SERIAL ULTRASOUND TO ESTIMATE FETAL GROWTH CURVES IN SOUTHERN TAMANDUA (TAMANDUA TETRADACTYLA)

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

1997 ◽  
Vol 49 (2) ◽  
pp. 157
Author(s):  
Y. Sakata ◽  
H. Nishida
Keyword(s):  

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Kjell Haram ◽  
Eirik Søfteland ◽  
Radek Bukowski

The growth of the fetus, which is strongly associated with the outcome of pregnancy, reflects interplay of several physiological and pathological factors. The assessment of fetal growth is based on comparison of birthweight (BW) or estimated fetal weight (EFW) to standards which define reference ranges at a spectrum of gestational ages. Most birthweight standards do not take into account effects of physiological determinants of fetal growth. Additionally, gestational age in many standards is based on the menstrual history and is often inaccurate. Fetal growth norms should be based on an early ultrasound estimate of gestational age. Customized standards, which have included only ultrasound-dated pregnancies, seem to be superior to population-based birthweight norms in predicting perinatal mortality and morbidity. Adjustment for individual variation in customized growth curves reduces false-positive diagnosis of IUGR and may lead to a very significant reduction in intervention for suspected IUGR. Customized growth potential identifies better the risk for adverse outcome than the currently used national standards, but customized charts may fail in detecting growth-restricted stillbirth. An individual’s birthweight is the sum of physiological and pathological influences operating during pregnancy. Growth potential norms are a better discriminator of aberrations of fetal growth than population, ultrasound, and customized norms.


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