Value of Pre-Induction Cervical Fetal Fibronectin (FFN) Assessment as A Predictor of Succesful Vaginal Birth in Nulliparas Undergoing Labor Induction
Keywords:Labor induction, Cervical fibronectin, Vaginal delivery, Prediction
OBJECTIVE: To determine the value of pre-induction assessment of cervical FFN in the prediction of succesful vaginal birth within 24 hours post-sampling.
STUDY DESIGN: This was a prospective observational trial of nulliparous women undergoing labor induction. Inclusion criterias were: gestational age between 36 to 42 weeks, singleton cephalic presentation of the fetus, intact membrane and Bishop score <6. Pre-induction cervical ripening was performed by using 25 microgr intravaginal misoprostol (PGE1), repeated every four hours, up to a maximum dose
of three doses. Induction was subsequently continued by oxytocin and amniotomy. Prior to cervical ripening, FFN samples were collected by using steril speculum and analyzed by standard quantitative immunoassay.
RESULTS: A total number of 43 women met the inclusion criterias, of which 51.1% delivered vaginally within 24 hours of labor induction. There was no statistically significant difference in the rates of vaginal delivery betwen women with positive (84%) and negative (72.0%) FFN results (p=0.54), although more FFN positive cases were vaginally delivered. Sensitivity, specificity, positive and negative predictive values of FFN in predicting successful vaginal birth within 24 hours of labor induction were:0.44,0.67,0.83 and 0.24, respectively. There were no differences in any of the neonatal outcomes between FFN negative and positive groups. Indications of cesarean section did not differ among two groups.
CONCLUSION: In nulliparas undergoing pre-induction cervical ripening, positive FFN test prior to labor induction did not predict successful vaginal birth within 24 hours.
How to Cite
All the articles published in GORM are licensed with "Creative Commons Attribution 4.0 License (CC BY 4.0)". This license entitles all parties to copy, share and redistribute all the articles, data sets, figures and supplementary files published in this journal in data mining, search engines, web sites, blogs and other digital platforms under the condition of providing references.