This study aimed to clarify the factors affecting the outcome of induction of labor (IOL) in a Japanese population and to develop a prediction model to assess the probability of emergent cesarean section (CS).Material and Methods:
By reviewing the medical records of 1029 women who underwent IOL, we compared the emergent CS rate during IOL among subgroups divided by parity and pre–labor risk, such as fetal anomaly and maternal complication. We created a prediction model to predict the CS rate during IOL focusing on 392 cases of nulliparous women with premature rupture of membrane (PROM). Six factors, including Bishop score (BS), gestational age, maternal body mass index (BMI), maternal height (MH) and birth weight (BW) were extracted and multivariable logistic regression analysis followed by cross–validation test were performed.Results:
The emergent CS rate was remarkably higher in the nulliparous group than in the multiparous group (17.6% vs 2.0%). In the nulliparous group, the high–risk group demonstrated a higher CS rate than the low–risk group (33.8% vs 15.6%). Multivariate analysis on nulliparous low–risk cases with PROM demonstrated significant odds ratios for emergent CS in BS, MH and BW. Cross–validation test selected these three factors as the best combination of parameters. The prediction formula was determined as follows: probability of CS (%) = (odds/1 + odds) * 100, odds = eX and X = 8.18 + 1.23 * BW (kg) − 7.74 * MH (m) − 0.253 * BS.Conclusion:
This study is the first to provide a prediction formula targeting an Asian population. Our model, which is specialized for nulliparous low–risk women could enable obstetricians to inform patients of the precise prospect of IOL outcome.