Predicting cesarean in the second stage of labor

Am J Perinatol. 2013 Nov;30(10):827-32. doi: 10.1055/s-0032-1333411. Epub 2013 Jan 17.

Abstract

Objective: To develop a prediction model for cesarean delivery (CD) in the second stage of labor using classification and regression tree (CART) analysis.

Study design: Retrospective cohort of term women who reached 10-cm dilation. The primary outcome was CD at 10-cm dilation. Logistic regression and CART analysis were performed to identify factors that best predict second-stage CD. Only factors known at the time a patient reaches 10-cm dilation were used.

Results: Of 5,388 subjects who reached 10 cm, 88 (1.6%) underwent CD. The logistic regression model identified 4 risk factors for CD and produced an area under the receiver operator characteristic curve of 0.75 (95% confidence interval 0.70 to 0.81). CART analysis identified the most important variable in predicting second-stage CD was a station at or higher than 0 at complete dilatation, but correctly classified only 19.3% of CD.

Conclusion: Second-stage cesarean cannot be reliably predicted based on antenatal and intrapartum characteristics by logistic regression or CART techniques.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms*
  • Cesarean Section / statistics & numerical data*
  • Cohort Studies
  • Decision Support Techniques*
  • Female
  • Humans
  • Labor Stage, Second / physiology*
  • Models, Statistical*
  • Pregnancy
  • ROC Curve
  • Retrospective Studies