Abstract
OBJECTIVE: To develop a model based on factors available at the first prenatal visit that predicts chance of successful vaginal birth after cesarean delivery (VBAC) for individual patients who undergo a trial of labor. METHODS: All women with one prior low transverse cesarean who underwent a trial of labor at term with a vertex singleton gestation were identified from a concurrently collected database of deliveries at 19 academic centers during a 4-year period. Using factors identifiable at the first prenatal visit, we analyzed different classification techniques in an effort to develop a meaningful prediction model for VBAC success. After development and cross-validation, this model was represented by a graphic nomogram. RESULTS: Seven-thousand six hundred sixty women were available for analysis. The prediction model is based on a multivariable logistic regression, including the variables of maternal age, body mass index, ethnicity, prior vaginal delivery, the occurrence of a VBAC, and a potentially recurrent indication for the cesarean delivery. After analyzing the model with cross-validation techniques, it was found to be both accurate and discriminating. CONCLUSION: A predictive nomogram, which incorporates six variables easily ascertainable at the first prenatal visit, has been developed that allows the determination of a patient-specific chance for successful VBAC for those women who undertake trial of labor.
Original language | English (US) |
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Pages (from-to) | 806-812 |
Number of pages | 7 |
Journal | Obstetrics and gynecology |
Volume | 109 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2007 |
ASJC Scopus subject areas
- Obstetrics and Gynecology