Fetal Growth Curves Research Articles

Effect of Race in the Diagnosis of Fetal Growth Restriction in a Multicultural Urban Population [A202

INTRODUCTION: Despite significant differences in fetal growth curves based on maternal race/ethnicity, fetal growth restriction (FGR) continues to be defined by the Hadlock formula generated from a study involving 392 predominantly White pregnancies. Accuracy in FGR diagnosis is crucial to prevent iatrogenic preterm delivery and unnecessary antenatal surveillance and intervention. We sought to compare the diagnostic accuracy of FGR in fetuses classified by Hadlock criteria versus Eunice Kennedy Shriver National Institute of Child Health and Human Development racial/ethnic-stratified criteria in a multicultural urban population. METHODS: A retrospective recalculation of estimated fetal weight (EFW) and abdominal circumference (AC) in fetuses diagnosed with FGR over a 5-year period using NICHD race-specific fetal growth criteria was performed. FGR was defined as EFW or AC less than 10th percentile. Chi-square analysis was performed to evaluate the differential effects of recalculation across racial groups. RESULTS: A total of 384 pregnancies with FGR were identified in 147 (38.3%) Asian, 114 (29.67%) Hispanic, 111 (28.9%) Black, and 12 (3.3%) White mothers. Recalculation normalized growth in 64 (16.7%) pregnancies and was disproportionate, with the greatest effect in pregnancies of Black mothers (29, 26.1%), followed by Hispanic mothers (17, 14.9%) and Asian mothers (18, 12.2%) (P=.01). CONCLUSION: Application of NICHD race-specific criteria reversed the diagnosis of a substantial number of FGR pregnancies, with the greatest reversal seen in pregnancies of Black mothers. More research is needed to evaluate the neonatal and long-term outcomes of fetuses misdiagnosed as FGR based on the old growth standards, as iatrogenic preterm delivery and steroid administration carry potential morbidity later in life.

Automated segmentation analysis of 3DUS placental volumes yields an early biomarker of fetal growth potential

Placental volume (PV), obtained by 3D ultrasound (3DUS) as early as the first trimester, have been associated with fetal growth outcomes, such as small for gestational age and macrosomia. However, significant, manual post-processing is generally required to obtain a volume measure, limiting the potential for PV to serve a clinical role. Recently, we have developed and validated an automated segmentation algorithm, based on convolutional neural networks that can calculate PV without any manual input. Herein, we sought to determine if automated early PV measures are associated with birthweight and neonatal anthropometric measures of fat deposition. In this prospective cohort, 3DUS volume sets of the placenta were obtained at 11-16 weeks gestation and followed to delivery. Neonatal birth weight (BW) and centile (BW%) were recorded. When feasible, trained research staff obtained neonatal length (BL), head (HC), abdominal (AC), right upper mid arm (RAC) circumferences within 48 hours of birth. 3DUS volumes were processed using the automated segmentation algorithm to yield a PV measure, which was then normalized to gestational age (PVGA). Data was analyzed to determine any associations between PV and PVGA with neonatal measures. 96 singleton pregnancies were included with a mean PV of 91.6 (SD:28.8) cc obtained at a mean GA of 13.9 (1.04) wks. Mean GA at delivery was 38.7(1.6) wks with mean BW of 3122 (528) gm. PV and PVGA were both significantly correlated with BW and BW%. 52 subjects underwent neonatal anthropometry. PV and PVGA were significantly correlated with neonatal BL, HC, and RAC. Table. This study demonstrates that an automated segmentation tool that estimated early placental volume can yield an early biomarker of fetal growth potential. Despite numerous large studies aimed at customizing fetal growth curves, there remains no universally validated tool. An automated tool that delivers an early biomarker of an individual fetus’ growth potential has the potential for achieving a precision medicine approach for monitoring fetal growth and guiding surveillance.

