title: Predictive model for risk of cesarean section in pregnant women after induction of labor.
abstract: OBJECTIVE
  To develop a predictive model for risk of cesarean section in pregnant women after induction of labor.
  
  
  METHODS
  A retrospective cohort study was conducted of 861 induced labors during 2009, 2010, and 2011 at Hospital "La Mancha-Centro" in Alcázar de San Juan, Spain. Multivariate analysis was used with binary logistic regression and areas under the ROC curves to determine predictive ability. Two predictive models were created: model A predicts the outcome at the time the woman is admitted to the hospital (before the decision to of the method of induction); and model B predicts the outcome at the time the woman is definitely admitted to the labor room.
  
  
  RESULTS
  The predictive factors in the final model were: maternal height, body mass index, nulliparity, Bishop score, gestational age, macrosomia, gender of fetus, and the gynecologist's overall cesarean section rate. The predictive ability of model A was 0.77 [95% confidence interval (CI) 0.73-0.80] and model B was 0.79 (95% CI 0.76-0.83). The predictive ability for pregnant women with previous cesarean section with model A was 0.79 (95% CI 0.64-0.94) and with model B was 0.80 (95% CI 0.64-0.96). For a probability of estimated cesarean section ≥80%, the models A and B presented a positive likelihood ratio (+LR) for cesarean section of 22 and 20, respectively. Also, for a likelihood of estimated cesarean section ≤10%, the models A and B presented a +LR for vaginal delivery of 13 and 6, respectively.
  
  
  CONCLUSIONS
  These predictive models have a good discriminative ability, both overall and for all subgroups studied. This tool can be useful in clinical practice, especially for pregnant women with previous cesarean section and diabetes.
authors: "Mancha-Centro" Teaching Unit, Ciudad Real, Spain. antomatron@gmail.com.|, C/Gerona 25 Tomelloso, 13700, Ciudad Real, Spain. antomatron@gmail.com.
authors: Antonio
authors: A
authors: Hernández-Martínez
authors: Gynecology and Obstetrics Department at Hospital "Mancha-Centro", Ciudad Real, Spain.
authors: Ana I
authors: AI
authors: Pascual-Pedreño
authors: Hospital "Mancha-Centro", Ciudad Real, Spain.
authors: Ana B
authors: AB
authors: Baño-Garnés
authors: Hospital "Mancha-Centro", Ciudad Real, Spain.
authors: María R
authors: MR
authors: Melero-Jiménez
authors: Public Health, Ciudad Real, Spain.
authors: José M
authors: JM
authors: Tenías-Burillo
authors: University of Castilla-La Mancha, Ciudad Real, Spain.
authors: Milagros
authors: M
authors: Molina-Alarcón
mesh_terms: D000293:Adolescent; D000328:Adult; D054791:Cervical Length Measurement / Q000379:methods*; D002585:Cesarean Section; D036861:Delivery, Obstetric; D005260:Female; D005865:Gestational Age; D006801:Humans; D007751:Labor, Induced / Q000379:methods*; D016015:Logistic Models; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011247:Pregnancy; D011248:Pregnancy Complications; D012372:ROC Curve; D012189:Retrospective Studies; D012306:Risk; D013030:Spain; D055815:Young Adult
keywords: Cesarean section; Induction of labor; Predictive model