Observational studyScientific reports2023
Prediction of an effective cervical ripenning in the induction of labour using vaginal dinoprostone.
Observational study in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The trial behind it
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Who cites it
7 citing papers in PubMed.
- The Bishop Index and Birth Outcomes in Nulliparous Women Undergoing Labor Induction: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Development of a prediction model for mortality in infants undergoing therapeutic hypothermia for neonatal encephalopathy.Journal of perinatology : official journal of the California Perinatal Association · 2026Article
- The Impact of Maternal Obesity on the Duration of Labor Stages in Dinoprostone-Induced Vaginal Delivery.Journal of clinical medicine · 2025Article
- Prediction Model for Successful Induction of Labor by Fetal Middle Cerebral Artery Pulsatility Index and Obstetric Factors in Term Pregnancy: A Prospective Cohort Study.Obstetrics and gynecology international · 2025Article
- Predictive Factors for the Success of Vaginal Dinoprostone for the Induction of Labour.International journal of women's health · 2024Article
- Liability, risks, and recommendations for ultrasound use in the diagnosis of obstetrics diseases.Heliyon · 2023Review
- Induction of labor with dinoprostone in hypertensive disorders of pregnancy: comparative analysis with normotensive pregnant women.Colombia medica (Cali, Colombia)Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To develop a predictive model for successful cervical ripening in women that undergo induction of labour by means of a vaginal prostaglandin slow-release delivery system (Propess®). Prospective observational study on 204 women that required induction of labour between February 2019 and May 2020 at "La Mancha Centro" hospital in Alcázar de San Juan, Spain. The main variable studied was effective cervical ripening (Bishop score > 6). Using multivariate analysis and binary logistic regression, we created three initial predictive models (model A: Bishop Score + Ultrasound cervical length + clinical variables (estimated fetal weight, premature rupture of membranes and body mass index)); model B: Ultrasound cervical lenght + clinical variables; and model C: Bishop score + clinical variables) to predict effective cervical ripening. All three predictive models obtained (A, B and C) presented good predictive capabilities, with an area under the ROC curve ≥ 0.76. Predictive model C, composed of the variables: gestational age (OR 1.55, 95% CI 1.18-2.03, p = 0.002), premature rupture of membranes (OR 3.21 95% CI 1.34-7.70, p = 0.09) body mass index (OR 0.93, 95% CI 0.87-0.98, p = 0.012), estimated fetal weight (OR 0.99, 95% CI 0.99-1.00, p = 0.068) and Bishop score (OR 1.49 95% CI 1.18-1.81, p = 0.001), is presented as the model of choice with an area under the ROC curve of 0.76 (95% CI 0.70-0.83, p < 0.001). A predictive model composed of the variables: gestational age, premature rupture of membranes, body mass index, estimated fetal weight and Bishop score upon admission presents good capabilities in predicting successful cervical ripening following administration of prostaglandins. This tool could be useful in making clinical decisions with regard to induction of labour.
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