Sonographic evaluation of fetal abdominal subcutaneous tissue in pregnancies complicated by gestational and type 1 diabetes mellitus
摘要
To perform a comparative analysis of fetal abdominal fat mass (AFM) thickness in women diagnosed with gestational (GDM) and type 1 diabetes mellitus (T1DM), and to evaluate the efficacy of the ultrasonographic AFM measurement in the estimation of the fetal birth-weight (FBW) and prediction of fetal macrosomia. A total of 245 participants were recruited for this prospective observational cohort study, including women with diet-controlled GDM (GDMG1) (n = 50), insulin-controlled GDM (GDMG2) (n = 50), T1DM (n = 50) as well as non-diabetic control patients (n = 95). In each participant measurements of the AFM in conjunction with the standard fetal biometric parameters were performed within the 72 h period prior to delivery. Fetal macrosomia was defined as birth-weight ≥ 4000 g irrespective of gestational age. After adjustment for confounding factors, median AFM and abdominal circumference (AC) measurements as well as the FBW were significantly higher among patients with T1DM as compared to other groups (p < 0.05). In each group both AFM and AC measurements showed strong positive correlations with the FBW (p < 0.001). Two new models comprising maternal (body mass index) and/or ultrasound-derived parameters (biparietal diameter, AC, AFM) for the FBW estimation were constructed. Both equations provided significantly lower mean absolute percent error among GDMG1 and T1DM women as compared to the Hadlock formula (p < 0.05). In addition novel equation for the prediction of fetal macrosomia, utilizing both AC and AFM measurements, yielded sensitivity of 84.8%, specificity 91.9%, positive predictive value 62.2% and negative predictive value of 97.5% within the total study population. In women with GDM/T1DM, the incorporation of the AFM measurement into equations for the FBW estimation provided better accuracy compared to standard formulas and increased the detection of fetal macrosomia. Further validation in large-scale multicenter studies is necessary prior to clinical implementation.