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The primary aim of this study is to evaluate whether fetal liver length and volume, as assessed by ultrasound, can serve as reliable markers of the metabolic impact of Gestational Diabetes Mellitus (GDM) on the fetus.
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Maternal hyperglycemia during pregnancy, even at levels below the diagnostic threshold for gestational diabetes mellitus (GDM), is associated with adverse outcomes such as macrosomia, neonatal hypoglycemia, and long-term metabolic risk in offspring. Current clinical assessment of glycemic impact relies primarily on maternal glucose testing, such as the oral glucose tolerance test (OGTT), and indirect fetal anthropometric markers including abdominal circumference or estimated fetal weight . However, these measures may not fully reflect the fetal metabolic response to maternal hyperglycemia . Emerging evidence suggests that the fetal liver is highly sensitive to maternal glycemic status due to its central role in glucose uptake, glycogen storage, and lipid metabolism . Ultrasound studies have demonstrated that fetuses of mothers with GDM often show increased liver length and volume compared with normoglycemic controls, and these changes can occur before overt increases in overall fetal size .Thus, fetal liver measurements may provide an earlier and more direct marker of intrauterine glycemic exposure . Currently, the strategy for evaluating glycemic impact in pregnancy is based on maternal glucose testing and late-gestation fetal growth assessment, which may delay timely intervention . Moreover, there is no widely accepted ultrasound marker that specifically reflects fetal metabolic adaptation to hyperglycemia . The rationale of this research is to evaluate fetal liver length and volume by ultrasound as novel markers of glycemic impact in pregnancy. By establishing their relationship with maternal glycemic status, this study aims to determine whether fetal liver measurements can serve as an early, non-invasive, and practical tool to identify at-risk pregnancies, thereby paving the way for improved monitoring and timely intervention.
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Yousef Ahmed Mahmoud Ahmed, Master; Mohamed Mahmoud Abd-Allah
Data sourced from clinicaltrials.gov
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