A practical guide to understanding fetal growth and newborn birthweight charts

Objectives: To compare fetal and neonatal growth charts pertaining to different models (population-specific, universal reference, universal standard and fully customised) in detecting suboptimal fetal growth in the third trimester. Methods: This was a prospective observational study conducted at two fetal medicine centers. After applying the inclusion criteria [singleton pregnancies between 28 and 40 weeks, verified dates and estimated fetal weight (EFW) ≤ 25th centile as per the Hadlock chart], 292 women were consecutively recruited. Four fetal growth charts (Hadlock, Intergrowth, fully customised GROW, Sonocare) and three neonatal charts (Fenton, Intergrowth and fully customised GROW) were used in the study. The EFW and birthweight centiles were categorized into three groups: < 3.0, 3.1–10th and > 10th centiles. The charts were evaluated by their ability to detect pregnancies with uteroplacental insufficiency and/or development of adverse neonatal outcomes in the third trimester. Results: Significant difference was noted between the fetuses/neonates assigned as < 3rd centile (Hadlock-9.3%, Sonocare-4.8%, Intergrowth- 6.8% and the fully customised GROW- 6.5%) and the neonatal charts (Fenton-18.5%, Intergrowth- 20.2% and fully customised GROW- 13.4%). At a cut-off of 3rd centile, the GROW chart had the highest sensitivity (84.2%) followed by Intergrowth (78.9%), Hadlock (70.37%) and Sonocare (64.29%). Similarly, for a cut-off of < 10th, the sensitivity was GROW 70.27%, Sonocare 64%, Intergrowth 60.8% and Hadlock 50%. Amongst the neonatal charts, fully customised GROW chart had the greatest detection rate (< 3rd = 74.36%, < 10th = 70.27%). However, there was no significant difference between the charts in the detection of pregnancies with suboptimal fetal growth associated with uteroplacental insufficiency and/or adverse neonatal outcomes. Conclusion: Despite substantial discrepancy between the growth charts in diagnosing fetal smallness, adding multivessel Doppler negates significant differences between them in diagnosing suboptimal fetal growth associated with uteroplacental insufficiency and adverse neonatal outcomes.

The World Health Organization fetal growth charts: concept, findings, interpretation, and application.

Early fetal growth: concepts and pitfalls

Objectives: Different retrospective growth charts for twin pregnancies debates whether twin growth is similar to singletons. Recently, the fetal medicine foundation (FMF) published a retrospective fetal growth chart that indicated similar growth charts for twins and singleton if only term delivery of both twins without major malformation are included. A national Denish growth chart confirmed these finding. We constructed prospective growth chart of estimated fetal weight (EFW) throughout pregnancy of monochorionic diamniotic (MCDA) and dichorionic (DC) twins using a multi-center, multi-national cohort. Study Design: Pregnancies with two live fetuses at 11-13 wks’ gestation were enrolled. Gestational age was determined from crown-rump length of the larger twin in the first trimester. EFW charts were made from fetal growth at 11-13, 20-22, 24-26, 28-30, 32-34, and 36-37 wks’ gestation using Hadlock-4 formula made of biparietal diameter, head and abdominal circumference, and femur length. Chorionicity specific charts were built for 376 DC and 158 MCDA live twins who were born at term, without malformations. Centers included were from Montreal, Canada, Bonn and Tubingen, Germany, Barcelona, Spain, Rome, Italy, and Zerifin, Israel. ANOVA was used to compare ethnic and centers charts and functional fit to were compared our charts to retrospective EFW charts of the FMF. Results: Growth was slower in MCDA compared with DC twins starting from 21st wks’ gestation and increased with advancing gestation. Our charts were similar but marginally slower than the FMF ones. Smaller EFW were in Barcelona and Rome compared to the larger in Bonn and Tubingen, and fetuses of white women were larger than those of other ethnicities Conclusions: We developed a prospective growth chart for pregnancies with two live DC and MCDA twins born at term without malformations that are consistent with those of the FMF, with small differences between countries and ethnicities.

BackgroundLittle is known about whether patterns of early growth are associated with altered respiratory and immune development. This study relates prenatal and infant growth patterns to wheeze and atopy at...

