Peripheral biomarkers show promise as diagnostic aids, but further research is necessary before they can be recommended in routine clinical care. Panels of markers may allow increased sensitivity and specificity of any diagnostic test.

), with technical support from four global specialised units, to study growth, health and nutrition from early pregnancy to infancy. It aims to produce prescriptive growth standards, which conceptually extend the World Health Organization (WHO) Multicentre Growth Reference Study (MGRS) to cover fetal and newborn life. The new international standards will describe: (1) fetal growth assessed by clinical and ultrasound measures; (2) postnatal growth of term and preterm infants up to 2 years of age; and (3) the relationship between birthweight, length and head circumference, gestational age and perinatal outcomes. As the project has selected healthy cohorts with no obvious risk factors for intrauterine growth restriction, these standards will describe how all fetuses and newborns should grow, as opposed to traditional charts that describe how some have grown at a given place and time. These growth patterns will be related to morbidity and mortality to identify levels of perinatal risk. Additional aims include phenotypic characterisation of the preterm and impaired fetal growth syndromes and development of a prediction model, based on multiple ultrasound measurements, to estimate gestational age for use in pregnant women without access to early/frequent antenatal care.

Background Neurodevelopmental disorders are increasingly believed to originate from intrauterine growth restriction (IUGR). Current reviews exploring the neurodevelopmental effects of IUGR, however, are mostly based on birthweight, an inadequate proxy. Objective We aimed to examine the association between IUGR documented in utero, and neurodevelopmental outcomes during childhood. Search strategy Medline, CINAHL, PsycInfo and Scopus were searched for relevant studies published after 1970. Selection criteria The analysis included studies that identified IUGR in utero, with follow‐up assessments between 1 month and 12 years of age. Data collection and analysis Data was extracted for cognitive, behavioural, language, motor, hearing, vision or sleep outcomes. Studies were summarised separately for children born at <35 and ≥35 weeks gestation. Main results Of 28 876 titles identified, 38 were suitable for inclusion. IUGR children born ≥35 weeks gestation scored on average 0.5 SD lower than non‐IUGR children across all neurodevelopmental assessments. IUGR children born <35 weeks of gestation scored approximately 0.7 SD lower than non‐IUGR children across all neurodevelopmental assessments. IUGR children with evidence of fetal circulatory redistribution (preferential perfusion of the brain) had more severe neurodevelopmental impairments than those born IUGR alone. Conclusions IUGR increases the risk of neurodevelopmental impairment during childhood differentially across domains. IUGR children born preterm or with evidence of fetal circulatory redistribution are more severely affected. Tweetable abstract IUGR is associated with an overall risk for neurodevelopmental delay in a range of neurodevelopmental domains.

Background Being able to predict preterm birth is important, as it may allow a high-risk population to be selected for future interventional studies and help in understanding the pathways that lead to preterm birth.Objective To investigate the accuracy of novel biomarkers to predict spontaneous preterm birth in women with singleton pregnancies and no symptoms of preterm labour.Search strategy Electronic searches in PubMed, Embase, Cinahl, Lilacs, and Medion, references of retrieved articles, and conference proceedings. No language restrictions were applied.Selection criteria Observational studies that evaluated the accuracy of biomarkers proposed in the last decade to predict spontaneous preterm birth in asymptomatic women. We excluded studies in which biomarkers were evaluated in women with preterm labour.Data collection and analysis Two reviewers independently extracted data on study characteristics, quality, and accuracy. Data were arranged in 2 · 2 contingency tables and synthesised separately for spontaneous preterm birth before 32, 34, and 37 weeks of gestation. We used bivariate meta-analysis to estimate pooled sensitivities and specificities, and calculated likelihood ratios (LRs).Main results A total of 72 studies, including 89 786 women and evaluating 30 novel biomarkers, met the inclusion criteria. Only three biomarkers (proteome profile and prolactin in cervicovaginal fluid, and matrix metalloproteinase-8 in amniotic fluid) had positive LRs > 10. However, each of these biomarkers was evaluated in only one small study. Four biomarkers had a moderate predictive accuracy (interleukin-6 and angiogenin, in amniotic fluid; human chorionic gonadotrophin and phosphorylated insulin-like growth factor binding protein-1, in cervicovaginal fluid). The remaining biomarkers had low predictive accuracies.Conclusions None of the biomarkers evaluated in this review meet the criteria to be considered a clinically useful test to predict spontaneous preterm birth. Further large, prospective cohort studies are needed to evaluate promising biomarkers such as a proteome profile in cervicovaginal fluid.

