Predicting vaginal birth after cesarean delivery: A review of prognostic factors and screening tools

Jason N. Hashima, Karen B. Eden, Patricia Osterweil, Peggy Nygren, Jeanne Marie Guise

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


Objective: Our purpose was to identify the factors associated with vaginal delivery after trial of labor in patients with a prior cesarean and to evaluate the effectiveness of existing screening tools. Study design: Studies were identified through MEDLINE and HealthSTAR (1980-2002), reference list reviews, and suggestions of national experts. Results: Thirteen of the 100 eligible studies provided fair to good quality evidence for the predictive nature of 12 factors. Two of the six screening tools were considered promising and demonstrated reproducibility through validation studies. Conclusions: There is little high-quality data to guide clinical decisions regarding which women are likely to have a successful trial of labor. Although we identified two validated screening tools that may be reasonable for practitioners to use, further development is needed to deliver them in a user-friendly manner and further research is needed to determine the clinical setting in which they are most useful. Conducting high-quality research on the factors that delineate women who are at higher likelihood of vaginal delivery without complications and developing accurate user-friendly screening tools to integrate these data should be a national research priority.

Original languageEnglish (US)
Pages (from-to)547-555
Number of pages9
JournalAmerican journal of obstetrics and gynecology
Issue number2
StatePublished - Feb 2004


  • Diagnostic testing
  • Evidence-based medicine
  • Predictors
  • Screening tests
  • Trial of labor
  • Vaginal birth after cesarean

ASJC Scopus subject areas

  • Obstetrics and Gynecology


Dive into the research topics of 'Predicting vaginal birth after cesarean delivery: A review of prognostic factors and screening tools'. Together they form a unique fingerprint.

Cite this