ABSTRACT
The aim of this systematic review was to examine the available scientific literature on ultrasound-detected fetal liver changes in pregnant women with gestational diabetes mellitus (GDM) and to explore the potential of these markers to inform clinical management and improve outcomes. A total of four articles investigating fetal liver changes in GDM pregnancies were selected. The studies varied in methodology, gestational age studied, and diagnostic criteria for GDM. Fetal liver indices, such as fetal liver length and fetal liver volume, emerged as potential markers for identifying GDM and predicting adverse outcomes. Studies suggest an association between fetal liver changes and GDM, with implications for both maternal glycemic control and fetal metabolic adaptation. Variability in study methodology highlights the need for standardized approaches to assess fetal hepatic indices and their correlation with GDM outcomes.
ABSTRACT
Background: To compare the best fetal weight formula with different biometric tables on the weight of Brazilian newborns. Methods: This observational study has tested the performance of different common fetal weight formulas and biometric tables. Weight estimates were performed by the methods of Warsof et al. (1977), Shepard et al. (1982), Hadlock et al. (1985), Furlan et al. (2012) and Stirnemann et al. (2017). The biometric tables selected were the following: Snijders and Nicolaides (1994), Hadlock et al. (1984), Papageorghiou et al. (2014) and Kiserud et al. (2016) and correlated to Pedreira et al. (2011) database, which was considered the gold standard. Statistical analyses were performed using the mean relative error, average absolute error and the Pearson correlation coefficient (r). Results: The best r was found when using the Snijders and Nicolaides (1994) biometric table with weight formula by Stirnemann et al. (2017). The average relative error was lower when using weight formula by Shepard et al. (1982) with biometric tables by Snijders and Nicolaides (1994), Papageorghiou et al. (2014) or Kiserud et al. (2016). On average, absolute error, the lowest r was obtained for the Furlan et al. (2012) weight formula and the Papageorghiou et al. (2014) biometric table. Conclusions: The best correlation was found for biometric table by Snijders and Nicolaides (1994) and fetal weight formula calculation for the estimation of Brazilian newborn weight by Stirnemann et al. (2017).Background: To compare the best fetal weight formula with different biometric tables on the weight of Brazilian newborns. Methods: This observational study has tested the performance of different common fetal weight formulas and biometric tables. Weight estimates were performed by the methods of Warsof et al. (1977), Shepard et al. (1982), Hadlock et al. (1985), Furlan et al. (2012) and Stirnemann et al. (2017). The biometric tables selected were the following: Snijders and Nicolaides (1994), Hadlock et al. (1984), Papageorghiou et al. (2014) and Kiserud et al. (2016) and correlated to Pedreira et al. (2011) database, which was considered the gold standard. Statistical analyses were performed using the mean relative error, average absolute error and the Pearson correlation coefficient (r). Results: The best r was found when using the Snijders and Nicolaides (1994) biometric table with weight formula by Stirnemann et al. (2017). The average relative error was lower when using weight formula by Shepard et al. (1982) with biometric tables by Snijders and Nicolaides (1994), Papageorghiou et al. (2014) or Kiserud et al. (2016). On average, absolute error, the lowest r was obtained for the Furlan et al. (2012) weight formula and the Papageorghiou et al. (2014) biometric table. Conclusions: The best correlation was found for biometric table by Snijders and Nicolaides (1994) and fetal weight formula calculation for the estimation of Brazilian newborn weight by Stirnemann et al. (2017).
