A population-based risk factor scoring will decrease unnecessary testing for the diagnosis of gestational diabetes mellitus.

Background: To determine the effectiveness of a population-based risk factor scoring to decrease unnecessary testing for the diagnosis of gestational diabetes mellitus (GDM).

Methods: We formed a risk factor scoring over five, which questions maternal age, body mass index and first-degree relatives with a diagnosis of diabetes mellitus, a prior macrosomic fetus and adverse outcome during the previous pregnancies. All participants underwent a 50-g glucose challenge test (GCT) followed by a 100-g oral glucose tolerence test (OGTT). We opened the 50-g GCT envelope if the participant had a risk score > or = 1 and opened the 100-g OGTT envelope if the 50-g GCT value was > or = 7.2 mmol/l. After all patients delivered we also built other strategies and tested their detection rates.

Results: Fourteen patients (3.3%) were diagnosed as having gestational diabetes mellitus via a 100-g OGTT. None of the patients with a score of zero had gestational diabetes mellitus. Logistic regression analysis revealed that an increase in the score by one caused a three times increase in gestational diabetes mellitus risk (OR = 3, CI = 1.9-5). Compared with the universal screening, our strategy to screen if the risk score was > or = 1, followed by a 50-g GCT with a 7.2-mmol/l cut-off value, decreased the number of women to be screened by 30% and diagnosed all cases with GDM. Screening the patients with a score > or = 2 would have decreased the number of women to be screened by 63%, still diagnosing 85% of cases with GDM. Also, risk factor-based screening strategies cause a 50% and 53% reduction in the number of OGTT applied, respectively.

Conclusion: A well integrated, population-based scoring will decrease the number of unnecessary testing but still diagnose 85-100% of GDM cases.