Quantitative Fetal Growth Curves Comparison: A Collaborative Approach

Author(s):  
Mario A. Bochicchio ◽  
Lucia Vaira ◽  
Antonella Longo ◽  
Antonio Malvasi ◽  
Andrea Tinelli
Author(s):  
Leah Zilversmit Pao ◽  
Emily W. Harville ◽  
Jeffrey K. Wickliffe ◽  
Arti Shankar ◽  
Pierre Buekens

Metals, stress, and sociodemographics are commonly studied separately for their effects on birth outcomes, yet often jointly contribute to adverse outcomes. This study analyzes two methods for measuring cumulative risk to understand how maternal chemical and nonchemical stressors may contribute to small for gestational age (SGA). SGA was calculated using sex-specific fetal growth curves for infants of pregnant mothers (n = 2562) enrolled in the National Institute of Child Health and Human Development (NICHD) Fetal Growth Study. The exposures (maternal lead, mercury, cadmium, Cohen’s perceived stress, Edinburgh depression scores, race/ethnicity, income, and education) were grouped into three domains: metals, psychosocial stress, and sociodemographics. In Method 1 we created cumulative risk scores using tertiles. Method 2 employed weighted quantile sum (WQS) regression. For each method, logistic models were built with three exposure domains individually and race/ethnicity, adjusting for age, parity, pregnancy weight gain, and marital status. The adjusted effect of overall cumulative risk with three domains, was also modeled using each method. Sociodemographics was the only exposure associated with SGA in unadjusted models ((odds ratio) OR: 1.35, 95% (confidence interval) CI: 1.08, 1.68). The three cumulative variables in adjusted models were not significant individually, but the overall index was associated with SGA (OR: 1.17, 95% CI: 1.02, 1.35). In the WQS model, only the sociodemographics domain was significantly associated with SGA. Sociodemographics tended to be the strongest risk factor for SGA in both risk score and WQS models.


2021 ◽  
Vol 224 (2) ◽  
pp. S82-S83
Author(s):  
Rebecca Simon ◽  
Brittany Bergam ◽  
Ronit Katz ◽  
Rosemary Shay ◽  
Shani Delaney

2019 ◽  
Author(s):  
Juan Jesus Fernández Alba ◽  
Estefania Soto Pazos ◽  
Rocio Moreno Cortes ◽  
Angel Vilar Sanchez ◽  
Carmen Gonzalez Macias ◽  
...  

Abstract Background Gestational diabetes mellitus is associated with increased incidence of adverse perinatal outcomes including newborns large for gestational age, macrosomia, preeclampsia, polihydramnios, stillbirth, and neonatal morbidity. Thus, fetal growth should be monitored by ultrasound to limit fetal overnutrition, and thereby, its clinical consequence, macrosomia. However, it is not clear which reference curve to use to define the limits of normality. Our aim is to determine which method, INTERGROWTH21st or customized curves, better identifies the nutritional status of newborns of diabetic mothers.Methods This retrospective cohort study compared the risk of malnutrition in SGA newborns and the risk of overnutrition in LGA newborns using INTERGROWTH21st and customized birth weight references in gestational diabetes. Additionally, to determine the ability of both methods in the identification of neonatal malnutrition and overnutrition, we calculate sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratios.Results 231 pregnant women with GDM were included in the study. The rate of SGA indentified by INTERGROWTH21st was 4.7% vs 10.7% identified by the customized curves. The rate of LGA identified by INTERGROWT21st was 25.6% vs 13.2% identified by the customized method. Newborns identified as SGA by the customized method showed a higher risk of malnutrition than those identified as SGA by INTERGROWTH21st.(RR 4.24 vs 2.5). LGA newborns according to the customized method also showed a higher risk of overnutrition than those classified as LGA according to INTERGROWTH21st. (RR 5.26 vs 3.57). In addition, the positive predictive value of the customized method was superior to that of INTERGROWTH21st in the identification of malnutrition (32% vs 27.27%), severe malnutrition (22.73% vs 20%), overnutrition (51.61% vs 32.20%) and severe overnutrition (28.57% vs 14.89%).Conclusions In pregnant women with GDM, the ability of customized fetal growth curves to identify the newborns with alterations in nutritional status exceeds that of INTERGROWTH21st.


2017 ◽  
Vol 129 ◽  
pp. 5S
Author(s):  
Akhila M. Rajaram ◽  
Emmie R. Strassberg ◽  
Michael J. Paglia ◽  
Jay J. Bringman ◽  
A. George Neubert ◽  
...  

Author(s):  
Mario A. Bochicchio ◽  
Antonella Longo ◽  
Lucia Vaira ◽  
Antonio Malvasi ◽  
Andrea Tinelli

2017 ◽  
Vol 48 (2) ◽  
pp. 294-297 ◽  
Author(s):  
Rachel Thompson ◽  
Tiffany M. Wolf ◽  
Heather Robertson ◽  
Margarita Woc Colburn ◽  
Alexis Moreno ◽  
...  
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