In this study, we found for the first time that macrosomal newborns were associated with lower protein density when mothers with GDM were analyzed by infrared ATR-FTIR (Attenuated Total Reflection Fourier Transform) spectroscopy, and the Genetic Algorithm (GA) mathematical model associated with Linear Discriminant Analysis (LDA). This is a case-control study, comprised of a total of 49 newborns from mothers with GDM compared with 45 newborns from mothers without GDM. The evaluated neonatal outcomes were: type of delivery, prematurity, weight in relation to gestational age, apgar, macrosomia, and head/chest perimeter. Furthermore, we correlated the presence of these neonatal adverse effects with the density of proteins in GDM. The neonatal outcomes observed in newborns of mothers with GDM showed prematurity (p = 0.018), minimum head circumference (p = 0.027), abdominal circumference (p <0.01) and macrosomia (p <0.01) when compared to newborns of mothers without GDM. Prematurity and macrosomia occurred with greater significance among pregnant women diagnosed with gestational diabetes (p <0.05). There was a correlation between macrosomal newborns and low protein density confirmed by ATR-FTIR (GA-LDA) in diabetic pregnant women. On the other hand, macrosomal newborns of mothers with GDM were correlated with women who showed lower density of protein when analyzed by ATR-FTIR (GA-LDA). In this study, we observed that macrosomia was associated with low protein density of a mother with GDM. The approach described here, can be useful for the identification and exploration of macrosomia inunder various pathophysiological conditions of maternal GDM.

Figure 1

Figure 2
No competing interests reported.
Loading...
Posted 26 Jan, 2021
Posted 26 Jan, 2021
In this study, we found for the first time that macrosomal newborns were associated with lower protein density when mothers with GDM were analyzed by infrared ATR-FTIR (Attenuated Total Reflection Fourier Transform) spectroscopy, and the Genetic Algorithm (GA) mathematical model associated with Linear Discriminant Analysis (LDA). This is a case-control study, comprised of a total of 49 newborns from mothers with GDM compared with 45 newborns from mothers without GDM. The evaluated neonatal outcomes were: type of delivery, prematurity, weight in relation to gestational age, apgar, macrosomia, and head/chest perimeter. Furthermore, we correlated the presence of these neonatal adverse effects with the density of proteins in GDM. The neonatal outcomes observed in newborns of mothers with GDM showed prematurity (p = 0.018), minimum head circumference (p = 0.027), abdominal circumference (p <0.01) and macrosomia (p <0.01) when compared to newborns of mothers without GDM. Prematurity and macrosomia occurred with greater significance among pregnant women diagnosed with gestational diabetes (p <0.05). There was a correlation between macrosomal newborns and low protein density confirmed by ATR-FTIR (GA-LDA) in diabetic pregnant women. On the other hand, macrosomal newborns of mothers with GDM were correlated with women who showed lower density of protein when analyzed by ATR-FTIR (GA-LDA). In this study, we observed that macrosomia was associated with low protein density of a mother with GDM. The approach described here, can be useful for the identification and exploration of macrosomia inunder various pathophysiological conditions of maternal GDM.

Figure 1

Figure 2
No competing interests reported.
Loading...