Variables that predict the success of labor induction

Bueno, Beatriz Piccolotto Siqueira; Sanfrutos, Luis; Salazar, Francisco; pgrave;rez-medina, Tirso; Engels, Virginia; Archilla, Beatriz; Izquierdo, F.; Bajo, Josgrave;

doi:10.1080/j.0001-6349.2005.00881.x

Cited by 15 publications

(13 citation statements)

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“…Given the mixed results established by the abovementioned studies, other researchers created models incorporating sonographic and digital elements, as well as other maternal features, in an effort to better predict IOL success (Table ). With these components, the different studies produced new scores or algorithms, allowing one to divide patients into subgroups with different labor induction prognoses . Although these models are more complex with several variables to be accounted for, their predictive values appear superior to any factor used alone.…”

Section: Resultsmentioning

confidence: 99%

The role of sonographic cervical length in labor induction at term

Papillon-Smith

Abenhaim

2014

J of Clinical Ultrasound

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The purpose of this study is to review the literature examining the role of ultrasound in the induction of labor. Databases including Ovid, PubMed, Web of Science, Google Scholar, and UpToDate were searched and current guidelines from the SOGC, the ACOG, the RCOG, and the RANZCOG were reviewed. Although studies have not demonstrated the superiority of cervical sonography to the Bishop score, the evidence indicates that sonography could be useful in planning induction of labor, significantly reducing the need for cervical ripening agents. A more comprehensive method integrating both sonography and digital exam may be more appropriate.

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Section: Resultsmentioning

confidence: 99%

The role of sonographic cervical length in labor induction at term

Papillon-Smith

Abenhaim

2014

J of Clinical Ultrasound

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“…The classification and regression tree analysis is a decision tree methodology that has the ability to efficiently segment populations into meaningful subgroups, whose members share similar characteristics that help determine participation in the healthrelated behavior as a basis for targeted interventions. As we described in previous publications, 15 we obtained different cutoff points, that best predict the success of labor induction, for cervical length, Bishop Score and parity. Integrating the significant variables of logistic regression, we obtain a flow chart (Figure 1), where we can know the prognosis of induction for each patient, following its placement in the flow chart.…”

Section: Discussionmentioning

confidence: 98%

The labor induction: integrated clinical and sonographic variables that predict the outcome

et al. 2006

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Objective: To analyze the clinical and sonographic variables that predicts the success of labor induction. Study design:We studied the Bishop score, cervical length and parity in 196 pregnant women in the prediction of successful vaginal delivery within 24 h of induction. Logistic regression and segmentation analysis were performed.Results: Cervical length (odds ratio (OR) 1.089, P<0.001), Bishop score (OR 0.751, P ¼ 0.001) and parity (OR 4.7, P<0.001) predict the success of labor induction. In a global analysis of the variables studied, the best statistic sequence that predicts the labor induction was found when we introduced parity in the first place. The success of labor induction in nulliparous was 50.8 and 83.3% in multiparous women (P ¼ 0.0001).Conclusions: Cervical length, Bishop score and parity, integrated in a flow chart, provide independent prediction of vaginal delivery within 24 h of induction.

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“…This method is subjective and demonstrates intra-and interobserver variability. Transvaginal ultrasound has been proposed as a better predictor of the success of labor compared with the Bishop score [2][3][4][5]. However, it has also been suggested that transvaginal ultrasonographic measurement of cervical length does not add any additional benefit to the prediction of cervical inducibility obtained by the Bishop score [6,7].…”

Section: Introductionmentioning

confidence: 96%