| Literature DB >> 19813165 |
William A Grobman1, Yinglei Lai, Mark B Landon, Catherine Y Spong, Kenneth J Leveno, Dwight J Rouse, Michael W Varner, Atef H Moawad, Hyagriv N Simhan, Margaret Harper, Ronald J Wapner, Yoram Sorokin, Menachem Miodovnik, Marshall Carpenter, Mary J O'Sullivan, Baha M Sibai, Oded Langer, John M Thorp, Susan M Ramin, Brian M Mercer.
Abstract
We sought to construct a predictive model for vaginal birth after cesarean (VBAC) that combines factors that can be ascertained only as the pregnancy progresses with those known at initiation of prenatal care. Using multivariable modeling, we constructed a predictive model for VBAC that included patient factors known at the initial prenatal visit as well as those that only become evident as the pregnancy progresses to the admission for delivery. We analyzed 9616 women. The regression equation for VBAC success included multiple factors that could not be known at the first prenatal visit. The area under the curve for this model was significantly greater ( P < 0.001) than that of a model that included only factors available at the first prenatal visit. A prediction model for VBAC success, which incorporates factors that can be ascertained only as the pregnancy progresses, adds to the predictive accuracy of a model that uses only factors available at a first prenatal visit. (c) Thieme Medical Publishers.Entities:
Mesh：
Year: 2009 PMID： 19813165 PMCID： PMC3008589 DOI： 10.1055/s-0029-1239494
Source DB: PubMed Journal: Am J Perinatol ISSN： 0735-1631 Impact factor: 1.862