ObjectiveEstimated fetal weight (EFW) and fetal biometry are complementary measures used to screen for fetal growth disturbances. Our aim was to provide international EFW standards to complement the INTERGROWTH‐21st Fetal Growth Standards that are available for use worldwide.MethodsWomen with an accurate gestational‐age assessment, who were enrolled in the prospective, international, multicenter, population‐based Fetal Growth Longitudinal Study (FGLS) and INTERBIO‐21st Fetal Study (FS), two components of the INTERGROWTH‐21st Project, had ultrasound scans every 5 weeks from 9–14 weeks' until 40 weeks' gestation. At each visit, measurements of fetal head circumference (HC), biparietal diameter, occipitofrontal diameter, abdominal circumference (AC) and femur length (FL) were obtained blindly by dedicated research sonographers using standardized methods and identical ultrasound machines. Birth weight was measured within 12 h of delivery by dedicated research anthropometrists using standardized methods and identical electronic scales. Live babies without any congenital abnormality, who were born within 14 days of the last ultrasound scan, were selected for inclusion. As most births occurred at around 40 weeks' gestation, we constructed a bootstrap model selection and estimation procedure based on resampling of the complete dataset under an approximately uniform distribution of birth weight, thus enriching the sample size at extremes of fetal sizes, to achieve consistent estimates across the full range of fetal weight. We constructed reference centiles using second‐degree fractional polynomial models.ResultsOf the overall population, 2404 babies were born within 14 days of the last ultrasound scan. Mean time between the last scan and birth was 7.7 (range, 0–14) days and was uniformly distributed. Birth weight was best estimated as a function of AC and HC (without FL) as log(EFW) = 5.084820 − 54.06633 × (AC/100)3 − 95.80076 × (AC/100)3 × log(AC/100) + 3.136370 × (HC/100), where EFW is in g and AC and HC are in cm. All other measures, gestational age, symphysis–fundus height, amniotic fluid indices and interactions between biometric measures and gestational age, were not retained in the selection process because they did not improve the prediction of EFW. Applying the formula to FGLS biometric data (n = 4231) enabled gestational age‐specific EFW tables to be constructed. At term, the EFW centiles matched those of the INTERGROWTH‐21st Newborn Size Standards but, at < 37 weeks' gestation, the EFW centiles were, as expected, higher than those of babies born preterm. Comparing EFW cross‐sectional values with the INTERGROWTH‐21st Preterm Postnatal Growth Standards confirmed that preterm postnatal growth is a different biological process from intrauterine growth.ConclusionsWe provide an assessment of EFW, as an adjunct to routine ultrasound biometry, from 22 to 40 weeks' gestation. However, we strongly encourage clinicians to evaluate fetal growth using separate biometric measures such as HC and AC, as well as EFW, to...

Background Reliable ultrasound charts are necessary for the prenatal assessment of fetal size, yet there is a wide variation of methodologies for the creation of such charts.Objective To evaluate the methodological quality of studies of fetal biometry using a set of predefined quality criteria of study design, statistical analysis and reporting methods.Search strategy Electronic searches in MEDLINE, EMBASE and CINAHL, and references of retrieved articles.Selection criteria Observational studies whose primary aim was to create ultrasound size charts for bi-parietal diameter, head circumference, abdominal circumference and femur length in fetuses from singleton pregnancies.Data collection and analysis Studies were scored against a predefined set of independently agreed methodological criteria and an overall quality score was given to each study. Multiple regression analysis between quality scores and study characteristics was performed.Main results Eighty-three studies met the inclusion criteria. The highest potential for bias was noted in the following fields: 'Inclusion/exclusion criteria', as none of the studies defined a rigorous set of antenatal or fetal conditions which should be excluded from analysis; 'Ultrasound quality control measures', as no study demonstrated a comprehensive quality assurance strategy; and 'Sample size calculation', which was apparent in six studies only. On multiple regression analysis, there was a positive correlation between quality scores and year of publication: quality has improved with time, yet considerable heterogeneity in study methodology is still observed today.Conclusions There is considerable methodological heterogeneity in studies of fetal biometry. Standardisation of methodologies is necessary in order to make correct interpretations and comparisons between different charts. A checklist of recommended methodologies is proposed.

