Worldwide 15 million babies are born before 37 weeks (preterm) each year. Over a million of these die of prematurity-related complications. A number of factors are used to determine a woman at risk for premature birth, including previous preterm births or late miscarriages. Two other factors to be considered are the length of cervix and levels of a vaginal fluid biomarker known as fetal fibronectin, if tested from 23 weeks onward.

Investigators have now developed a fetal fibronectin test that can be accurately used in the first half of pregnancy.

The app developed at King's uses an algorithm combining gestation of previous pregnancies and cervix length and levels of fetal fibronectin to classify a woman's risk. The first study focused on women at high risk of preterm birth, because of a previous early pregnancy — without showing any symptoms. The second study predicted likelihood of early delivery in women with symptoms of early labour — which often didn't progress to real labour.

In the first study, published in the journal Ultrasound in Obstetrics & Gynecology1, 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 same issue of the journal Ultrasound in Obstetrics & Gynecology2, 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 single component (previous pregnancy, cervical length or fetal fibronectin) alone.

The authors feel the app can help clinicians improve estimation of premature delivery (before 34 weeks' gestation or within two weeks of the fetal fibronectin test). However, further clinical evaluation is needed.

Professor Andrew Shennan, lead author, Professor of Obstetrics at King's College London and consultant obstetrician at Guy's and St Thomas' NHS Foundation Trust, adds: "Despite advances in prenatal care, the rate of preterm birth has never been higher in recent years. In the US and UK, doctors need reliable ways to predict whether a woman is at risk of giving birth early. It can be difficult to accurately assess a woman's risk, given many women with symptoms of preterm labour do not 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 'higher risk' women to hospital, prescribe steroids or offer other treatments to prevent an early birth."

QUiPP is free to download from Apple.

Abstract1: Development and validation of a tool incorporating cervical length and quantitative fetal fibronectin to predict spontaneous preterm birth in asymptomatic high-risk women

Objective
To develop a predictive tool for spontaneous preterm birth (sPTB) in asymptomatic high-risk women that includes quantification of fetal fibronectin (fFN) along with cervical length (CL) measurement and other clinical factors.

Methods
Data were analyzed that had been collected prospectively from 1249 women at high risk for sPTB attending preterm surveillance clinics. Clinicians were blinded to quantitative measurements of fFN (qfFN), although they were aware of qualitative fFN results. Parametric survival models for sPTB, with time-updated covariates, were developed and the best was selected using the Akaike and Bayesian information criteria. The model was developed on the first 624 consecutive women and validated on the subsequent 625. Fractional polynomials were used to accommodate possible non-linear effects of qfFN and CL. The estimated probability of delivery before 30, 34 or 37 weeks' gestation and within 2 or 4 weeks of testing was calculated for each patient and analyzed as a predictive test for the actual occurrence of each event. Predictive statistics were calculated to compare training and validation sets.

Results
The final model that was selected used a log-normal survival curve with CL, √qfFN and previous sPTB/preterm prelabor rupture of membranes as predictors. Predictive statistics were similar for training and validation sets. Areas under the receiver–operating characteristics curves ranged from 0.77 to 0.99, indicating accurate prediction across all five delivery outcomes.

Conclusions
sPTB in high-risk asymptomatic women can be predicted accurately using a model combining qfFN and CL, which supersedes the single-threshold fFN test, demographic information and obstetric history. This algorithm has been incorporated into an App (QUiPP) for widespread use. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

Abstract2: Development and validation of a tool incorporating cervical length and quantitative fetal fibronectin to predict spontaneous preterm birth in asymptomatic high-risk women

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Feb 3, 2016   Fetal Timeline   Maternal Timeline   News   News Archive   

Worldwide 15 million babies are born before 37 weeks (preterm) each year.
Over a million infants die of prematurity-related complications.
Image Credit: public domain