Ultrasound fetal biometry in third trimester in urban Nepalese population

INTRODUCTION: Fetal biometry is an important component of fetal growth surveillance and can detect small for gestation age fetuses. However, we use growth curves from studies done in other high-income countries and do not have a standard of our own. This study aims to study the deviation of biometry and expected fetal weight from these curves in pregnancy with normal birth weight term deliveries.
 METHODS: The study was a retrospective hospital record-based study including term delivery from 2018 May to 2020 January. All lowrisk patients visiting ultrasound OPD in our hospital in 3rd trimester were retrieved and included in the study. Patient with low AFI, major fetal anomaly, abnormal fetal heart rate, preterm delivery, birth weight less than 2500 gm (low birth weight), intrauterine fetal demise, preeclampsia or other complications were excluded from the study. Fetal biometry and expected fetal weight were evaluated. Data was entered in predesigned performa and analysis was performed with IBM SPSS 20.0.
 RESULTS: A total of 590 ultrasound examinations done in 372 patients were included in the study. Mean age of the patients was 30.78+/-3.98 years, median age was 30 years (IQ range-5). Approximately 316(53.6%) patients were under 30 years of age, 198(33.6%) patients were between 30-35 and 76(12.9%) patients were above 35 years. Median gestational age at birth was 39 weeks and median birth weight was 3120 grams. Median and percentile for various biometry was calculated. EFW was below 50th percentile in 424(71.9%) according to WHO chart. The median percentile for EFW was 30.6 (IQ-33.6).
 CONCLUSION: Expected fetal weight in Nepalese population is smaller than that predicted by WHO chart. Development of country specific fetal growth curve is recommended for accurate fetal growth surveillance.

Reconsidering upstream approaches to improving population health

Racial and socioeconomic disparities in health outcomes have been well documented. 1 Blumenshine P Egerter S Barclay CJ Cubbin C Braveman PA Socioeconomic disparities in adverse birth outcomes: a systematic review. Am J Prev Med. 2010; 39: 263-272 Summary Full Text Full Text PDF PubMed Scopus (477) Google Scholar , 2 Matoba N Collins Jr, JW Racial disparity in infant mortality. Semin Perinatol. 2017; 41: 354-359 Crossref PubMed Scopus (43) Google Scholar Although overall global rates of poor birth outcomes have decreased, decades of research and interventions have not eliminated disparities. However, much intervention research has focused on individual-level risk factors and groups at high risk. In The Lancet, Jennifer Jardine and colleagues 3 Jardine J Walker K Gurol-Urganci I et al. Adverse pregnancy outcomes attributable to socioeconomic and ethnic inequalities in England: a national cohort study. Lancet. 2021; (published online Nov 1.)https://doi.org/10.1016/S0140-6736(21)01595-6 Summary Full Text Full Text PDF PubMed Scopus (7) Google Scholar report on population attributable fractions, which indicate the proportion of a particular outcome that would be removed if a risk factor did not exist or was more similar to a reference population. The use of population attributable fractions is an important contribution because it demonstrates the excess risk of poor outcomes that can be attributed to population-level factors. The authors provide a potential roadmap for future interventions, emphasising the role of widespread health promotion in improving population-level health metrics over targeted, individual-level interventions that have less population impact. 4 Rose G Sick individuals and sick populations. Int J Epidemiol. 1985; 14: 32-38 Crossref PubMed Scopus (2188) Google Scholar This study 3 Jardine J Walker K Gurol-Urganci I et al. Adverse pregnancy outcomes attributable to socioeconomic and ethnic inequalities in England: a national cohort study. Lancet. 2021; (published online Nov 1.)https://doi.org/10.1016/S0140-6736(21)01595-6 Summary Full Text Full Text PDF PubMed Scopus (7) Google Scholar included 1·16 million singleton births in England, which represented 94% of England's births obtained from administrative hospital data linked to the National Maternity and Perinatal Audit between 2015 and 2017. The authors report that 24% of stillbirths, 19% of preterm births, and 31% of fetal growth restriction could be attributed to socioeconomic inequality. The women included in the sample were 77·2% White, 11·9% south Asian, 4·9% Black, 1·8% mixed ethnicity, and 4·2% other ethnicity. Perhaps most striking were the authors’ findings on the intersection of race and socioeconomic disadvantage, describing that more than half of stillbirths, a third of preterm births, and nearly two-thirds of fetal growth restriction among south Asian and Black women could be eliminated if their risk factors were equal to the least socioeconomically deprived White women. The authors suggest that this finding supports a combination of population-based and risk-based approaches, but does not consider the inextricable link between ethnic background and socioeconomic deprivation. 5 Kane JB Miles G Yourkavitch J King K Neighborhood context and birth outcomes: going beyond neighborhood disadvantage, incorporating affluence. SSM Popul Health. 2017; 3: 699-712 Crossref PubMed Scopus (17) Google Scholar Additionally, the association between race or socioeconomic inequality and birth outcomes might vary because of factors like social support and experiences of racism and discrimination. In combination with the limitation of using an area-level index of deprivation, the authors acknowledge potential inaccuracies and bias in the population attributable fractions. 6 Mansournia MA Altman DG Population attributable fraction. BMJ. 2018; 360: k757 Crossref PubMed Scopus (114) Google Scholar They rightfully note that more detailed causal mediation analysis is a research priority. Moreover, because the definition of fetal growth restriction varies by the reference used, which itself varies by ethnic mix in the index population, 7 Grantz KL Fetal growth curves: is there a universal reference?. Obstet Gynecol Clin North Am. 2021; 48: 281-296 Summary Full Text Full Text PDF PubMed Scopus (2) Google Scholar interpretations of this outcome are unclear. Indeed, the authors may be capturing small-for-gestational age rather than fetal growth restriction, which may not indicate pathology. Adverse pregnancy outcomes attributable to socioeconomic and ethnic inequalities in England: a national cohort studyOur results indicate that socioeconomic and ethnic inequalities were responsible for a substantial proportion of stillbirths, preterm births, and births with FGR in England. The largest inequalities were seen in Black and South Asian women in the most socioeconomically deprived quintile. Prevention should target the entire population as well as specific minority ethnic groups at high risk of adverse pregnancy outcomes, to address risk factors and wider determinants of health. Full-Text PDF

