Taqdees Iftikhar, Naila Qazi, Naushaba Malik, Nida Hamid, Nadia Gul, Razia Rauf.
Prediction of Successful Induction of Labour jointly using Bishop Score and Transvaginal Sonography in Primigravida Women in Pakistan.
Ann Pak Inst Med Sci Jan ;19(2):141-6.

Objective: To assess the diagnostic efficacy of the Bishop Score and Transvaginal Ultrasonography (TVS) in predicting successful labor induction in primigravida women in a peri-urban population in Islamabad. Additionally, the study aimed to evaluate the effectiveness of combining the predictions from both methods to enhance accuracy in predicting successful labor induction. Methodology: A prospective comparative study was conducted at the Departments of Obstetrics and Gynecology, Rawal Institute of Health Sciences, and Farooq Hospital, Islamabad, from December 2021 to December 2022. A total of 520 pregnant, primigravida women undergoing labor induction were included, and they were randomly divided into two groups for assessment using either the Bishop Score or Transvaginal ultrasonography. The outcome of interest was documented as the initiation of active labor within 24 hours. The efficacy of each method was validated separately and jointly, and the predictive accuracy of all three predictors was compared. Results: The two groups demonstrated that both TVS and the Bishop Score were individually effective at predicting successful labor induction (p<0.00001 for both methods). TVS outperformed the Bishop Score in several key predictive measures, such as accuracy and the F1 Score. However, combining predictions from both the Bishop Score and TVS significantly improved both positive and negative predictive values (by more than 10% for each metric), resulting in a more reliable prediction. Conclusion: Both the Bishop Score and TVS are effective methods for predicting successful labor induction in the peri-urban population of Islamabad, Pakistan. While TVS showed significant quantitative advantages over the Bishop Score, combining both predictors yielded even better performance, suggesting that using both methods together should be prioritized for prediction.

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