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

Abstract

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. 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. 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. 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.