ObjeCtiveTo describe patterns in maternal gestational weight gain (GWG) in healthy pregnancies with good maternal and perinatal outcomes. DesignProspective longitudinal observational study. Main OutCOMe MeasuresMaternal weight measured with standardised methods and identical equipment every five weeks (plus/minus one week) from the first antenatal visit (<14 weeks' gestation) to delivery. After confirmation that data from the study sites could be pooled, a multilevel, linear regression analysis accounting for repeated measures, adjusted for gestational age, was applied to produce the GWG values. results 13 108 pregnant women at <14 weeks' gestation were screened, and 4607 met the eligibility criteria, provided consent, and were enrolled. The variance within sites (59.6%) was six times higher than the variance between sites (9.6%). The mean GWGs were 1.64 kg, 2.86 kg, 2.86 kg, 2.59 kg, and 2.56 kg for the gestational age windows 14-18 +6 weeks, 19-23 +6 weeks, 24-28 +6 weeks, 29-33 +6 weeks, and 34-40 +0 weeks, respectively. Total mean weight gain at 40 weeks' gestation was 13.7 (SD 4.5) kg for 3097 eligible women with a normal BMI in the first trimester. Of all the weight measurements, 71.7% (10 639/14 846) and 94.9% (14 085/14 846) fell within the expected 1 SD and 2 SD thresholds, respectively. Data were used to determine fitted 3rd, 10th, 25th, 50th, 75th, 90th, and 97th smoothed GWG centiles by exact week of gestation, with equations for the mean and standard deviation to calculate any desired centiles according to gestational age in exact weeks. COnClusiOnsWeight gain in pregnancy is similar across the eight populations studied. Therefore, the standards generated in this study of healthy, well nourished women may be used to guide recommendations on optimal gestational weight gain worldwide.

Meticulous standardisation and ongoing monitoring of adherence to measurement protocols during data collection are essential to ensure consistency and to minimise systematic error in multicentre studies. Strict ultrasound fetal biometric measurement protocols are used in the st Project so that data of the highest quality from different centres can be compared and potentially pooled. A central Ultrasound Quality Unit (USQU) has been set up to oversee this process. After initial training and standardisation, the USQU monitors the performance of all ultrasonographers involved in the project by continuously assessing the quality of the images and the consistency of the measurements produced. Ultrasonographers are identified when they exceed preset maximum allowable differences. Corrective action is then taken in the form of retraining or simply advice regarding changes in practice. This paper describes the procedures used, which can form a model for research settings involving ultrasound measurements.

ObjectivesTo identify risk factors for antepartum stillbirth, including fetal growth restriction, among women with well‐dated pregnancies and access to antenatal care.DesignPopulation‐based, prospective, observational study.SettingEight international urban populations.PopulationPregnant women and their babies enrolled in the Newborn Cross‐Sectional Study of the INTERGROWTH‐21st Project.MethodsCox proportional hazard models were used to compare risks among antepartum stillborn and liveborn babies.Main outcome measuresAntepartum stillbirth was defined as any fetal death after 16 weeks’ gestation before the onset of labour.ResultsOf 60 121 babies, 553 were stillborn (9.2 per 1000 births), of which 445 were antepartum deaths (7.4 per 1000 births). After adjustment for site, risk factors were low socio‐economic status, hazard ratio (HR): 1.6 (95% CI, 1.2–2.1); single marital status, HR 2.0 (95% CI, 1.4–2.8); age ≥40 years, HR 2.2 (95% CI, 1.4–3.7); essential hypertension, HR 4.0 (95% CI, 2.7–5.9); HIV/AIDS, HR 4.3 (95% CI, 2.0–9.1); pre‐eclampsia, HR 1.6 (95% CI, 1.1–3.8); multiple pregnancy, HR 3.3 (95% CI, 2.0–5.6); and antepartum haemorrhage, HR 3.3 (95% CI, 2.5–4.5). Birth weight <3rd centile was associated with antepartum stillbirth [HR, 4.6 (95% CI, 3.4–6.2)]. The greatest risk was seen in babies not suspected to have been growth restricted antenatally, with an HR of 5.0 (95% CI, 3.6–7.0). The population‐attributable risk of antepartum death associated with small‐for‐gestational‐age neonates diagnosed at birth was 11%.ConclusionsAntepartum stillbirth is a complex syndrome associated with several risk factors. Although small babies are at higher risk, current growth restriction detection strategies only modestly reduced the rate of stillbirth.Tweetable abstractInternational stillbirth study finds individual risks poor predictors of death but combinations promising.

