PDF(Pubmed)
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.
摘要：
背景：宏观出生体重已被认为是各种成人代谢疾病如糖尿病和冠心病的重要危险因素；它也与复杂出生的高发病率有关。这项研究旨在使用孕妇临床特征和妊娠上半年进行的非整倍性筛查的血清生物标志物来检查高血糖孕妇的宏观分娩的可预测性。方法：对1,668名孕妇进行了回顾性观察性研究，这些孕妇1）在两家大学医院接受50克口服葡萄糖激发试验（OGCT）后具有阳性结果，并且2）接受了以下任何一项母体生物标志物筛查胎儿非整倍性测试：三重测试，四重测试,和综合测试。开发了基于逻辑回归的模型，用于使用母体特征和血清生物标志物预测宏观出生，并评估了预测能力。一个列线图,这是最好的可预测模型的图形显示，然后生成。结果：研究队列包括157例宏观出生病例，定义为出生体重≥3,820g，这相当于建模队列的前10百分位数。仅基于血清生物标志物的三个主要模型获得0.55-0.62的曲线下面积(AUC)。扩展模型，包括孕产妇人口统计学和临床因素，性能提高了25%(AUC，0.69-0.73）。结论：我们的预测模型将有助于使用孕妇临床因素和常规产前筛查测试的血清标志物来识别高血糖母亲中大体代谢风险升高的怀孕。预测妊娠中期的宏观分娩可能允许定制的产前护理，以降低宏观分娩的风险。
