data to predict significant neonatal morbidity, neonatal length of stay and risk for very preterm delivery. Today College of Medicine – Phoenixadult-1850223_1280-web.jpg A new study led by the College of Medicine – Phoenix allowed researchers to predict, with a high degree of certainty, women who were more likely to have a very preterm birth. Very preterm births – babies born before 32 weeks of pregnancy – often result in neonatal morbidity and mortality.HealthScience and TechnologyCollege of Medicine - Phoenix Media contact(s)Beth Smith College of Medicine – Phoenixbhsmith1@arizona.edu602-827-2676Researchers from the University of Arizona  College of Medicine – Phoenix and Indiana University School of Medicine have developed a new diagnostic tool to better predict the likelihood of premature birth and neonatal morbidity in the early stages of pregnancy, which may improve care and outcomes for both baby and mother.Premature birth affects one out of 10 women in the United States and can lead to multiple complications in newborns. Until now, there were limited tools available to predict preterm birth and no tools to predict neonatal morbidity.patil-web.jpg Dr. Avi...
Source: The University of Arizona: Health - Category: Universities & Medical Training Authors: Source Type: research