Chinese Fetal Growth: A Multicenter Cohort Study Based on Fetal Ultrasound Measurements

Abstract Objective To build a reference fetal growth chart for the Chinese population based on fetal ultrasound measurements. Methods This was a multicenter, population-based retrospective cohort study. Longitudinal ultrasound measurement data were collected from 24 hospitals in 18 provinces of China from 1st September through 31st October of 2019. The estimated fetal weight (EFW) was calculated based on head circumference, abdominal circumference, and femur length using Hadlock formula 3. Fetal growth curves were estimated using a two-level linear regression model with cubic splines. All participants were divided into two groups: the northern group (n = 5829) and the southern group (n = 3246) based on the geographical division of China and male fetus group (n = 4775) and female fetus group (n = 4300) based on fetal gender. The EFW was compared by fetal gender and geographical group. All statistical models were adjusted for maternal sociodemographic characteristics. Results A total of 9075 participants with 31,700 ultrasound measurement records were included in this study. Male fetuses demonstrated significantly larger EFW compared to female ones starting at 16 weeks of gestation and extending to delivery (global test P < 0.01). The overall geographic difference in EFW was significant (global test P = 0.03), and week-specific comparisons showed that the northern group had a greater EFW starting at 15 weeks of gestation and extending to 29 weeks of gestation, although this difference did not extend to the time of delivery. The Z-score of EFW confirmed that our Chinese fetal growth charts differed from previously published standards. Conclusion This study provides EFW and ultrasound biometric reference measurements for Chinese fetuses and reveals differences from other fetal growth charts. The chart is worth promoting in more regions of China but should be tested prudently before use.

Fetal growth trajectory in type 1 pregestational diabetes (PGDM) — an ultrasound study