Giants in Obstetrics and Gynecology Series: Philippe Jeanty, MD, PhD, a pioneer in the study of fetal anatomy, biometry, growth, and congenital anomalies

The assessment of fetal growth represents a fundamental step towards the identification of the true growth restricted fetus that is associated to important perinatal morbidity and mortality. The possible ways of detecting abnormal fetal growth are taken into consideration in this review and their strong and weak points are discussed. An important debate still remains about how to discriminate between the physiologically small fetus that does not require special surveillance and the truly growth restricted fetus who is predisposed to perinatal complications, even if its parameters are above the cut-off limits established. In this article, we present the clinical tools of fetal growth assessment: Symphyseal-Fundal Height (SFH) measurement, the fetal ultrasound parameters widely taken into consideration when discussing fetal growth: Abdominal Circumference (AC) and Estimated Fetal Weight (EFW); several types of growth charts and their characteristics: populational growth charts, standard growth charts, individualized growth charts, customized growth charts and growth trajectories. Abbreviations: FGR = Fetal growth restriction; IUGR = Intrauterine Growth Restriction; SGA = small for gestational age fetus; EFW = estimated fetal weight; AC = abdominal circumference; SD = Standard Deviation; SFH = Symphyseal-fundal height; US = ultrasound; 2D = bidimensional; 3D = tridimensional; RCOG = Royal College of Obstetricians and Gynecologists; FL = femur length; BPD = biparietal diameter; BW = birth weight; IGA = Individualized Growth Assessment; PIH = Pregnancy Induced hypertension; PE = Preeclampsia; NICU = Neonatal Intensive Care Unit.

Background and objective Growth charts are important in monitoring the growth of neonates. The growth of Indian fetuses is understood to be different from the Western population due to multiple factors. In this study, we aimed to analyze the utility of the application of various growth charts in evaluating the birth weights of liveborn neonates at a tertiary teaching hospital. Methodology A total of 729 liveborn neonates between 24 to 42 weeks of gestation delivered at the study institute during the study period were included. Birth weights were plotted on three growth charts - Fenton 2013, INTERGROWTH-21st(IG-21), and Kandraju et al. chart - and classified as small for gestational age (SGA), or appropriate for gestational age (AGA), or large for gestational age (LGA) according to the respective centiles and sex. The incidences of SGA and LGA were calculated with respect to various charts and compared. Statistical analysis was done using the McNemar Chi-square test for paired categorical variables. Cohen's kappa (K) was used to analyze the concordance between the growth charts. A p-value <0.005 was considered statistically significant. Results Among668 term neonates, the number of neonates classified as SGA was 313 (46.86%), 236 (35.33%), and 219 (32.78%) according to Fenton 2013, IG-21, and Kandraju et al. chart respectively. The difference in incidences of SGA betweenFenton 2013 and IG-21 for term neonates was significant (p=0.0001). The difference between incidences of SGA amongterm neonates according toFenton 2013 and Kandraju et al. and IG-21 vs. Kandraju et al. was significant (p=0.0001). Among 61 preterm neonates, the number of neonates classified as SGA was 15, 11, and five according to Fenton 2013, IG-21, and Kandraju et al. respectively. There was no statistically significant difference between the three charts. Among 729 neonates, the number of neonates classified as LGA was 10 (1.37%), 22 (3.02%), and 32 (4.39%) according to Fenton 2013, IG-21, and Kandraju, et al. respectively. The difference in incidences of LGA between Fenton 2013 and IG-21 was significant (p=0.0015). The difference in incidences of LGA between Fenton 2013 and Kandraju et al. was significant (p=0.0001). The difference in incidences of LGA between IG-21 and Kandraju et al. was also significant (p=0.0044). Conclusion Fenton 2013, IG-21, and Kandraju et al. growth charts vary significantly in detecting the incidence of SGA and LGA among term neonates. Among term neonates, IG-21 and Kandraju et al. growth charts are comparable in terms of the estimation of SGA. The Fenton 2013 growth chart showed a higher incidence of SGA among term neonates. The incidence of LGA was highest according to Kandraju et al. growth chart and least according toFenton 2013. Among preterm neonates, the incidence of SGA as per birth weight was comparable across the three growth charts.

