An estimated 2.6 million third trimester stillbirths occurred in 2015 (uncertainty range 2.4-3.0 million). The number of stillbirths has reduced more slowly than has maternal mortality or mortality in children younger than 5 years, which were explicitly targeted in the Millennium Development Goals. The Every Newborn Action Plan has the target of 12 or fewer stillbirths per 1000 births in every country by 2030. 94 mainly high-income countries and upper middle-income countries have already met this target, although with noticeable disparities. At least 56 countries, particularly in Africa and in areas affected by conflict, will have to more than double present progress to reach this target. Most (98%) stillbirths are in low-income and middle-income countries. Improved care at birth is essential to prevent 1.3 million (uncertainty range 1.2-1.6 million) intrapartum stillbirths, end preventable maternal and neonatal deaths, and improve child development. Estimates for stillbirth causation are impeded by various classification systems, but for 18 countries with reliable data, congenital abnormalities account for a median of only 7.4% of stillbirths. Many disorders associated with stillbirths are potentially modifiable and often coexist, such as maternal infections (population attributable fraction: malaria 8.0% and syphilis 7.7%), non-communicable diseases, nutrition and lifestyle factors (each about 10%), and maternal age older than 35 years (6.7%). Prolonged pregnancies contribute to 14.0% of stillbirths. Causal pathways for stillbirth frequently involve impaired placental function, either with fetal growth restriction or preterm labour, or both. Two-thirds of newborns have their births registered. However, less than 5% of neonatal deaths and even fewer stillbirths have death registration. Records and registrations of all births, stillbirths, neonatal, and maternal deaths in a health facility would substantially increase data availability. Improved data alone will not save lives but provide a way to target interventions to reach more than 7000 women every day worldwide who experience the reality of stillbirth.Copyright © 2016 Elsevier Ltd. All rights reserved.

To develop a model for prediction of stillbirth based on maternal characteristics and components of medical history and to evaluate the performance of screening with this model for all stillbirths and those due to impaired placentation and to unexplained causes.This was a prospective screening study of 113 415 singleton pregnancies at 11 + 0 to 13 + 6 weeks' gestation and at 19 + 0 to 24 + 6 weeks. The study population included 113 019 live births and 396 (0.35%) antepartum stillbirths; 230 (58%) were secondary to impaired placentation and 166 (42%) were due to other or unexplained causes. Multivariable logistic regression analysis was used to determine the factors from maternal characteristics and medical history which provided a significant contribution to the prediction of stillbirth.The risk for stillbirth increased with maternal weight (odds ratio (OR), 1.01 per kg above 69 kg), was higher in women of Afro-Caribbean racial origin (OR, 2.01), those with assisted conception (OR, 1.79), cigarette smokers (OR, 1.71), and in those with a history of chronic hypertension (OR, 2.62), systemic lupus erythematosus/antiphospholipid syndrome (OR, 3.61) or diabetes mellitus (OR, 2.55) and was increased in women with a history of previous stillbirth (OR, 4.81). Screening with the model predicted 26% of unexplained stillbirths and 31% of those due to impaired placentation, at a false-positive rate of 10%; within the impaired-placentation group the detection rate of stillbirth < 32 weeks' gestation was higher than that of stillbirth ≥ 37 weeks (38% vs 28%).A model based on maternal characteristics and medical history recorded in early pregnancy can potentially predict one-third of subsequent stillbirths. The extent to which such stillbirths could be prevented remains to be determined. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

To develop and internally validate a prognostic model for perinatal death that could guide community-based antenatal care of women with a hypertensive disorder of pregnancy (HDP) in low-resourced settings as part of a mobile health application.Using data from 1688 women (110 (6.5%) perinatal deaths) admitted to hospital after 32weeks gestation with a HDP from five low-resourced countries in the miniPIERS prospective cohort, a logistic regression model to predict perinatal death was developed and internally validated. Model discrimination, calibration, and classification accuracy were assessed and compared with use of gestational age alone to determine prognosis.Stillbirth or neonatal death before hospital discharge.The final model included maternal age; a count of symptoms (0, 1 or ⩾2); and dipstick proteinuria. The area under the receiver operating characteristic curve was 0.75 [95% CI 0.71-0.80]. The model correctly identified 42/110 (38.2%) additional cases as high-risk (probability >15%) of perinatal death compared with use of only gestational age <34weeks at assessment with increased sensitivity (48.6% vs. 23.8%) and similar specificity (86.6% vs. 90.0%).Using simple, routinely collected measures during antenatal care, we can identify women with a HDP who are at increased risk of perinatal death and who would benefit from transfer to facility-based care. This model requires external validation and assessment in an implementation study to confirm performance.Copyright © 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Placental insufficiency contributes to the risk of stillbirth. Cerebroplacental ratio (CPR) is an emerging marker of placental insufficiency. The aim of this study was to evaluate the association of third-trimester fetal CPR, uterine artery (UtA) Doppler and estimated fetal weight (EFW) with stillbirth and perinatal death.This was a retrospective cohort study including 2812 women with a singleton pregnancy who underwent an ultrasound scan in the third trimester. EFWs were converted into centiles, and Doppler indices (UtA and CPR) were converted into multiples of the median (MoM), adjusting for gestational age. Regression analysis was performed to identify, and adjust for, potential confounders, and receiver-operating characteristics (ROC) curve analysis was used to assess the predictive value.When adjusting for EFW centile and UtA mean pulsatility index (UtA-PI) MoM, CPR-MoM remained an independent predictor of stillbirth (odds ratio (OR) = 0.003 (95% CI, 0.00-0.11), P = 0.003) and perinatal mortality (OR = 0.001 (95% CI, 0.00-0.03), P < 0.001). UtA-PI ≥ 1.5 MoM was significantly associated with low CPR-MoM, even after adjusting for EFW centile (OR = 5.22 (95% CI, 3.88-7.04), P < 0.001) or small-for-gestational age (SGA; OR = 4.73 (95% CI, 3.49-6.41), P < 0.001). These associations remained significant, even when excluding pregnancies with SGA or including only cases in which Doppler indices were recorded at term (P < 0.01). For prediction of stillbirth, the area under the ROC curve, using a combination of these three parameters, was 0.88 (95% CI, 0.77-0.99) with a sensitivity of 66.7%, specificity of 92.1%, positive likelihood ratio (LR) of 8.46 and negative LR of 0.36.Third-trimester CPR is an independent predictor of stillbirth and perinatal mortality. The role of UtA Doppler, CPR and EFW in assessing risk of adverse pregnancy outcome should be evaluated prospectively.Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

