Rapid detection of health problems is often crucial to the successful management of what is uncovered. A new app that has been developed at King’s College London hopes to better identify women who are at risk of giving birth prematurely.
Across the world, it’s believed that 15 million babies are born preterm each year. Of these, over 1 million die of complications linked to their prematurity.
The app considers a number of factors to determine the risk of giving birth prematurely, including a history of preterm births or late miscarriages, the length of the cervix and the level of fetal fibronectin (a biomarker found in vaginal fluid).
The app uses an algorithm that mixes the gestation of previous pregnancies with both the length of the cervix and the amount of fetal fibronectin to determine a risk level. By using these measures, the app is able to detect high risk women before they showed any symptoms.
The results were published in the journal Ultrasound in Obstetrics & Gynecology, and showed that the app performed well as a predictive tool. It was especially effective when compared to each element of the test (the previous pregnancy, cervical length and fetal fibronectin) when taken in isolation.
Clinical use
The team hope that the app will prove to be valuable for clinicians wishing to improve their ability to manage the risk of premature delivery and to enable them to tailor management decisions accordingly.
Before that’s possible however, more work will be needed to evaluate the model and app in a clinical setting to test whether it actually has a positive impact on the pregnancy outcome of high risk women.
Professor Andrew Shennan, lead author who is Professor of Obstetrics at King’s College London and consultant obstetrician at Guy’s and St Thomas’ NHS Foundation Trust, 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.”
The QUiPP app is currently available from the Apple store.
QUiPP is available to download for free from the Apple store.
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