# name
An ultrasound prediction model for probability of vaginal delivery in induction of labor

# metadata.dc.description.abstract[].value
Objective: Our aim was (i) to evaluate a pre-induction ultrasound score for prediction of vaginal delivery and compare it with the Bishop score in term nulliparous women, and (ii) to formulate a prediction model to calculate probability of vaginal delivery for clinical use. Methods: Ninety-six nulliparous women between 36–41 weeks gestation were recruited. All subjects fulfilled the inclusion criteria of a live singleton pregnancy, vertex presentation, intact amniotic membrane, in the absence of active labor with no contraindication to vaginal delivery. The patients were assessed by our ultrasound score comprising of 3 cervical and 2 fetal head parameters. These parameters were fetal head position, fetal head - symphysis pubis distance relation, cervical length, funneling and posterior cervical angle. Each parameter was scored from 0–2, with a maximum score of 10. A second obstetrician blinded to the sonographic findings assessed the modified Bishop score. SPSS 20 was used for ROC curves plots and calculation of area under curve. Binary logistic regression model was prepared and probability of vaginal delivery for various scores was calculated. Results: Out of 91, 61 (67%) achieved active phase of labor and 54 (59%) had vaginal delivery. Our pelvic ultrasound score showed better sensitivity and specificity in comparison to the Bishop score. At a cut-off of ≥5, the ultrasound score showed sensitivity of 79.3%, specificity of 75.8%, whereas, the Bishop score showed sensitivity of 66.7% and specificity of 44.2%. Binary logistic regression model predicted 78.0% of the events correctly. Conclusion: Our study shows that “Garg ultrasound score” can predict success of induction of labor in nulliparous women. This proposed pelvic ultrasound score, if validated in larger multicenter studies, could help clinicians provide evidence-based counselling for predicting probability of vaginal delivery. This in turn, may allow women make a more informed decision before undergoing induction of labor.

# metadata.dc.relation.ispartof[].value
Journal of Perinatal Medicine, 2019, vol. 27, num.3, p. 161-168

# metadata.dc.source[].value
Articles publicats en revistes (Ciències Clíniques)

# metadata.dc.title[].value
An ultrasound prediction model for probability of vaginal delivery in induction of labor