Growth disorders are frequent in diabetic pregnancies. However, they are difficult to predict and capture early during pregnancy. These newborns are at risk of obesity, diabetes, and cardiovascular disease. While developing, fetal growth abnormalities are typically progressive. Therefore, capturing the earliest moment when they emerge is essential to guide subsequent obstetric management. We aimed to analyze fetal ultrasound growth trajectories in type 1 diabetics. Moreover, we aimed to establish time points when first ultrasound manifestations of fetal growth abnormalities appear and to identify factors that affect fetal growth in women with diabetes. We collected clinical and ultrasound data from 200 patients with PGDM managed in the third-referential centre for diabetes in pregnancy. During every visit, patients underwent an ultrasound examination according to a standard protocol giving 1072 ultrasound scan's records. Every ultrasound consisted of fetal weight estimation, according to the Hadlock 3 formula. Retrospectively patients were divided into three groups depending on neonatal weight. In the group of 200 patients, 60 (30%) delivered LGA and 9 (4.5%) SGA newborns. Fetal growth trajectories show different patterns among fetuses with growth abnormalities in women with type 1 diabetes. The moment, when fetal growth curves diverge, seems to take place in the second trimester, just after the 23rd week of gestation. It suggests that fetal growth abnormalities in type 1 diabetes may have its roots much earlier than expected. In the first trimester, there were differences in LDL-cholesterol, total cholesterol, triglyceride levels and in insulin requirements between AGA, SGA and LGA subgroups.

Fetal growth prediction: Establishing fetal growth prediction curves in the second trimester.

BACKGROUND: Monitoring fetal weight during pregnancy has a guiding role in prenatal care.OBJECTIVE: To establish a personalized fetal growth curve for effectively monitoring fetal growth during pregnancy.METHODS: (1) This study retrospectively analyzed the birth weight database of 2,474 singleton newborns delivered normally at term. The personalized fetal growth curve model was formed by combining the estimating birth weight of newborns with the proportional weight formula. (2) Multiple linear stepwise regression method was used to estimate the birth weight of newborns.RESULTS: (1) Delivery gestational age, weight at first visit, maternal height, pre-pregnancy body mass index, fetal sex, parity had significant effects on birth weight. Based on these parameters, the formula for calculating term optimal weight was obtained ( 22.8%, 0.001). (2) The personalized fetal growth curve was obtained according to the epidemiological factors input model of each pregnant woman.CONCLUSIONS: A model of personalized fetal growth curve can be established, and be used to evaluate fetal growth and development through estimated fetal weight monitoring.

Establishment of a personalized fetal growth curve model.

BACKGROUND: Fetal weight is one of the important indicators for judging whether fetal growth and development are normal. Fetal weight exceeding the normal range may lead to poor delivery outcomes.OBJECTIVE: We aimed to establish a personalized fetal growth curve in order to effectively monitor fetal growth during pregnancy. Fetal weight can be monitored while fetal growth and development are assessed.METHODS: This study retrospectively analyzed the birth weight and ultrasound database of 3,093 newborns delivered at normal term. The personalized fetal growth curve model was generated based on the birth weight formula established by Gardosi combined with the proportional weight equation.RESULTS: (1) The average birth weight of the single fetus at normal term was 3,457g. (2) According to the regression results of the proportion of fetal weight in full-term pregnancy and gestational week, the proportional weight equation is Weight% 500.9 51.60GA 1.727GA 0.01718GA (GA is gestational week), is 98%, 0.001.CONCLUSIONS: In this study, the normal birth weight of newborns and normal range of fetal weight can be estimated by using the personalized fetal growth curve model.

