PDF icon PDF herunterladen
Am J Perinatol 2018; 35(07): 660-668
DOI: 10.1055/s-0037-1608847
Original Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Predicting Vaginal Delivery in Nulliparous Women Undergoing Induction of Labor at Term

T. Kawakita
1   Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, District of Columbia
,
U. M. Reddy
1   Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, District of Columbia
,
C. C. Huang
2   Department of Biostatistics and Bioinformatics, MedStar Health Research Institute, Hyattsville, Maryland
3   Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, District of Columbia
,
T. C. Auguste
1   Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, District of Columbia
4   MedStar Simulation Training & Education Lab, Washington, District of Columbia
,
D. Bauer
4   MedStar Simulation Training & Education Lab, Washington, District of Columbia
,
R. T. Overcash
1   Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, District of Columbia
› Institutsangaben
Funding This project was funded in part with Federal funds (Grant # UL1TR000101 previously UL1RR031975) from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), through the Clinical and Translational Science Awards Program (CTSA), a trademark of DHHS, part of the Roadmap Initiative, “Re-Engineering the Clinical Research Enterprise.”
Weitere Informationen

Publikationsverlauf

04. Oktober 2017

12. Oktober 2017

Publikationsdatum:
06. Dezember 2017 (online)

Auch verfügbar aufeRefHebammen
   Lizenzen und Reprints
Preview

Abstract

Objective We sought to develop a model to calculate the likelihood of vaginal delivery in nulliparous women undergoing induction at term.

Study Design We obtained data from the Consortium on Safe Labor by including nulliparous women with term singleton pregnancies undergoing induction of labor at term. Women with contraindications for vaginal delivery were excluded. A stepwise logistic regression analysis was used to identify the predictors associated with vaginal delivery by considering maternal characteristics and comorbidities and fetal conditions. The receiver operating characteristic curve, with an area under the curve (AUC) was used to assess the accuracy of the model.

Results Of 10,591 nulliparous women who underwent induction of labor, 8,202 (77.4%) women had vaginal delivery. Our model identified maternal age, gestational age at delivery, race, maternal height, prepregnancy weight, gestational weight gain, cervical exam on admission (dilation, effacement, and station), chronic hypertension, gestational diabetes, pregestational diabetes, and abruption as significant predictors for successful vaginal delivery. The overall predictive ability of the final model, as measured by the AUC was 0.759 (95% confidence interval, 0.749–0.770).

Conclusion We identified independent risk factors that can be used to predict vaginal delivery among nulliparas undergoing induction at term. Our predictor provides women with additional information when considering induction.

Keywords

induction of labor - nulliparous women - predictors - vaginal delivery - web calculator

Note

The data included in this paper were obtained from the Consortium on Safe Labor, supported by the Intramural Research Program of the NICHD, NIH through contract number HHSN267200603425C. This study was presented as an oral presentation at the SMFM 37th Annual Meeting—The Pregnancy Meeting, Las Vegas, NV (January 23–28, 2017). MedStar Institutional Review Board approved the study (#2016–084, approved on May 19, 2016). The named authors alone are responsible for the views expressed in this manuscript, which does not necessarily represent the decisions or the stated policy of the NICHD.


Supplementary Material