title: Estimating the risk of gestational diabetes mellitus: a clinical prediction model based on patient characteristics and medical history.
abstract: OBJECTIVE
  To develop a clinical prediction rule that can help the clinician to identify women at high and low risk for gestational diabetes mellitus (GDM) early in pregnancy in order to improve the efficiency of GDM screening.
  
  
  METHODS
  We used data from a prospective cohort study to develop the clinical prediction rule.
  
  
  METHODS
  The original cohort study was conducted in a university hospital in the Netherlands.
  
  
  METHODS
  Nine hundred and ninety-five consecutive pregnant women underwent screening for GDM.
  
  
  METHODS
  Using multiple logistic regression analysis, we constructed a model to estimate the probability of development of GDM from the medical history and patient characteristics. Receiver operating characteristics analysis and calibration were used to assess the accuracy of the model.
  
  
  METHODS
  The development of a clinical prediction rule for GDM. We also evaluated the potential of the prediction rule to improve the efficiency of GDM screening.
  
  
  RESULTS
  The probability of the development of GDM could be predicted from the ethnicity, family history, history of GDM and body mass index. The model had an area under the receiver operating characteristic curve of 0.77 (95% CI 0.69-0.85) and calibration was good (Hosmer and Lemeshow test statistic, P = 0.25). If an oral glucose tolerance test was performed in all women with a predicted probability of 2% or more, 43% of all women would be tested and 75% of the women with GDM would be identified.
  
  
  CONCLUSIONS
  The use of a clinical prediction model is an accurate method to identify women at increased risk for GDM, and could be used to select women for additional testing for GDM.
authors.affiliation: Department of Obstetrics and Gynaecology, Academic Medical Centre, Amsterdam, the Netherlands. marsha.vanleeuwen@amc.uva.nl
authors.forename: M
authors.initials: M
authors.lastname: van Leeuwen
authors.forename: B C
authors.initials: BC
authors.lastname: Opmeer
authors.forename: E J K
authors.initials: EJ
authors.lastname: Zweers
authors.forename: E
authors.initials: E
authors.lastname: van Ballegooie
authors.forename: H G
authors.initials: HG
authors.lastname: ter Brugge
authors.forename: H W
authors.initials: HW
authors.lastname: de Valk
authors.forename: G H A
authors.initials: GH
authors.lastname: Visser
authors.forename: B W J
authors.initials: BW
authors.lastname: Mol
mesh_terms: D016640:Diabetes, Gestational / Q000175:diagnosis*; D005260:Female; D005951:Glucose Tolerance Test; D006801:Humans; D008487:Medical History Taking; D049451:Nomograms; D011247:Pregnancy; D011296:Prenatal Diagnosis / Q000379:methods; D011446:Prospective Studies