The primary aim of the INTERGROWTH-21st Project is to construct new, prescriptive standards describing optimal fetal and preterm postnatal growth. The anthropometric measurements include the head circumference, recumbent length and weight of the infants, and the stature and weight of the parents. In such a large, international, multicentre project, it is critical that all study sites follow standardised protocols to ensure maximal validity of the growth and nutrition indicators used. This paper describes in detail the anthropometric training, standardisation and quality control procedures used to collect data for these new standards. The initial standardisation session was in Nairobi, Kenya, using newborns, which was followed by similar sessions in the eight participating study sites in Brazil, China, India, Italy, Kenya, Oman, UK and USA. The intraobserver and inter-observer technical error of measurement values for head circumference range from 0.3 to 0.4 cm, and for recumbent length from 0.3 to 0.5 cm. These standardisation protocols implemented at each study site worldwide ensure that the anthropometric data collected are of the highest quality to construct international growth standards.

The st Project has in its mandate to develop prescriptive standards for fetal, neonatal and preterm post-neonatal growth. The project comprises three components: the Fetal Growth Longitudinal Study (FGLS), the Preterm Postnatal Follow-up Study (PPFS), and the Newborn Cross-Sectional Study (NCSS). We consider here the statistical aspects of the three components as they relate to the construction of these standards, in particular the sample size, and outline the principles that will guide the planned main analyses.

Background Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population's general health and nutritional status. Current clinical methods of estimating fetal gestational age are often inaccurate. For example, between 20 and 30 weeks of gestation, the width of the 95% prediction interval around the actual gestational age is estimated to be 18-36 days, even when the best ultrasound estimates are used. The aims of this study are to improve estimates of fetal gestational age and provide personalised predictions of future growth. Methods Using ultrasound-derived, fetal biometric data, we developed a machine learning approach to accurately estimate gestational age. The accuracy of the method is determined by reference to exactly known facts pertaining to each fetus-specifically, intervals between ultrasound visits-rather than the date of the mother's last menstrual period. The data stem from a sample of healthy, well-nourished participants in a large, multicentre, population-based study, the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st). The generalisability of the algorithm is shown with data from a different and more heterogeneous population (INTERBIO-21st Fetal Study). Findings In the context of two large datasets, we estimated gestational age between 20 and 30 weeks of gestation with 95% confidence to within 3 days, using measurements made in a 10-week window spanning the second and third trimesters. Fetal gestational age can thus be estimated in the 20-30 weeks gestational age window with a prediction interval 3-5 times better than with any previous algorithm. This will enable improved management of individual pregnancies. 6-week forecasts of the growth trajectory for a given fetus are accurate to within 7 days. This will help identify at-risk fetuses more accurately than currently possible. At population level, the higher accuracy is expected to improve fetal growth charts and population health assessments. Interpretation Machine learning can circumvent long-standing limitations in determining fetal gestational age and future growth trajectory, without recourse to often inaccurately known information, such as the date of the mother's last menstrual period. Using this algorithm in clinical practice could facilitate the management of individual pregnancies and improve population-level health. Upon publication of this study, the algorithm for gestational age estimates will be provided for research purposes free of charge via a web portal.