Objective: The first aim of the study is to validate the Grobmans Nomogram on Italian population, and then to include other variables with the purpose to increase the accuracy of the Nomogram.Methods: This is a multicenter study in which eligible subjects were pregnant women reaching term having one prior cesarean section (CS) and then choosing for a trial of labor. Multivariate logistic regression model have been performed, and then the predicted percentages of vaginal delivery (VD) success were divided into 10 groups and compared with the observed ones.Results: Among 1161 women, 1100 were enrolled, of which 857 (77.9%) delivered vaginally. At the multivariate logistic regression, the variables predicting vaginal birth after cesarean (VBAC) in the validation were maternal age (p < 0.001), maternal body mass index (p = 0.007), having had a VD (p = 0.008) and recurring indication for CS (p < 0.001). By adding the two new variables in the proposed model, was reached the significance of "African ethnicity" (p = 0.037) and especially "years of education" (p = 0.032).Conclusions: The Grobmans Nomogram seems to be applicable to Italian population too, even if with less accuracy than in the US population. The addition of the level of maternal education increases the accuracy of the model, underlining the importance of the social context in the choice of VBAC.

A modified prediction model for VBAC, in a European population / Annessi, E.; Del Giovane, C.; Magnani, L.; Carossino, E.; Baldoni, G.; Battagliarin, G.; Accorsi, P.; Facchinetti, F.. - In: THE JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE. - ISSN 1476-7058. - 29:3(2016), pp. 435-439. [10.3109/14767058.2014.1002767]

A modified prediction model for VBAC, in a European population

Del Giovane C.;Facchinetti F.
2016

Abstract

Objective: The first aim of the study is to validate the Grobmans Nomogram on Italian population, and then to include other variables with the purpose to increase the accuracy of the Nomogram.Methods: This is a multicenter study in which eligible subjects were pregnant women reaching term having one prior cesarean section (CS) and then choosing for a trial of labor. Multivariate logistic regression model have been performed, and then the predicted percentages of vaginal delivery (VD) success were divided into 10 groups and compared with the observed ones.Results: Among 1161 women, 1100 were enrolled, of which 857 (77.9%) delivered vaginally. At the multivariate logistic regression, the variables predicting vaginal birth after cesarean (VBAC) in the validation were maternal age (p < 0.001), maternal body mass index (p = 0.007), having had a VD (p = 0.008) and recurring indication for CS (p < 0.001). By adding the two new variables in the proposed model, was reached the significance of "African ethnicity" (p = 0.037) and especially "years of education" (p = 0.032).Conclusions: The Grobmans Nomogram seems to be applicable to Italian population too, even if with less accuracy than in the US population. The addition of the level of maternal education increases the accuracy of the model, underlining the importance of the social context in the choice of VBAC.
2016
29
3
435
439
A modified prediction model for VBAC, in a European population / Annessi, E.; Del Giovane, C.; Magnani, L.; Carossino, E.; Baldoni, G.; Battagliarin, G.; Accorsi, P.; Facchinetti, F.. - In: THE JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE. - ISSN 1476-7058. - 29:3(2016), pp. 435-439. [10.3109/14767058.2014.1002767]
Annessi, E.; Del Giovane, C.; Magnani, L.; Carossino, E.; Baldoni, G.; Battagliarin, G.; Accorsi, P.; Facchinetti, F.
File in questo prodotto:
File Dimensione Formato  
14767058.2014.1002767.pdf

Accesso riservato

Tipologia: Versione pubblicata dall'editore
Dimensione 304.53 kB
Formato Adobe PDF
304.53 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1223058
Citazioni
  • ???jsp.display-item.citation.pmc??? 6
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 20
social impact