A new app called QUiPP could help doctors better identify the risk of premature birth. The researchers tested the application software developed at King's College London in two studies with womenDoctors monitored in maternity hospitalshave.
Every year around the world, 15 million babies are born prematurely, i.e. before the 37th week of pregnancy. Unfortunately, over a million of them die from complications. Medicine uses a number of factors to determine whether a woman is at risk of premature birth. This includes, among other things, a history of premature birth or late miscarriage. Two other influencing factors that doctors can consider are the length of the cervix and a biomarker in the vaginal fluid. The latter is known as fetal fibronectin. Doctors typically test the two factors from the 23rd week of pregnancy. Researchers have further developed the fetal fibronectin test, which can be used accurately from the first half of pregnancy.
So the developed app uses a mathematical algorithm. The software can better classify a woman's risk of premature birth. The first study focused primarily on women who are at high risk of premature birth. Usually this happens because of a previous pregnancy even though they didn't show any symptoms. The second study predicted the likelihood of early delivery in a group of women. These showed symptoms of early labor, which usually do not lead to an actual birth.
Study results
In the first study, researchers collected data from 1,249 women at high risk of preterm birth attending preterm monitoring clinics. They developed the model on the first 624 consecutive women and validated it on the following 625. The estimated probability of delivery before 30, 34, or 37 weeks of gestation and within two or four weeks of fetal fibronectin testing was calculated for each patient. In addition, scientists analyzed risk as a predictive test of the actual occurrence of each event.
In the second study, they collected data from 382 women who were at high risk. The researchers developed the model on the first 190 women. They also estimated the likelihood of premature delivery.
In bothStudiesThe scientists found that the app performs well as a forecaster and provides information far better than any other component. Accordingly, the authors conclude that physicians can use this software to improve assessment of the likelihood of premature delivery and potentially make better clinical decisions.
