Development and validation of a clinical model to predict preconception risk of gestational diabetes mellitus in nulliparous women: A retrospective cohort study

ObjectiveTo develop and validate a model to predict the preconception risk of gestational diabetes mellitus (GDM) in nulliparous women.MethodsThis was a retrospective cohort study. A total of 1565 women in early pregnancy who underwent preconception health examinations in the Women and Children's Hospital of Chongqing Medical University between January 2020 and June 2021 were invited to participate in a questionnaire survey. Logistic regression analysis was performed to determine the preconception risk factors for GDM. These factors were used to construct a model to predict GDM risk in nulliparous women. Then, the model was used to assess the preconception risk of GDM in 1060 nulliparous women.ResultsIndependent preconception risk factors for GDM included the following: age 35 years or greater, diastolic blood pressure 80 mm Hg or greater, fasting plasma glucose 5.1 mmol/L or greater, body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters) 24 or greater, weight gain 10 kg or greater in the year before pregnancy, age of menarche 15 years or greater, three or more previous pregnancies, daily staple food intake 300 g or greater, fondness for sweets, and family history of diabetes. BMI less than 18.5, daily physical activity duration 1 h or greater, and high-intensity physical activity were protective factors. These factors were used to construct a model to predict GDM risk in nulliparous women, and the incidence of GDM significantly increased as the risk score increased. The area under the curve of the prediction model was 0.82 (95% confidence interval 0.80-0.85).ConclusionThe preconception GDM risk prediction model demonstrated good predictive efficacy and can be used to identify populations at high risk of GDM before pregnancy, which provides the possibility for preconception intervention. A preconception gestational diabetes mellitus risk prediction model for nulliparous women was constructed and demonstrated to have good predictive efficacy.