A new app could help doctors predict risks of preterm birth

Researchers from King's College London have developed a mobile tool to help doctors better predict preterm birth dangers. The QUiPP app relies on gathering personal data, such as the state of a previous pregnancy, to anticipate a woman's chances of delivering a child before 37 weeks. Its algorithm also takes into account information about the cervix and fetal fibronectin, a vaginal fluid that doctors start testing in the first half of the typical 9-month term.

According to King's College London, QUiPP performed well as a predictive tool during two studies, one of which collected info from 1,250 women who were at high risk of giving birth before their due date. "The authors conclude," said the university in a news release, "that the app can be used by clinicians to improve the estimation of the probability of premature delivery (before 34 weeks' gestation or within two weeks of the fetal fibronectin test) and to potentially tailor clinical management decisions."

Still, researchers believe that the application, which is currently only available for iOS, needs to be further evaluated before it can become a trusted solution for detecting risks of preterm birth. "It can be difficult to accurately assess a woman's risk, given that many women who show symptoms of preterm labor do not go on to deliver early," says professor Andrew Sherman, who's leading the development of QUiPP.

"The more accurately we can predict her risk, the better we can manage a woman's pregnancy to ensure the safest possible birth for her and her baby, only intervening when necessary to admit these 'higher risk' women to hospital, prescribe steroids or offer other treatments to try to prevent an early birth," he added.