ArticleFrontiers in medicine2026
Construction of a nomogram model for predicting vaginal birth after induction of labor in pregnant women with fetal growth restriction at term.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Pre-delivery prediction of vaginal delivery in late-onset foetal growth restriction: development and internal validation of a model with decision curve analysis and bedside calculator.Archives of gynecology and obstetrics · 2026Article
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5 authors.
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Abstract
Objectives: The study aimed to develop and validate a predictive nomogram model of vaginal delivery in women with fetal growth restriction (FGR) who undergo labor induction. Methods: A retrospective cohort study was conducted at Fujian Maternity and Child Health Hospital, involving 507 singleton pregnancies complicated with fetal growth restriction (FGR) between October 2017 and December 2022. These pregnancies underwent labor induction with dinoprostone or Cook's double balloon. The cohort was randomly divided into two groups: 75% of pregnancies ( Results: A predictive nomogram model was constructed with five validated factors including maternal age, multiparity, oligohydramnios (borderline significant), Bishop score after cervical ripening and Cook's double balloon. The trained and validated area under the curve were 0.811 (95% confident interval 0.757-0.865) and 0.760 (95% confident interval 0.669-0.860), respectively. The Hosmer-Lemeshow test indicated no statistically significant difference between the predicted and observed outcomes ( Conclusion: The nomogram model could be utilized to inform patients with FGR about their success of vaginal delivery during labor induction. Moreover, this model established a foundation for clinical intervention and the development of personalized medical treatment strategies.
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