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New app helps identify risk of premature birth

A new app called QUiPP could help doctors predict the risk of preterm deliveries. Infants born before 37 weeks’ gestation are considered premature. Each year 15 million babies worldwide are born prematurely. More than one million die from the resulting birth injures and complications.

Doctors use several factors to determine the risk of premature birth in pregnant women. These include patient history, incidents of late miscarriages, cervix length and fetal fibronectin levels. Fetal fibronectin is a biomarker present in vaginal fluid. QUiPP uses an algorithm to combine data about the various factors to provide a more accurate classification of a woman’s risk of preterm birth.

Researchers at King’s College London in the United Kingdom developed the app and tested it in two separate studies involving high-risk pregnant women. The findings were published in Obstetrics & Gynecology journal. They showed that premature births were predicted more accurately with the app than by individually analyzing each factor.

According to the scientists, doctors can use QUiPP to better determine the probability of premature delivery and improve pregnancy outcomes by making more tailored clinical decisions regarding interventions. However, further clinical evaluation of the model’s practical application is needed.

Obstetrics professor Andrew Shennan, the study’s lead author, said, “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.”

The app is available for free download from the Apple store.

It is important to note that determining fault can be more complicated than it might seem. If your child was injured and you believe someone else is fully or partially to blame, contact Chalik & Chalik to learn more about your rights.

Birth Injury, Medical Malpractice