Can common clinical parameters be used to identify patients who will need insulin treatment in gestational diabetes mellitus?

Abstract

Objective: To identify patients with gestational diabetes mellitus (GDM) who will need antenatal insulin treatment (AIT) by using a risk-prediction tool based on maternal clinical and biochemical characteristics at diagnosis.

Research design and methods: Data from 3,009 women attending the Royal Prince Alfred Hospital GDM Clinic, Australia, between 1995 and 2010 were studied. A risk engine was developed from significant factors identified for AIT using a logistic regression model.

Results: A total of 51% of GDM patients required AIT. Ethnicity, gestation at diagnosis, HbA(1c), fasting and 60-min glucose at oral glucose tolerance test, BMI, and diabetes family history were significant independent determinants of AIT. Notably, only 9% of the attributable risk for AIT can be explained by the clinical factors studied. A modeled risk-scoring system was therefore a poor predictor of AIT.

Conclusions: Baseline maternal characteristics including HbA(1c) alone cannot predict the need for AIT in GDM. Lifestyle, compliance, or as yet unmeasured influences play a greater role in determining AIT.