A new study from the American Journal of Obstetrics & Gynecology proposes a new model of more accurately predicting whether a mother will give birth naturally or through a C-section. They hope this model can be standardized and used globally to improve the decision to choose C-section deliveries during labor.
Babies born into the world can come in through one of two ways: naturally, through a vaginal birth, or through surgical delivery by Cesarean section (C-section, where the abdomen is cut to remove the baby). The decision of choosing which method is used is usually left to the doctor and requires the consideration of many factors (number of children given birth to, size of the fetus, position of the fetus, length of labor, etc). C-sections are often associated with more risks, such as morbidity to the mother or fetus, and so the decision to carry out this form of child birth needs to be critically assessed. A woman may know in advance if she needs a C-section, but often, C-sections are unplanned and the decision to carry one out is done at the time of labor. In the present day, there are a few methods of predicting whether a C-section will be required to give birth (such as ultrasounds to observe fetal positioning), but none are effective in accurately predicting the need for C-section.
A new study in the American Journal of Obstetrics & Gynecology proposed an original model of predicting the likelihood of the need for C-section in women in the first stage of labor. 122 women in labor with their first child were assessed. Researchers measured maternal characteristics (like body mass index, age, cervix dilation), and clinical and ultrasound observations (like fetal position, distance between fetus and perineum, and size of fetus head swelling due to cervical pressure), as predictors of C-section. The characteristics were pooled and graphed against the outcome of a vaginal birth in order to create a risk score for each woman. Results showed that vaginal birth could be predicted based on the positioning of a specific risk score above or below the median of all scores. Women with risk scores above the median score were 10 times more likely to have a vaginal birth than those with risk scores below the median.
Researchers hope that these results can be used to create a universal assessment system to predict the chances of a C-section birth. A quicker and more accurate prediction of a C-section birth would help in earlier detection for its need and more time for its preparation, helping to reduce the negative risks commonly associated with C-section deliveries.
Reference: Eggeebo TM, Wilhelm-Benartzi C, Hassam WA, Usman S, Salvesen KA, Lees CC. A model to predict vaginal delivery in nulliparous women based on maternal characteristics and intrapartum ultrasound. Obstetrics: Am J Obstet Gynecol 2015;213:362.e1-
Written by Alexandra Lostun, BSc