Development

New App can Help Doctors Predict Risk of Preterm Birth

A new app called QUiPP could help doctors to better identify women at risk of giving birth prematurely. The app, developed at King's College London, was tested in two studies of high-risk women being monitored at ante-natal clinics. Worldwide 15 million babies are born preterm (before 37 weeks) each year and over a million of these die of prematurity-related complications. A number of factors are used to determine if a woman is at risk of giving birth prematurely, including a history of preterm births or late miscarriages. Two further factors which doctors can consider are the length of cervix and levels of a biomarker found in vaginal fluid known as fetal fibronectin, which are typically tested from 23 weeks. The investigators have further developed the fetal fibronectin test to be accurately used from the first half of pregnancy.

The app developed at King's uses an algorithm which combines the gestation of previous pregnancies and the length of the cervix with levels of fetal fibronectin to classify a woman's risk. The first study focused on women deemed to be a high risk of preterm birth, usually because of a previous early pregnancy, despite not showing any symptoms. The second study predicted the likelihood of early delivery in a group of women showing symptoms of early labour which often doesn't progress to real labour.

In the first study, published in the journal Ultrasound in Obstetrics & Gynecology, researchers collected data from 1,249 women at high risk for pre-term birth attending pre-term surveillance clinics. The model was developed on the first 624 consecutive women and validated on the subsequent 625. The estimated probability of delivery before 30, 34 or 37 weeks' gestation and within two or four weeks of testing for fetal fibronectin was calculated for each patient and analyzed as a predictive test for the actual occurrence of each event.

In the second study, also published in the journal Ultrasound in Obstetrics & Gynecology, data from 382 high-risk women was collected. The model was developed on the first 190 women and validated on the remaining 192. Probabilities of delivering early were estimated as above.

In both studies, the app was found to perform well as a predictive tool, and far better than each component (previous pregnancy, cervical length or fetal fibronectin) taken alone.

The authors conclude 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.

However, further work is needed to clinically evaluate the model in practice, and to ascertain whether interventions improve the pregnancy outcome for women identified as high risk by the app.

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."

QUiPP is available to download for free from the Apple store.

Most Popular Now

Smartphone Apps not so Smart at Hel…

You might not want to depend on your smartphone app alone to help you avoid or achieve pregnancy, say the authors of a new study. A review of nearly 100 fertility awarene...

Read more

eHealth Projects - Research and Inn…

What have the best brains of Europe come up with to improve health and wellbeing with the help of Information and Communication Technology (ICT)? This report offers an ...

Read more

Philips and Spanish Hospital Campus…

Royal Philips (NYSE: PHG, AEX: PHIA) has announced the successful start of a long-term strategic partnership with Servicio Andaluz de Salud (Andalusian Health Service, Sp...

Read more

Artificial Intelligence may Aid in …

Machine learning is a type of artificial intelligence that allows computer programs to learn when exposed to new data without being programmed. Now, researchers in The Ne...

Read more

Your Wearable Devices Reveal Your P…

Wearable devices can give away your passwords, according to new research. In the paper "Friend or Foe?: Your Wearable Devices Reveal Your Personal PIN" scientists from Bi...

Read more

Electronic Tablets Speed Stroke Car…

A clinical trial testing mobile videoconferencing as a means for physicians to diagnose stroke patients while they're being transported to the hospital has found that a t...

Read more

Can a Computer Game Train Your Brai…

That's the question Drexel University researchers hope to answer with one of two new studies launching this month. They have developed a computer game and smartphone app ...

Read more

Welch Allyn and Patientrack Collabo…

A national focus on reducing avoidable patient harm in NHS hospitals is to benefit from a new collaboration between two vital signs monitoring and technology specialists...

Read more

Philips Teams Up with Visiopharm to…

Royal Philips (NYSE: PHG, AEX: PHIA) has signed a licensing agreement with Visiopharm to offer their breast cancer panel software algorithms [1] with Philips IntelliSite ...

Read more

Tackling Youth Obesity by Playing G…

Imagine a companion who is able to constantly motivate you, actively encourages you and changes your bad habits into healthy ones. A companion who is always present and w...

Read more

'Big Data' Study Discovers Earliest…

Scientists at the Montreal Neurological Institute and Hospital have used a powerful tool to better understand the progression of late-onset Alzheimer's disease (LOAD), id...

Read more

A 'Big Data' Approach to Developing…

Scientists are starting to accumulate huge datasets on which genes mutate during cancer, allowing for a more systematic approach to "precision medicine." In a study publi...

Read more

Digest Newsletter

Subscribe to our weekly Newsletter and stay updated on the latest eHealth News. Subscribe now, it's free!
© eHealthNews.eu 2006 - 2016