260 Antepartum and delivery outcomes for growth-restricted fetuses based on gastroschisis-specific fetal growth curves

To determine the utility of gastroschisis-specific fetal growth curves by evaluating antepartum and delivery outcomes for fetuses with fetal growth restriction (FGR) based on Hadlock growth curves compared to gastroschisis-specific growth curves. This was a single-institution, retrospective cohort study of pregnancies complicated by isolated gastroschisis delivered between 2011 and 2020. Using ultrasound biometric data, we generated estimated fetal weight growth curves specific to fetuses with gastroschisis, including the 10th, 50th, and 90th percentiles between 15 and 37 weeks. We compared antepartum and delivery outcomes for fetuses diagnosed with FGR by Hadlock growth curves to fetuses diagnosed with FGR by gastroschisis growth curves. 413 ultrasounds from 116 fetuses were included. 67 (58%) of the fetuses met criteria for FGR based on Hadlock growth curves, and 28 (24%) met criteria based on the gastroschisis growth curves. 60% of fetuses diagnosed with FGR by Hadlock were misdiagnosed based on the new growth curves. When comparing fetuses with FGR by Hadlock to those with FGR by the gastroschisis curves, the new curves better predicted 5 out of 16 observed outcomes, including: increased betamethasone administration (52% vs 45%, p=0.001), decreased spontaneous vaginal delivery (43% vs 51%, p<0.001), increased cesarean delivery (54% vs 49%, p=0.001), increased unplanned hospital admission (96% vs 82%, p<0.001), and worsening bowel findings leading to delivery (39% vs 28%, p=0.033). Hadlock growth curves derived from non-anomalous fetuses over-diagnose FGR in fetuses with gastroschisis due to small abdominal circumference measurements caused by abdominal organ herniation. FGR defined by gastroschisis-specific growth curves better predicts many of the common perinatal outcomes seen in pregnancies complicated by this anomaly. Given the known risks of prematurity, using gastroschisis-specific growth curves may assist in improved risk stratification and delivery planning among cases of gastroschisis.

Updated Gestational Age Specific Birthweight Reference of Hong Kong Chinese Newborns and Comparison with Local and International Growth Charts

Background: Different gestational age specific birthweight reference charts have been produced for different populations and ethnic groups over different time periods, mostly based on birthweight data. This study aims to update birthweight references for Hong Kong (HK) Chinese newborns to provide norms for identification of small and large for gestational age (SGA and LGA) fetuses, and to verify whether there are significant differences compared to previously published local reference charts, as well as to other southern Chinese and international data. Methods: All singleton Chinese livebirths delivered in United Christian Hospital from 2012 to 2017 were retrospectively included. The smoothed birthweight centiles at each gestation were computed. The birthweight centiles were then compared with other reference charts. Results: A total of 25,508 livebirths between 24 and 42 completed weeks of gestation were enrolled in the final analysis. The mean birthweights of our cohort were largely similar to previous studies at each gestation, but the 10th and 90th centile ranges differed significantly, so that the proportion of babies that would be classified as SGA or LGA varied widely using cut-offs from different studies. Older local studies tend to under-estimate, while the international growth charts would over-estimate the proportion of SGA babies. Conclusions: Updating fetal growth curve references based on local data is essential to establish more precise definitions of SGA and LGA babies in clinical management. The use of international growth charts in our population may not be appropriate and requires further validation.

Outcome dependent growth curves for singleton pregnancies based on birth weight of babies for Polish population.

To create outcome dependent fetal growth curves and birth weight standards that can be analyzed for use in clinic specifically for Western European populations. We conducted a retrospective study on fetal growth and birth weight trends from live birth singleton pregnancies between 2005 and 2018 at one of the largest tertiary gynecologic-obstetric hospitals in Poland. The inclusion criteria were at least 22 weeks of gestation at birth regardless of delivery mode (vaginal or C-section), no congenital anomalies diagnosed before and after delivery and an Apgar score of at least 7 in the first minute. The final sample had a total of 39,413 cases (18,562 girls and 20,851 boys). We presented 7 (for all fetuses in the 5th, 10th, 25th, 50th, 75th, 90th and 95th percentiles) and 6 (for boys and girls each at 10th, 50th and 90th percentiles) fetal growth curves between 25 and 40 weeks of gestation. Birth weight trends were obtained and analyzed from all babies in the 5th, 10th, 25th, 50th, 75th and 95th percentiles born between 22 to 42 weeks of gestation with also separate trends for boys and girls. The largest differences in fetal growth curves were observed in the 10th and 50th percentiles between 22 and 34 weeks of gestation. A decreasing fetal weight gain pattern was observed between 27 and 30 weeks and after 38 weeks of gestation, the decrease was more drastic in female. A significant increase from 2009 to 2017 was observed in the weight of 50th percentile babies born at or after 35 weeks. We found significant discrepancies between our results and the most used European fetal growth curves particularly in the 10th and 90th percentile weights at 30 weeks. Separate scales for boys and girls were implied and given the overall difference form commonly used references. We believe there is significant value in using these unique patterns found in fetal growth curves and birth weights of ethnically homogenous population (such as Poland) at everyday clinical practice for more opportunities of safe obstetric care and higher chances of delivering a healthy child.

