title: Improvement of selective screening strategy for gestational diabetes through a more accurate definition of high-risk groups.
abstract: OBJECTIVE
  This study aimed to assess the predictive value of risk factors (RFs) for gestational diabetes mellitus (GDM) established by selective screening (SS) and to identify subgroups of women at a higher risk of developing GDM.
  
  
  METHODS
  A retrospective, single-center study design was employed.
  
  
  METHODS
  Data of 1015 women screened for GDM at 24-28 weeks of gestation and diagnosed according to the International Association of Diabetes and Pregnancy Study Groups criteria were evaluated. Information on RFs established by SS was also collected and their association with GDM was determined. To identify distinct and homogeneous subgroups of patients at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used.
  
  
  RESULTS
  Overall, 113 (11.1%) women were diagnosed as having GDM. The application of the SS criteria would result in the execution of an oral glucose tolerance test (OGTT) in 58.3% of women and 26 (23.0%) cases of GDM would not be detected due to the absence of any RF. The RECPAM analysis identified high-risk subgroups characterized by fasting plasma glucose values >5.1 mmol/l (odds ratio (OR)=26.5; 95% CI 14.3-49.0) and pre-pregnancy BMI (OR=7.0; 95% CI 3.9-12.8 for overweight women). In a final logistic model including RECPAM classes, previous macrosomia (OR=3.6; 95% CI 1.1-11.6), and family history of diabetes (OR=1.8; 95% CI 1.1-2.8), but not maternal age, were also found to be associated with an increased risk of developing GDM. A screening approach based on the RECPAM model would reduce by over 50% (23.0 vs 10.6%) the number of undiagnosed GDM cases when compared with the current SS approach, at the expense of 50 additional OGTTs required.
  
  
  CONCLUSIONS
  A screening approach based on our RECPAM model results in a significant reduction in the number of undetected GDM cases compared with the current SS procedure.
authors.affiliation: Department of Clinical Pharmacology and Epidemiology, Consorzio Mario Negri Sud, Via Nazionale, 66030 S. Maria Imbaro (CH), Italy.
authors.forename: Basilio
authors.initials: B
authors.lastname: Pintaudi
authors.forename: Giacoma
authors.initials: G
authors.lastname: Di Vieste
authors.forename: Francesco
authors.initials: F
authors.lastname: Corrado
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Lucisano
authors.forename: Fabio
authors.initials: F
authors.lastname: Pellegrini
authors.forename: Loretta
authors.initials: L
authors.lastname: Giunta
authors.forename: Antonio
authors.initials: A
authors.lastname: Nicolucci
authors.forename: Rosario
authors.initials: R
authors.lastname: D'Anna
authors.forename: Antonino
authors.initials: A
authors.lastname: Di Benedetto
mesh_terms: D000328:Adult; D015992:Body Mass Index; D016640:Diabetes, Gestational / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology / Q000503:physiopathology; D005192:Family Health; D005260:Female; D005320:Fetal Macrosomia / Q000503:physiopathology; D006801:Humans; D006943:Hyperglycemia / Q000209:etiology; D007558:Italy / Q000453:epidemiology; D016015:Logistic Models; D050177:Overweight / Q000503:physiopathology; D011247:Pregnancy; D011262:Pregnancy Trimester, Second; D018566:Pregnancy, High-Risk / Q000097:blood; D011296:Prenatal Diagnosis / Q000379:methods*; D015995:Prevalence; D058996:Quality Improvement; D012189:Retrospective Studies; D012307:Risk Factors; D012680:Sensitivity and Specificity