title: Predicting cesarean in the second stage of labor.
abstract: OBJECTIVE
  To develop a prediction model for cesarean delivery (CD) in the second stage of labor using classification and regression tree (CART) analysis.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  Second-stage cesarean cannot be reliably predicted based on antenatal and intrapartum characteristics by logistic regression or CART techniques.
authors: Department of Obstetrics and Gynecology, The University of Alabama at Birmingham, Birmingham, Alabama.
authors: Lorie M
authors: LM
authors: Harper
authors: Anthony O
authors: AO
authors: Odibo
authors: George A
authors: GA
authors: Macones
authors: Alison G
authors: AG
authors: Cahill
mesh_terms: D000328:Adult; D000465:Algorithms; D002585:Cesarean Section / Q000706:statistics & numerical data*; D015331:Cohort Studies; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D007748:Labor Stage, Second / Q000502:physiology*; D015233:Models, Statistical; D011247:Pregnancy; D012372:ROC Curve; D012189:Retrospective Studies