To establish new standards fetal biometry and growth curves for Indian population. 11567 patients were included in the present study to measure BPD(Biparital diameter), HC (Head circumference), AC (Abdominal circumference), FL (Femur length) and EFW (expected fetal weight). Statistical analysis has been performed using MS excel 2010. Data analysed as recommended by Altman, Chitty and Royton. For each measurement, polynomial regression models were fitted separately to estimate the mean and standard deviation (SD) as functions of gestational age. The SD was modelled via the absolute residuals from the regression to estimate the mean. We have developed fetal biometry for Indian population that can be utilised for clinical practice or fetal size and fetal grow Centile Trendline Equation BPD 1sty = -0.0013x3 + 0.0083x2 + 3.383x + 11.9620.9997, 5thy = -0.0014x3 + 0.0114x2 + 3.3853x + 12.9750.9998, 50thy = -0.0013x3 + 0.0094x2 + 3.4777x + 15.5430.9998, 95thy = -0.0014x3 + 0.013x2 + 3.5186x + 18.0160.9999, 99thy = -0.0014x3 + 0.0106x2 + 3.5725x + 19.1240.9998. Centile Trendline Equation AC 90thy = -0.0046x3 + 0.1042x2 + 11.047x + 54.697 50thy = -0.0037x3 + 0.0711x2 + 10.93x + 48.511 10thy = -0.0027x3 + 0.038x2 + 10.812x + 42.325, 5thy = -0.0026x3 + 0.0326x2 + 10.755x + 40.787, 3rdy = -0.0023x3 + 0.0225x2 + 10.757x + 39.426, 1sty = -0.002x3 + 0.0109x2 + 10.715x + 37.251. Centile Trendline Equation for HC R-squared: 1sty = -0.0049x3 - 0.0029x2 + 13.39x + 45.230.9999,5thy = -0.0048x3 - 0.01x2 + 13.584x + 48.3310.999,950thy = -0.0039x3 - 0.057x2 + 14.444x + 54.3260.9998. Centile Trendline Equation FL 1sty = -0.0006x3 - 0.0089x2 + 3.0605x + 1.6256 5thy = -0.0006x3 - 0.0088x2 + 3.0746x + 2.5481 10thy = -0.0007x3 - 0.0062x2 + 3.0599x + 3.1166 50thy = -0.0007x3 - 0.003x2 + 3.0591x + 4.934. For better diagnosis of fetal growth related problems, we have developed fetal biometry and growth curves for the Indian population to prevent over-diagnosis of intrauterine growth retardation, under diagnosis of fetal macrosomia and correct prediction of fetal age in Indian population. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Objective To elucidate whether antenatal administration of corticosteroids in pregnancies with threatened preterm labor affects growth velocity. Methods A cohort of 262 pregnancies exposed to antenatal corticosteroids longitudinally studied and delivered from 36 weeks (cases) were compared to an unexposed group of 270 women (controls). Methods Fetal growth was assessed analyzing the growth velocity of head circumference (HC), abdominal circumference (AC), femur length (FL) and estimated fetal weight (EFW). Growth velocity (GV) was calculated as the difference in the Z-score between the biometric measurements recorded at the time of steroids administration and at 36 week of gestation, divided by the time interval (expressed in days) between the two scans and multiplied by 100. Similarly, changes in the Pulsatility Index (PI) of uterine, umbilical (UA), middle cerebral (MCA) arteries and cerebroplacental ratio (CPR) during the same time interval were also computed. Results Median gestational age at steroid administration (30.2 weeks vs 30.4) and follow-up ultrasound (36.4 weeks vs 36.4) were similar between cases and controls. In pregnancies exposed to antenatal corticosteroids, growth velocity in the HC (−0.61 vs. 0.12; p ≤ 0.001), AC (−0.55 vs. −0.04; p ≤ 0.001) and EFW (−0.89 vs. 0.06; p ≤ 0.001) were lower when compared to pregnancies not exposed to steroid therapy, while there was no difference in the growth velocity of FL (−0.05 vs 0.19; p = .06) or in any of the Doppler parameters explored. Conclusion In pregnancies exposed to antenatal steroid therapy, there is a significant reduction in fetal growth velocity not otherwise associated with changes in cerebroplacental Dopplers.

Fetal intra-uterine growth charts are generally based on last menstrual period (LMP) data. Such charts may not really be applicable to infants whose gestational age is ultrasonically determined in early pregnancy. 1369 consecutive singleton pregnancies were studied. All fetuses had their gestational age estimated both by ultrasonic measurement of fetal crown-rump length and from registered last menstrual period data. All infants were weighed at birth as a part of the routine care. The age determination according to the two methods differed in 664 out of 1369 cases and in 516 of these 664 cases the age according to LMP was higher than according to CRL--a highly significant difference (p less than 0.001). Mean values for birth weight were found to be larger when correlated to age in terms of CRL determinations than when related to age as calculated from LMP data. Birth weight also showed a significant increase between 40 and 42 weeks when age was determined ultrasonically. This was not the case when age determination was based on LMP data. The explanation of this fact is that age is overestimated in late pregnancy when calculated from LMP data. These facts ought to be considered when future fetal growth charts are constructed.

