Predictors of repeat cesarean delivery after trial of labor: do any exist?

Autor: L A, Learman, L R, Evertson, S, Shiboski
Rok vydání: 1996
Předmět:
Zdroj: Journal of the American College of Surgeons. 182(3)
ISSN: 1072-7515
Popis: We evaluated the predictive value of risk factors for repeat cesarean delivery identified in retrospective studies.We identified 175 consecutive patients who underwent trial of labor (TOL) and compared detailed admission, intrapartum, and postpartum characteristics of those who required repeat cesarean delivery with those who had vaginal births. We calculated relative risks, positive predictive values, and sensitivities for potentially predictive admission characteristics. We also performed multiple logistic regression and classification analyses.Ninety-five percent of eligible patients underwent a TOL, and 85 percent of them delivered vaginally. Patients who had labor induced and patients with high fetal station on admission were significantly more likely to require repeat cesarean section (relative risk [RR]=2.9 and 2.1; 95 percent confidence interval [CI]=1.5 to 5.3, 1.1 to 4.2, respectively), but even these patients had high rates of vaginal birth (67 percent and 75 percent, respectively). A subgroup of patients who underwent labor induction and had large fetuses (estimated weight 3,800 g or more) had a 75 percent risk of cesarean delivery (RR=2.5, 95 percent CI=0.9 to 7.5). Multivariate models using different combinations of admission characteristics could not correctly identify which patients would require repeat cesarean delivery.Admission characteristics with statistically significant risk ratios have low predictive values because of the extremely low rate of repeat cesarean delivery in this population. A larger series is needed to study TOL outcomes in patients with large fetuses who are being induced. We conclude that until risk factors with high predictive value for repeat cesarean delivery are identified, all eligible patients should be encouraged to undergo a TOL.
Databáze: OpenAIRE