Sonographic growth curves versus neonatal birthweight growth curves for the identification of fetal growth restriction

Objective Fetal growth restriction is suspected when the estimated fetal weight is <10th percentile for gestational age. Using a regional sonographic estimated fetal weight growth curve to diagnose fetal growth restriction has no known benefits; however, the traditional approach of using birthweight curves is misleading, since a large proportion of preterm births arise from pathological pregnancies. Our aim was to compare the diagnostic accuracies of sonographic versus birthweight curves in diagnosing fetal growth restriction. Our secondary aim was to compare maternal, fetal and neonatal outcome based on these two approaches. Methods Retrospective study based on computerized medical records. Included were women with a singleton pregnancy, that underwent fetal biometry between 24 and 36.6 weeks' gestation (January 2010–February 2016) and delivered in our center. Each pregnancy was assigned to one of three groups based on the earliest sonographic estimated fetal weight performed: G1—Appropriate for gestational age, G2—fetal growth restriction based on sonographic but not birthweight curves; or G3—fetal growth restriction based on birthweight growth curves. Demographics, obstetric characteristics, ultrasound data, and neonatal data were retrieved and compared between groups. Primary outcome: rate of small for gestational age neonates in each group. Secondary outcomes were various adverse maternal and neonatal outcomes. Results Six thousand and five pregnancies met inclusion criteria. Of these 5386 (89.6%) were categorized as G1, 300 (5%) as G2 and 319 (5.3%) as G3. The rate of small for gestational age neonates differed significantly between groups: G1 9.2%, G2 39.7% and G3 70%. Multivariable logistic regression modeling reiterated these rates: the odds ratios for small for gestational age were 6.47 [95% CI 4.99–8.40] and 23.99 [95% CI 18.26–31.51] for G2 and G3 respectively. Prediction of small for gestational age based on sonographic EFW curves increased the sensitivity for detection of SGA from 26% to 41% with a slight decrease in specificity from 98% to 95%, and a decrease of the positive likelihood ratio from 18.4 to 7.7, however there was no significant change in the overall test accurcy; 88.5% to 87.1%. Secondary outcomes also differed between groups: G2 and G3 had similar rates of maternal and neonatal morbidities and most parameters were higher than G1. G2 and G3 showed lower mean gestational age at delivery (36.2 weeks and 35.9 weeks vs.37.8; p < .0001), and higher rates of preterm delivery (40% and 51.7% vs. 21.5%; p < .001), as well as higher rates of intrauterine fetal demise 3% in G2, 6.9% in G3 and 0.9% in G1, p < .0001. Conclusion Pregnancies that are currently managed as appropriate for gestational age based on birthweight curves, but classified as growth restricted when prenatal sonographic curves are used, are associated with higher rates of small for gestational age and poor perinatal outcomes, at rates comparable to pregnancies that are classified as growth restricted based on birthweight curves. Furthermore, applying sonographic curves increases the sensitivity for detection of small for gestational age neonates. Consequently, consideration should be given to the use of sonographic biometry curves for defining fetal growth restriction.

Caveats in the monitoring of fetal growth using ultrasound estimated fetal weight.

Ultrasound estimated fetal weight is increasingly being used in the monitoring of fetal growth. Differences between estimated fetal weight formulae, curves and measurement methods could lead to significant differences in results. The aim of this study was to investigate the potential impact of these differences on estimated fetal weight and its use in monitoring fetal growth, both by modelling and by analysis of ultrasound scan data. Four estimated fetal weight curves were compared in their original form and also normalised to term weight. Estimated fetal weight was calculated from 50th centiles of widely used charts of abdominal and head circumference and femur length and plotted on a widely used estimated fetal weight curve. Fetal measurement data were used to assess the impact of fetal proportions on estimated fetal weight error and on growth trajectory when different estimated fetal weight formulae are used. Estimated fetal weight curves differ significantly, but after normalisation there is closer agreement. Estimated fetal weight modelled using modern measurement methods differs from the widely used estimated fetal weight growth curve. Errors in estimated fetal weight are correlated with differences in fetal proportions and this can lead to significant changes in estimated fetal weight growth trajectory if different estimated fetal weight formulae are used. Choice of measurement methods, estimated fetal weight formulae and growth curves have a significant effect on estimated fetal weight growth trajectories relative to normal ranges. It is important to understand these caveats when using estimated fetal weight to monitor fetal growth.

