Doctors in London have developed a smartphone app to help predict the risk of a pregnant woman going into premature labour.
The app, available for Apple products, combines standard measures of risk into a single prediction, setting out the risk a woman faces.
Its developers at King’s College, London, say they have tested it in two studies involving high risk women so far.
The app combines a woman’s history of pregnancy, the length of the cervix and levels of foetal fibronectin.
The first study involved some 1,249 women and the second involved 382 women.
The findings have been published in Ultrasound in Obstetrics & Gynecology.
The researchers say the app performed well and better than predictions based on the individual components.
Researcher Professor Andrew Shennan said: "Despite advances in prenatal care the rate of preterm birth has never been higher in recent years, including in the US and UK, so doctors need reliable ways of predicting whether a woman is at risk of giving birth early.
“It can be difficult to accurately assess a woman’s risk, given that many women who show symptoms of preterm labour do not go on to deliver early.
"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."
Kuhrt et al. Development and validation of a predictive tool for spontaneous preterm birth incorporating cervical length and quantitative fetal fibronectin in asymptomatic high-risk women. Ultrasound in Obstetrics & Gynecology February 2016; doi: 10.1002/uog.14894
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