A retrospective longitudinal study was performed to quantify foetal growth velocities in twin pregnancies and to determine the effect of variables specific to twin pregnancies on growth velocity. Foetal growth velocity standard deviation (Z) scores were calculated from serial ultrasound data using published singleton reference data for 131 consecutive sets of twins from 30 to 37 weeks' gestation. Compared with low-risk pregnancies, the twin foetal abdominal area growth velocity Z scores were significantly reduced from 30 to 37 weeks and biparietal diameter growth velocity Z scores were also significantly lower, from 30 to 33 weeks. Amongst the twin pairs there were no significant differences in Z scores with respect to chorionicity, foetal sex, birth order to whether delivery was premature or term. This retrospective study has demonstrated that twin foetal growth velocity is reduced when compared to singletons from at least as early as 30 weeks' gestation. Twin specific variables such as chorionicity, sex, birth order and subsequent premature birth do not need to be accounted for in the interpretation of growth velocities in twins. The clinical importance of determining foetal growth velocity in twin pregnancies awaits further prospective study.

753 Umbilical artery doppler improvement after steroid administration is associated with improved fetal growth

Subjective recall of supine sleep during pregnancy has been linked to increased risk of stillbirth, but longitudinal, objective data are lacking. We aimed to examine how sleep position and breathing parameters change throughout pregnancy, and investigated associations between maternal supine sleep, assessed objectively in early and late gestation, and fetal growth velocity in high-risk women. Women with singleton pregnancies and body mass index (BMI) ≥27 kg/m2 underwent level-III sleep apnea testing. Sleep position was assessed by accelerometry. We derived percentiles of estimated fetal weight and birthweight using FetalGPSR software, then calculated growth velocity as change in percentile/week between the second-trimester anatomy scan and birth. In total, 446 women were included, with N = 126 in the longitudinal sleep pattern analysis and N = 83 in the fetal growth analysis. Sleep-onset position and predominant sleep position were significantly correlated in both early (p = 0.001) and late (p < 0.01) pregnancy. However, supine going-to-bed position predicted predominant supine sleep in only 47% of women. Between early and late pregnancy there was a reduction in predominant supine sleepers (51.6% to 30.2%). Percent of sleep spent supine and oxygen desaturation index, in the third trimester, were significantly associated after BMI adjustment (B = 0.018, p = 0.04). Models did not suggest significant effects of early or late pregnancy supine sleep on growth velocity (p > 0.05). Going-to-bed position predicts predominant supine sleep in less than half of women with overweight and obesity. Time spent supine throughout pregnancy correlates with measures of sleep-disordered breathing. Maternal sleep position patterns did not affect fetal growth velocity in this high-risk population, but the study was not powered to detect differences.

Fetal growth restriction is defined as failure to reach growth potential and considered one of the major complications of pregnancy. These infants are often, although not universally, small for gestational age (SGA). SGA is defined as a weight less than a specified percentile (usually the 10th percentile). Identification of SGA infants is important because these infants are at increased risk of perinatal morbidity and mortality. Screening for SGA is a challenge for all maternity care providers and current methods of clinical assessment fail to detect many infants that are SGA. Large observational studies suggest that customised growth charts may be better able to differentiate between constitutional and pathologic smallness. Customised charts adjust for physiological variables such as maternal weight and height, ethnicity and parity. To assess the benefits and harms of using population-based growth charts compared with customised growth charts as a screening tool for detection of fetal growth in pregnant women. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 September 2011), reviewed published guidelines and searched the reference lists of review articles. Randomised, quasi-randomised or cluster randomised clinical trials comparing customised versus population-based growth charts used as a screening tool for detection of fetal growth in pregnant women. Two review authors independently assessed trials for inclusion. No randomised trials met the inclusion criteria. There is no randomised trial evidence currently available. Further randomised trials are required to accurately assess whether the improvement in detection shown is secondary to customised charts alone or an effect of the policy change. Future research in large trials is needed to investigate the benefits and harms (including perinatal mortality) of using customised growth charts in different settings and for both fundal height and ultrasound measurements.