title: Risk stratification in early pregnancy for women at increased risk of gestational diabetes.
abstract: OBJECTIVE
  To evaluate the addition of fasting glucose and lipids to a simple, validated risk prediction tool for gestational diabetes (GDM) applied in early pregnancy.
  
  
  METHODS
  Women at risk of developing GDM on a validated risk prediction tool were recruited in early pregnancy into a large randomised controlled trial. Outcome measures included fasting biochemical markers (glucose, lipids) at 12-15 weeks gestation and GDM diagnosis (28 weeks gestation). Multivariable logistic regression was used to identify additional predictive biochemical variables for GDM, with corresponding receiver operator characteristic (ROC) curves generated. Unadjusted and adjusted models were derived for both the Australasian Diabetes in Pregnancy (ADIPS) and the International Association for Diabetes in Pregnancy Study Group (IADPSG) GDM diagnostic criteria.
  
  
  RESULTS
  51 (23%) Women were diagnosed with GDM based on ADIPS criteria, with 60 (30%) diagnosed based on IADPSG criteria. In all four regression models, fasting glucose was the strongest predictor for GDM development with an odds ratio range of 4.7-6.3 (ADIPS) and 8.8-10 (IADPSG). ROC curves revealed an area under the curve of 0.79 (95% CI: 0.72-0.86) for ADIPS criteria and 0.83 (95% CI: 0.77-0.90) for IADPSG criteria for adjusted models.
  
  
  CONCLUSIONS
  In a two-step approach, when applied with a validated risk prediction tool, fasting glucose in early pregnancy was predictive of GDM and incrementally improved risk identification, presenting potential for an early pregnancy, GDM risk screening strategy for streamlining of pregnancy care and opportunity for preventive intervention.
authors.affiliation: Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
authors.forename: C L
authors.initials: CL
authors.lastname: Harrison
authors.affiliation: Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
authors.forename: C B
authors.initials: CB
authors.lastname: Lombard
authors.affiliation: Monash Women's Maternity Services, Monash Health, Melbourne, Australia.
authors.forename: C
authors.initials: C
authors.lastname: East
authors.affiliation: Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
authors.forename: J
authors.initials: J
authors.lastname: Boyle
authors.affiliation: Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Diabetes and Vascular Medicine Unit, Monash Health, Melbourne, Australia. Electronic address: Helena.teede@monash.edu.
authors.forename: H J
authors.initials: HJ
authors.lastname: Teede
mesh_terms: D000328:Adult; D001786:Blood Glucose / Q000378:metabolism; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D015331:Cohort Studies; D016640:Diabetes, Gestational / Q000097:blood* / Q000175:diagnosis; D005260:Female; D006801:Humans; D016015:Logistic Models; D011237:Predictive Value of Tests; D011247:Pregnancy / Q000097:blood*; D016032:Randomized Controlled Trials as Topic / Q000379:methods; D012189:Retrospective Studies; D012306:Risk; D014280:Triglycerides / Q000097:blood
chemical_list: D001786:Blood Glucose; D008076:Cholesterol, HDL; D014280:Triglycerides; D002784:Cholesterol
keywords: Gestational diabetes; Pregnancy; Risk stratification; Screening