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BACKGROUND: Third trimester fetal anthropometric parameters are known to predict neonatal complications. A better understanding of predictors of adverse fetal parameters might help to personalize the use and frequency of fetal ultrasound. The objectives of this study were: (a) to evaluate the utility of maternal sociodemographic, anthropometric and metabolic predictors to predict 3rd trimester fetal anthropometric parameters in women with gestational diabetes mellitus (GDM), (b) to assess whether the impact of these maternal predictors is fetal sex-dependent, and (c) to provide a risk stratification for markers of fetal overgrowth (fetal weight centile (FWC) and fetal abdominal circumference centile (FACC) depending on prepregnancy BMI and gestational weight gain (GWG) until the 1st GDM visit. METHODS: This prospective study included 189 women with GDM. Maternal predictors were age, ethnicity, prepregnancy BMI, GWG and excessive weight gain until the 1st GDM visit, fasting, 1-hour and 2-hour blood glucose oral glucose tolerance test values, HbA1c at the 1st visit and medical treatment requirement. Fetal outcomes included FWC, FWC >90% and <10%, FACC, FACC >90% and <10%, at 29 0/7 to 35 6/7 weeks of gestational age. We performed univariate and multivariate regression analyses and probability analyses. RESULTS: In multivariate analyses, prepregnancy BMI was associated with FWC, FWC > 90% and FACC. GWG until the 1st GDM visit was associated with FWC, FACC and FACC > 90% (all p ≤ 0.045). Other maternal parameters were not significantly associated with fetal anthropometry in multivariate analyses (all p ≥ 0.054). In female fetuses, only GWG was associated with FACC (p= 0.044). However, in male fetuses, prepregnancy BMI was associated with FWC, FWC > 90% and FACC and GWG with FWC in multivariate analyses (all p ≤ 0.030). In women with a prepregnancy BMI of ≥ 25 kg/m2 and a GWG until the 1st GDM visit ≥ 10.3 kg (mean GWG), the risk for FWC > 90% and FACC > 90% was 5.3 and 4 times higher than in their counterparts. CONCLUSIONS: A personalized fetal ultrasound surveillance guided by fetal sex, prepregnancy BMI and GWG may be beneficial in reducing adverse fetal and neonatal outcomes.
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Diabetes Gestacional , Antropometria , Índice de Massa Corporal , Diabetes Gestacional/epidemiologia , Feminino , Macrossomia Fetal , Humanos , Recém-Nascido , Masculino , Gravidez , Estudos ProspectivosRESUMO
Background: Gestational Diabetes Mellitus (GDM) is frequently associated with chronic, low-grade inflammation. Whether this environment affects offspring anthropometry during early childhood remains to be elucidated. The aim of this study was to investigate the associations between maternal and fetal (cord blood-umbilical artery) inflammatory biomarkers and offspring weight and BMI up to 1 year in pregnancies with GDM. Methods: In this prospective secondary analysis of the MySweetheart study, we included 193 women with GDM and their offspring. Maternal and fetal (N=39) predictors included serum levels of inflammatory biomarkers including CRP, IL-6, and TNF-α at 24-32 weeks of gestational age (GA) and in the cord blood. Offspring outcomes were small and large for gestational age (SGA, LGA), sex- and age-adjusted weight, and BMI at birth and at 1 year. Univariate and multivariate regression models were performed. Associations were adjusted for maternal pre-pregnancy BMI, age, and ethnicity. Results: Mean maternal age was 33.6 ± 4.8 years, and pre-pregnancy BMI 25.9 ± 5.6 kg/m2. Their mean gestational age at the 1st GDM visit was 29 ± 2.4 weeks. Gestational age at delivery was 39.7 ± 1.1 weeks, with a mean birthweight of 3.4 ± 0.46 kg; 11.8% of offspring were LGA and 10.8% were SGA. At 1 year of age, mean offspring weight was 9.8 ± 1.2 kg and BMI z-score 0.23 ± 1.1 kg/m2. In the models including only maternal predictors, TNF-α at 24-32 weeks of GA was positively associated with SGA and inversely with offspring weight and BMI at birth and at 1 year (p ≤0.034). In the models including only fetal predictors and the combined model, CRP was inversely associated with BMI at 1 year (p ≤0.020). Conclusions: In women with GDM, maternal and fetal inflammatory biomarkers distinctively influenced offspring anthropometry during the first year of life, independent of maternal age, prepregnancy BMI and ethnicity. These results suggest that low-grade inflammation during pregnancy may affect the developing offspring by leading to a decrease in weight and BMI and may have implications for future personalized follow-up of women with GDM and their offspring.
