Predictability of Macrosomic Birth based on Maternal Factors and Fetal Aneuploidy Screening Biochemical Markers in Hyperglycemic Mothers

Abstract

Background: Macrosomic birth weight has been implicated as a significant risk factor for developing various adult metabolic diseases such as diabetes mellitus and coronary heart diseases; it has also been associated with higher incidences of complicated births. This study aimed to examine the predictability of macrosomic births in hyperglycemic pregnant women using maternal clinical characteristics and serum biomarkers of aneuploidy screening performed in the first half of pregnancy. Methods: A retrospective observational study was performed on a cohort of 1,668 pregnant women who 1) had positive outcomes after undergoing 50-g oral glucose challenge test (OGCT) at two university-based hospitals and 2) underwent any one of the following maternal biomarker screening tests for fetal aneuploidy: triple test, quadruple test, and integrated test. Logistic regression-based models for predicting macrosomic births using maternal characteristics and serum biomarkers were developed and evaluated for prediction power. A nomogram, which is a graphical display of the best predictable model, was then generated. Results: The study cohort included 157 macrosomic birth cases defined as birth weight >= 3,820 g, which was equivalent to the top 10 percentile of the modeling cohort. Three primary models solely based on serum biomarkers achieved area under curves (AUCs) of 0.55-0.62. Expanded models, including maternal demographic and clinical factors, demonstrated an improved performance by 25% (AUCs, 0.69-0.73). Conclusion: Our prediction models will help to identify pregnancies with an elevated risk of macrosomic births in hyperglycemic mothers using maternal clinical factors and serum markers from routine antenatal screening tests. Prediction of macrosomic birth at mid-pregnancy may allow customized antenatal care to reduce the risk of macrosomic births.