BackgroundBy increased concerns about the accuracy of the traditional methods to predict outcomes after induction of labor, developing new standards has a great clinical importance. Here, we compared the predictive value of translabial ultrasound measurements with Bishop Score to determine the suitability of induction of labor.MethodsA homogenous population of primigravid women was recruited. Induction of labor was performed with low-dose infusion of oxytocin. Translabial ultrasound and assessment of Bishop Score were performed by two different obstetricians. Receiver–operating characteristics curves were obtained to measure area under curve and subsequently, test sensitivity of each method.ResultsOne hundred women entered the investigation. Maternal body mass index was significantly higher among candidates of Cesarean section (P: 0.02). Maternal age and fetus weight, gender and occiput position were not determinants of outcomes of induction of labor. Cervical length and fetal head-pubis symphysis distance measured by translabial ultrasound had a test sensitivity of 90 and 88 %, respectively which were slightly higher than sensitivity of Bishop score (84 %).ConclusionThis study demonstrates that translabial measurements can be a suitable alternative method to monitor labor progress with an admissible predictive value compared with Bishop Score. It is a non-invasive method which provides valuable objective measurements and can be better accepted by women when considering the painful process which is required in evaluating Bishop Score.

The fast growth of social networks and their privacy requirements in recent years, has lead to increasing difficulty in obtaining complete topology of these networks. However, diffusion information over these networks is available and many algorithms have been proposed to infer the underlying networks by using this information. The previously proposed algorithms only focus on inferring more links and do not pay attention to the important characteristics of the underlying social networks In this paper, we propose a novel algorithm, called DANI, to infer the underlying network structure while preserving its properties by using the diffusion information. Moreover, the running time of the proposed method is considerably lower than the previous methods. We applied the proposed method to both real and synthetic networks. The experimental results showed that DANI has higher accuracy and lower run time compared to well-known network inference methods.

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Objectives: Determining the necessity of cesarean section (C/S) due to failure of induction of labor (IOL) is essential to avoid fetus distress. In this study, the performance of the Bishop score and trans-vaginal ultrasound measurements were compared to predict successful IOL, and the most useful cutoff points were estimated. Methods: Nulliparous women with gestation age of > 37 weeks with a live fetus in cephalic presentation were invited to participate in this study. Bishop score was assessed by digital examination, and trans-vaginal ultrasound was used to measure cervical length. Trans-abdominal ultrasound was utilized to determine the fetal head position. Results: One hundred women entered the study. Multiple regression analysis revealed that the Bishop score and cervical length had a reliable predictive value in determining successful IOL. The cutoff points for predicting successful induction were 16 mm for cervical length and 5 for the Bishop score, using receiver operating characteristic curves (ROC). Both cervical length and Bishop score were good predictors for vaginal delivery (sensitivity and specificity of 85% and 67%, respectively for cervical length; and 84% and 70%, respectively for Bishop score). Conclusions: Cervical length is a good predictor of successful IOL. Considering the painful process of digital exam, implementing trans-vaginal ultrasound is preferred.