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Biomarcadores , Peso ao Nascer , Índice de Massa Corporal , Diabetes Gestacional , Inflamação , Humanos , Feminino , Gravidez , Diabetes Gestacional/sangue , Adulto , Biomarcadores/sangue , Estudos Prospectivos , Recém-Nascido , Inflamação/sangue , Lactente , Masculino , Sangue Fetal/metabolismo , Idade Gestacional , Proteína C-Reativa/metabolismo , Proteína C-Reativa/análise , Peso CorporalRESUMO
Introduction: Gestational Diabetes Mellitus (GDM) carries an increased risk for adverse perinatal and longer-term cardiometabolic consequences in offspring. This study evaluated the utility of maternal anthropometric, metabolic and fetal (cord blood) parameters to predict offspring anthropometry up to 1 year in pregnancies with GDM. Materials and methods: In this prospective analysis of the MySweetheart study, we included 193/211 women with GDM that were followed up to 1 year postpartum. Maternal predictors included anthropometric (pre-pregnancy BMI, gestational weight gain (GWG), weight and fat mass at the 1st GDM visit), and metabolic parameters (fasting insulin and glucose, Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), Quantitative insulin-sensitivity check index (QUICKI), HbA1c, triglycerides, and high-density lipoprotein (HDL) at the 1st visit and HbA1c at the end of pregnancy). Fetal predictors (N=46) comprised cord blood glucose and insulin, C-Peptide, HOMA-IR, triglycerides and HDL. Offspring outcomes were anthropometry at birth (weight/weight z-score, BMI, small and large for gestational age (SGA,LGA)), 6-8 weeks and 1 year (weight z-score, BMI/BMI z-score, and the sum of 4 skinfolds). Results: In multivariate analyses, birth anthropometry (weight, weight z-score, BMI and/or LGA), was positively associated with cord blood HDL and HbA1c at the 1st GDM visit, and negatively with maternal QUICKI and HDL at the 1st GDM visit (all p ≤ 0.045). At 6-8 weeks, offspring BMI was positively associated with GWG and cord blood insulin, whereas the sum of skinfolds was negatively associated with HDL at the 1st GDM visit (all p ≤0.023). At 1 year, weight z-score, BMI, BMI z-score, and/or the sum of skinfolds were positively associated with pre-pregnancy BMI, maternal weight, and fat mass at the 1st GDM visit and 3rd trimester HbA1c (all p ≤ 0.043). BMI z-score and/or the sum of skinfolds were negatively associated with cord blood C-peptide, insulin and HOMA-IR (all p ≤0.041). Discussion: Maternal anthropometric, metabolic, and fetal metabolic parameters independently affected offspring anthropometry during the 1st year of life in an age-dependent manner. These results show the complexity of pathophysiological mechanism for the developing offspring and could represent a base for future personalized follow-up of women with GDM and their offspring.
