title: A mathematical model for predicting outcome in preterm labour.
abstract: OBJECTIVE
  This study aimed to develop a model for predicting the outcome and evaluating the treatment of patients with threatened of preterm labour.
  
  
  METHODS
  Clinical data from 236 patients at <32 weeks gestation who were in preterm labour were analysed to develop a discriminant function using multiple logistic regression to identify significant risk factors. The function was validated retrospectively in a further 501 patients and prospectively in 63 patients with premature labour.
  
  
  RESULTS
  Factors that increased the risk of preterm birth were premature rupture of the membranes, intrauterine infection, dilatation of the cervix and uterine bleeding. Factors that decreased the risk of preterm birth were hospital admission after 28 weeks of gestation and intravenous administration of ritodrine. The predictive accuracy of the function was 75.4% in the 236 patients analysed, 84.8% in the further 501 retrospectively studied patients and 85.7% in the prospective group.
  
  
  CONCLUSIONS
  The discriminant function described was clinically useful for predicting the outcome of threatened preterm labour before initiating treatment and for determining the medical care of patients, including maternal transfer to a high-level perinatal care centre.
authors.affiliation: Department of Obstetrics and Gynaecology, Saitama Medical University Saitama Medical Centre, 1981 Tsujido-machi, Kamoda, Kawagoe-shi, Saitama 350-8550, Japan. 0384504001@jcom.home.ne.jp
authors.forename: K
authors.initials: K
authors.lastname: Takagi
authors.forename: K
authors.initials: K
authors.lastname: Satoh
authors.forename: M
authors.initials: M
authors.lastname: Muraoka
authors.forename: K
authors.initials: K
authors.lastname: Takagi
authors.forename: H
authors.initials: H
authors.lastname: Seki
authors.forename: M
authors.initials: M
authors.lastname: Nakabayashi
authors.forename: S
authors.initials: S
authors.lastname: Takeda
authors.forename: K
authors.initials: K
authors.lastname: Yoshida
authors.forename: N
authors.initials: N
authors.lastname: Nishioka
authors.forename: T
authors.initials: T
authors.lastname: Ikenoue
authors.forename: N
authors.initials: N
authors.lastname: Kanayama
authors.forename: T
authors.initials: T
authors.lastname: Kanzaki
authors.forename: T
authors.initials: T
authors.lastname: Sagawa
authors.forename: Y
authors.initials: Y
authors.lastname: Matsuda
mesh_terms: D000328:Adult; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D016015:Logistic Models; D008954:Models, Biological; D007752:Obstetric Labor, Premature / Q000188:drug therapy / Q000517:prevention & control*; D016017:Odds Ratio; D011247:Pregnancy; D011446:Prospective Studies; D012189:Retrospective Studies; D012307:Risk Factors; D012312:Ritodrine / Q000627:therapeutic use; D012680:Sensitivity and Specificity; D015145:Tocolysis; D015149:Tocolytic Agents / Q000627:therapeutic use; D016896:Treatment Outcome; D055815:Young Adult
chemical_list: D015149:Tocolytic Agents; D012312:Ritodrine