Fetal brain ultrasound measures and maternal nutrition: A feasibility study in Ecuador.

Nutrition during pregnancy is an important modifiable determinant of fetal growth and development. This pilot study aimed to characterize the association between fetal anthropometry, fetal brain development, and maternal diet among women in Ecuador using portable ultrasound in resource-limited clinics, including measurements of brain structures not typically imaged in this setting. Pregnant women (n = 47) from four resource-limited health centers were surveyed on demographic, socioeconomic, morbidity, and dietary information. Maternal height, weight, and blood pressure were taken. A sonographer took 15 images per participant, including those standardly assessed during the fetal survey and additional brain structures identified as potentially responsive to maternal nutrition, but not part of the standard fetal survey. Mean percentiles for all standard fetal survey measurements generated from WHO Fetal Growth Curves fell below 50%, and negative mean Z scores were found for biparietal diameter (-0.95 ± 1.11) and femur length (-0.22 ± 1.10). Generalized linear modeling adjusting for gestational age and other covariates showed frequency of seafood consumption was positively associated with fetal biparietal diameter Z score (P = 0.005), beans and legumes positively associated with femur length (P = 0.006), and a negative association was found for soda consumption and fetal head circumference (P = 0.013). This pilot study demonstrated the feasibility of capturing images of nutrition-relevant fetal brain structures not part of the standard fetal survey in resource-limited settings using portable ultrasound. Our study revealed associations between anthropometry, brain structure size, and maternal diet demonstrating potential for prenatal nutrition research using ultrasound in the field.

Outcome dependent twin growth curves based on birth weight percentiles for Polish population

Objective The objective of this study is to determine a healthy fetal growth pattern of twins from a Polish population based on an outcome-dependent growth curve. Methods The fetal growth data of live-born twin pregnancies between 25th and 40th week gestation in the period of 1 January 2005 to 31 March 2018 from the database of a tertiary care women’s hospital in Western Poland was used to calculate birth weight percentiles. The growth curves of singletons from the same database were used as comparison. Because this study aimed for an outcome-dependent approach for the calculation of fetal growth curves, all babies born that may have high risk of unfavorable outcome were excluded. After application of all exclusion criteria, 1317 records referring to 2634 children were included in our analysis. Growth curves of singletons from the same database were used as reference for this study. Results A linear relationship between 10th, 50th, and 90th percentiles and gestational age were found for twins but not for singletons suggesting the different mechanisms of intrauterine growth between singleton and twin pregnancies. Week-to-week weight gain equal to or higher than 150 g in twins also predict a favorable outcome in absence of other pathologies. Conclusion The calculated outcome-dependent fetal growth curves for twins in this study may help in the accurate diagnosis of small or large twin fetuses for their gestational age in this Western Poland population.

\u201cINTERGROWTH21st vs customized fetal growth curves in the assessment of the neonatal nutritional status: a retrospective cohort study of gestational diabetes\u201d

BackgroundGestational diabetes mellitus is associated with increased incidence of adverse perinatal outcomes including newborns large for gestational age, macrosomia, preeclampsia, polyhydramnios, stillbirth, and neonatal morbidity. Thus, fetal growth should be monitored by ultrasound to assess for 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.MethodsThis 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. The nutritional status of newborns was assessed using the ponderal index. 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.ResultsTwo hundred thirty-one 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 INTERGROWTH21st 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%).ConclusionsIn pregnant women with DMG, the ability of customized fetal growth curves to identify newborns with alterations in nutritional status appears to exceed that of INTERGROWTH21st.

Neonatal morbidity and small and large size for gestation: a comparison of birthweight centiles.