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Diabetes Gestacional , Resistência à Insulina , Gravidez , Recém-Nascido , Humanos , Feminino , Diabetes Gestacional/metabolismo , Hemoglobinas Glicadas , Peptídeo C , Índice de Massa Corporal , Peso ao Nascer , Antropometria , Insulina , TriglicerídeosRESUMO
INTRODUCTION: Lipedema is a poorly known condition. Diagnosis is based almost exclusively on clinical criteria, which may be subjective and not always reliable. This study aimed to investigate regional body composition (BC) by dual-energy X-ray absorptiometry (DXA) in patients with lipedema and healthy controls and to determine cut-off values of fat mass (FM) indices to provide an additional tool for the diagnosis and staging of this condition. METHODS: This study is a single-center case-control study performed at Lausanne University Hospital, Switzerland. Women with clinically diagnosed lipedema underwent regional BC assessment by DXA. The control group without clinical lipedema was matched for age and body mass index (BMI) at a ratio of 1:2 and underwent similar examination. Regional FM (legs, arms, legs and arms, trunk, android and gynoid FM) was measured in (kg) and divided by FM index (FMI) (kg/m2) and total FM (kg). The trunk/legs and android/gynoid ratios were calculated. For all indices of FM distribution showing a significant difference between cases and controls, we defined the receiver operating characteristic (ROC) curves, calculating the area under the curve (AUC), sensitivity, specificity, and Youden's index. Types and stages of lipedema were compared in terms of FM indices. Correlation analyses between all FM distribution indices and lipedema stages were performed. RESULTS: We included 222 women (74 with lipedema and 148 controls). Overall, the mean age was 41 years (standard deviation [SD] 11), and mean BMI was 30.9 kg/m2 (SD 7.6). A statistically significant difference was observed for all DXA-derived indices of FM distribution between groups, except for arm FM indices. The ROC curve analysis of leg FM/total FM, as a potential indicator of lipedema, resulted in an AUC of 0.90 (95% confidence interval 0.86-0.94). According to Youden's index, optimal cut-off value identifying lipedema was 0.384. Sensitivity and specificity were 0.95 and 0.73, respectively. We found no significant differences between lipedema types and stages in terms of FM indices, nor significant correlations between the latter and lipedema stages. DISCUSSION/CONCLUSION: BC assessment by DXA, and particularly calculation of the leg FM/total FM index, is a simple tool that may help clinicians rule out lipedema in doubtful cases.
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Lipedema , Humanos , Feminino , Adulto , Absorciometria de Fóton , Lipedema/diagnóstico por imagem , Estudos de Casos e Controles , Composição Corporal , Índice de Massa CorporalRESUMO
The objectives of this study were to (a) assess the utility of fetal anthropometric variables to predict the most relevant adverse neonatal outcomes in a treated population with gestational diabetes mellitus (GDM) beyond the known impact of maternal anthropometric and metabolic parameters and (b) to identify the most important fetal predictors. A total of 189 patients with GDM were included. The fetal predictors included sonographically assessed fetal weight centile (FWC), FWC > 90% and <10%, and fetal abdominal circumference centile (FACC), FACC > 90% and < 10%, at 29 0/7 to 35 6/7 weeks. Neonatal outcomes comprising neonatal weight centile (NWC), large and small for gestational age (LGA, SGA), hypoglycemia, prematurity, hospitalization for neonatal complication, and (emergency) cesarean section were evaluated. Regression analyses were conducted. Fetal variables predicted anthropometric neonatal outcomes, prematurity, cesarean section and emergency cesarean section. These associations were independent of maternal anthropometric and metabolic predictors, with the exception of cesarean section. FWC was the most significant predictor for NWC, LGA and SGA, while FACC was the most significant predictor for prematurity and FACC > 90% for emergency cesarean section. In women with GDM, third-trimester fetal anthropometric parameters have an important role in predicting adverse neonatal outcomes beyond the impact of maternal predictors.
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Based on the Hyperglycemia and Adverse Pregnancy Outcome study, new universal screening recommendations and cut-offs for gestational diabetes mellitus (GDM) have been proposed. In addition to the immediate perinatal risk, GDM carries an increased risk of metabolic disease in the mother and child. Maternal obesity has even been shown to be associated with increased all-cause mortality in offspring. In addition to known risk factors, excessive gestational weight gain, increased fat consumption, a low vitamin D level, psychological stress and negative mood are risk factors for GDM. Regarding therapy, the US Preventive Task Force concluded in 2013 that GDM treatment significantly reduces the risks of pre-eclampsia, macrosomia and shoulder dystocia (relative risks of 0.62, 0.5 and 0.42, respectively). Although nutrition therapy represents a cornerstone in GDM management, the results of studies are not clear regarding which types of dietary advice are the most suitable. Most physical activity interventions improve glucose control and/or reduce insulin use. Recent studies have evaluated and provided more information about treatment with metformin or glyburide. Postpartum management is essential and should focus on long-term screening and diabetes prevention strategies.