NICHD-nuMoM2b Home page

A clinically useful tool for predicting adverse pregnancy outcomes in the pathway to severe maternal morbidity: GESTATIONAL DIABETES (GDM)

We have devised this tool to give individualized risk of developing GDM for nulliparous patients who present in the first trimester of pregnancy. These prediction rules were developed using the nuMoM2b data set within DASH (Data and Specimen Hub).

Please select the features for your patient and the next screen will give you the results in absolute risk and odds ratios

Age:	Gravidity:
Race:	Family Diabetes History:
BMI:	High Blood Pressure (Systolic > 140 or Diastolic > 80):
	Exercise:

NOTE about the nuMoM2b study population: nuMoM2b, which recruited women from 2010-2013, studied pregnant women who would be delivering for the first time (nulliparous women). This prospective cohort study evaluated the underlying, interrelated mechanisms of several common adverse pregnancy outcomes (including GDM), which can be difficult to predict for nulliparous women. As nulliparous women comprise 40% of U.S. births each year, this is an important group to understand risks. The predictive models we have developed, using machine learning techniques, should help inform healthcare providers and their patients understand risks of adverse pregnancy outcomes that contribute to severe maternal morbidity.