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Deriving a prediction model for emergency cesarean delivery following induction of labor in singleton term
Manisha Dorwal1, Garima Yadav1, Pratibha Singh1
1Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, India.
Objectives:
To derive a prediction model combining various clinical factors associated with increased risk of emergency cesarean section following induction of labor in women with unfavorable cervix.
Methods:
All women with singleton term pregnancies undergoing induction of labor and fulfilling inclusion criteria were included in this cross-sectional study after supplying consent. Women with a Bishop score of 6 or less were induced with dinoprostone gel. Multiple regression analysis was used to find the most significant independent predictive factors and these factors were used to develop the predictive model and calculator.
Results:
After multiple logistic regression, risk of emergency cesarean after induction of labor was significantly associated with the following variables: height (adjusted odds ratio [aOR] 0.955, P = 0.033), nulliparity (aOR 3.987, P < 0.001), closed cervix (aOR 2.030, P = 0.030), fetal station -3 above ischial spine (aOR 2.719, P = 0.043), firm or medium cervical consistency (aOR 2.028, P = 0.004), cervical length 3 cm or longer (aOR 3.090, P = 0.015), posterior cervix (aOR 2.112, P = 0.002).
Conclusion:
Use of a prediction model would help to reduce the number of emergency cesarean sections secondary to unsuccessful inductions and help in the reduction of maternal and perinatal morbidity.