To compare rates of small- and large-for-gestational age (SGA and LGA) neonates using four different weight centiles, and to relate these classifications to neonatal morbidity. Neonates born at 33-40 weeks' gestation in a multiethnic population were classified as SGA or LGA by population reference (Fenton), population standard (INTERGROWTH), fetal growth curves (WHO), and customized (GROW) centiles. Likelihood of composite morbidity was determined compared with a common appropriate-for-gestational age referent group. Among 45,505 neonates, SGA and LGA rates varied up to threefold by different centiles. Those most likely to develop neonatal morbidity were SGA or LGA on both the population reference and an alternative centile. Customized centiles identified over twice as many at-risk SGA neonates. Customized centiles were most useful in identifying neonates at increased risk of morbidity, and those that were small on both customized and population reference centiles were at the highest risk.

734: Which fetal growth curve best predicts a small for gestational age infant in obese women?

To determine if prediction of small for gestational age (SGA) infants using standardized ultrasound growth curves (GC) is affected by maternal obesity and which GC performs best in obese women. Retrospective cohort study from 6/1/18 to 6/1/19 of all growth ultrasounds performed from 30+0 to 32+6 weeks at a single institution. Multifetal gestations and intrauterine fetal demises were excluded. We determined the estimated fetal weight (EFW) for all patients using four clinically utilized GCs (Hadlock, Brenner, Hadlock abdominal circumference (AC) alone, and Brenner plus AC (B + AC)). We defined fetal growth restriction (FGR) as EFW < 10th percentile for Hadlock and Brenner or AC < 5th percentile for AC. SGA was defined as birthweight < 10th percentile by WHO or Fenton GCs. The primary outcome was the impact of maternal obesity (BMI ≥30 kg/m2) on the ability of each GC to predict SGA and to determine which GC performs best in obese women. Predictive characteristics were calculated for each GC and the area under the receiver operating characteristic curve (AUC) was compared between non-obese and obese patients. Within the obese patients, the AUC was compared between all four GCs. Of 763 patients included, 77 infants (10.3%) were SGA. Obese women were significantly less likely to deliver an SGA infant (p< 0.01). Maternal obesity significantly decreased the ability of Hadlock to predict SGA compared to non-obese patients (AUC 0.58 (95%CI 0.48-0.69) vs AUC 0.73 (95%CI 0.66-0.79), p=0.02) (Fig 1). There was no significant difference in the ability of the other GCs to predict SGA between obese and non-obese women. In obese patients, there was no significant difference between ability of the GCs to predict SGA (p=0.41) (Fig 2). Brenner identified no cases of FGR in obese patients. In non-obese women, Hadlock outperformed the other three GCs (p< 0.01) (Fig 2). Maternal obesity decreases the ability of the Hadlock GC to predict SGA infants. Among obese women, no GC is significantly more predictive of SGA infants. All performed poorly in the obese population.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Breeding and calving seasonality in the endangered Cook Inlet beluga whale population: Application of captive fetal growth curves to fetuses and newborns in the wild

Breeding and calving seasonality in the endangered Cook Inlet beluga whale population: Application of captive fetal growth curves to fetuses and newborns in the wild

Longitudinal study of individually adjusted fetal growth.

To construct individualized fetal growth curves estimated by ultrasound parameters adjusted for maternal and fetal characteristics. Data were retrospectively assessed from serial ultrasonographic examinations of singleton pregnancies at 12-42 gestational weeks among women without maternal or fetal conditions and full-term delivery at the University Hospital of University of São Paulo between July 1, 2014, and December 31, 2017. Measurements included biparietal diameter, head circumference, abdominal circumference, and femur length. Mixed linear regression was used to model the ultrasound biometric parameters as a function of gestational age, parity, maternal height, pre-pregnancy weight, and fetal sex. In total, data were assessed from 1445 examinations of 434 pregnancies meeting the inclusion criteria. The estimated fetal weight model included gestational age, fetal sex, maternal height, and pre-pregnancy body mass index as covariates. The model enabled the construction of individual estimated fetal weight curves with respective percentiles covering 12-42 gestational weeks using maternal and fetal characteristics. The growth curves, which are based on a sample of the Brazilian population with low risk of maternal or fetal morbidity and mortality, will make it possible to determine whether a fetus is achieving ideal growth potential according to maternal and fetal characteristics.