Second trimester prediction of gestational diabetes: maternal analytes as an additional screening tool

Abstract

Abstract Objectives Early diagnosis of gestational diabetes can lead to greater optimization of glucose control. We evaluated associations between maternal serum analytes (alpha-fetoprotein [AFP], free beta-human chorionic gonadotropin [beta-hCG], inhibin, and estriol) and the development of gestational diabetes mellitus (GDM). Methods This retrospective cohort study identified single-ton pregnancies with available second trimester serum analytes between 2009 and 2017. GDM was identified by ICD-9 and -10 codes. We examined the associations between analyte levels and GDM and to adjust for potential confounders routinely collected during genetic serum screening (maternal age, BMI, and race) using logistic regression. Optimal logistic regression predictive modeling for GDM was then performed using the analyte levels and the above mentioned potential confounders. The performance of the model was assessed by receiver operator curves. Results Out of 5,709 patients, 660 (11.6%) were diagnosed with GDM. Increasing AFP and estriol were associated with decreasing risk of GDM, aOR 0.76 [95% CI 0.60–0.95] and aOR 0.67 [95% CI 0.50–0.89] respectively. Increasing beta-hCG was associated with a decreasing risk for GDM(aOR 0.84 [95% CI 0.73–0.97]). There was no association with inhibin. The most predictive GDM predictive model included beta-hCG and estriol in addition to the clinical variables of age, BMI, and race (area under the curve (AUC 0.75), buy this was not statistically different than using clinical variables alone (AUC 0.74) (p=0.26). Conclusions Increasing second trimester AFP, beta-hCG, and estriol are associated with decreasing risks of GDM, though do not improve the predictive ability for GDM when added to clinical risk factors of age, BMI, and race.