Background Several biomarkers for predicting intrauterine growth restriction (IUGR) have been proposed in recent years. However, the predictive performance of these biomarkers has not been systematically evaluated.Objective To determine the predictive accuracy of novel biomarkers for IUGR in women with singleton gestations.Search strategy Electronic databases, reference list checking and conference proceedings.Selection criteria Observational studies that evaluated the accuracy of novel biomarkers proposed for predicting IUGR.Data collection and analysis Data were extracted on characteristics, quality and predictive accuracy from each study to construct 2 9 2 tables. Summary receiver operating characteristic curves, sensitivities, specificities and likelihood ratios (LRs) were generated.Main results A total of 53 studies, including 39 974 women and evaluating 37 novel biomarkers, fulfilled the inclusion criteria. Overall, the predictive accuracy of angiogenic factors for IUGR was minimal (median pooled positive and negative LRs of 1.7, range 1.0-19.8; and 0.8, range 0.0-1.0, respectively). Two small case-control studies reported high predictive values for placental growth factor and angiopoietin-2 only when IUGR was defined as birthweight centile with clinical or pathological evidence of fetal growth restriction. Biomarkers related to endothelial function/ oxidative stress, placental protein/hormone, and others such as serum levels of vitamin D, urinary albumin : creatinine ratio, thyroid function tests and metabolomic profile had low predictive accuracy.Conclusions None of the novel biomarkers evaluated in this review are sufficiently accurate to recommend their use as predictors of IUGR in routine clinical practice. However, the use of biomarkers in combination with biophysical parameters and maternal characteristics could be more useful and merits further research.

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.

Background Several biophysical and biochemical tests have been proposed to predict stillbirth but their predictive ability remains unclear.Objective To assess the accuracy of tests performed during the first and/or second trimester of pregnancy to predict stillbirth in unselected women with singleton, structurally and chromosomally normal fetuses through use of formal methods for systematic reviews and meta-analytic techniques.Search strategy Electronic databases, bibliographies and conference proceedings.Selection criteria Observational studies that evaluated the predictive accuracy for stillbirth of tests performed during the first two trimesters of pregnancy.Data collection and analysis Two reviewers selected studies, assessed risk of bias and extracted data. Summary receiver operating characteristic curves, pooled sensitivities, specificities and likelihood ratios (LRs) were generated. Data were synthesised separately for stillbirth as a sole category and for specific stillbirth categories.Main results Seventy-one studies, evaluating 16 single and five combined tests, met the inclusion criteria. A uterine artery pulsatility index >90th centile during the second trimester and low levels of pregnancy-associated plasma protein A (PAPP-A) during the first trimester had a moderate to high predictive accuracy for stillbirth related to placental abruption, small-for-gestational-age or pre-eclampsia (positive and negative LRs from 6.3 to 14.1, and from 0.1 to 0.4, respectively). All biophysical and biochemical tests assessed had a low predictive accuracy for stillbirth as a sole category.Conclusions Currently, there is no clinically useful first-trimester or second-trimester test to predict stillbirth as a sole category. Uterine artery pulsatility index and maternal serum PAPP-A levels appeared to be good predictors of stillbirth related to placental dysfunction disorders.Keywords Biomarker, meta-analysis, prediction, stillbirth, systematic review, test.

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.