To establish proof‐of‐concept for the dynamic prediction of adverse pregnancy outcome in women with a history of stillbirth or perinatal death, repeatedly throughout the pregnancy.

Stillbirth remains a major problem in both developing and developed countries. Omics evaluation of stillbirth has been highlighted as a top research priority. To identify new putative first-trimester biomarkers in maternal serum for stillbirth prediction using metabolomics-based approach. Targeted, nuclear magnetic resonance (NMR) and mass spectrometry (MS), and untargeted liquid chromatography-MS (LC-MS) metabolomic analyses were performed on first-trimester maternal serum obtained from 60 cases that subsequently had a stillbirth and 120 matched controls. Metabolites by themselves or in combination with clinical factors were used to develop logistic regression models for stillbirth prediction. Prediction of stillbirths overall, early (<28 weeks and <32 weeks), those related to growth restriction/placental disorder, and unexplained stillbirths were evaluated. Targeted metabolites including glycine, acetic acid, L-carnitine, creatine, lysoPCaC18:1, PCaeC34:3, and PCaeC44:4 predicted stillbirth overall with an area under the curve [AUC, 95% confidence interval (CI)] = 0.707 (0.628-0.785). When combined with clinical predictors the AUC value increased to 0.740 (0.667-0.812). First-trimester targeted metabolites also significantly predicted early, unexplained, and placental-related stillbirths. Untargeted LC-MS features combined with other clinical predictors achieved an AUC (95%CI) = 0.860 (0.793-0.927) for the prediction of stillbirths overall. We found novel preliminary evidence that, verruculotoxin, a toxin produced by common household molds, might be linked to stillbirth. We have identified novel biomarkers for stillbirth using metabolomics and demonstrated the feasibility of first-trimester prediction.

Preeclampsia is a major cause of morbidity and mortality worldwide. Numerous candidate biomarkers have been proposed for diagnosis and prediction of preeclampsia. Measurement of maternal circulating angiogenesis biomarker as the ratio of sFlt-1 (soluble FMS-like tyrosine kinase-1; an antiangiogenic factor)/PlGF (placental growth factor; an angiogenic factor) reflects the antiangiogenic balance that characterizes incipient or overt preeclampsia. The ratio increases before the onset of the disease and thus may help in predicting preeclampsia. We conducted a meta-analysis to explore the predictive accuracy of sFlt-1/PlGF ratio in preeclampsia. We included 15 studies with 534 cases with preeclampsia and 19 587 controls. The ratio has a pooled sensitivity of 80% (95% confidence interval, 0.68-0.88), specificity of 92% (95% confidence interval, 0.87-0.96), positive likelihood ratio of 10.5 (95% confidence interval, 6.2-18.0), and a negative likelihood ratio of 0.22 (95% confidence interval, 0.13-0.35) in predicting preeclampsia in both high- and low-risk patients. Most of the studies have not made a distinction between early- and late-onset disease, and therefore, the analysis for it could not be done. It can prove to be a valuable screening tool for preeclampsia and may also help in decision-making, treatment stratification, and better resource allocation.© 2017 American Heart Association, Inc.

We evaluated the potential of cardiovascular-disease-associated microRNAs to predict in the early stages of gestation (from 10 to 13 gestational weeks) the occurrence of a miscarriage or stillbirth. The gene expressions of 29 microRNAs were studied retrospectively in peripheral venous blood samples derived from singleton Caucasian pregnancies diagnosed with miscarriage (n = 77 cases; early onset, n = 43 cases; late onset, n = 34 cases) or stillbirth (n = 24 cases; early onset, n = 13 cases; late onset, n = 8 cases; term onset, n = 3 cases) and 80 selected gestational-age-matched controls (normal term pregnancies) using real-time RT-PCR. Altered expressions of nine microRNAs (upregulation of miR-1-3p, miR-16-5p, miR-17-5p, miR-26a-5p, miR-146a-5p, and miR-181a-5p and downregulation of miR-130b-3p, miR-342-3p, and miR-574-3p) were observed in pregnancies with the occurrence of a miscarriage or stillbirth. The screening based on the combination of these nine microRNA biomarkers revealed 99.01% cases at a 10.0% false positive rate (FPR). The predictive model for miscarriage only was based on the altered gene expressions of eight microRNA biomarkers (upregulation of miR-1-3p, miR-16-5p, miR-17-5p, miR-26a-5p, miR-146a-5p, and miR-181a-5p and downregulation of miR-130b-3p and miR-195-5p). It was able to identify 80.52% cases at a 10.0% FPR. Highly efficient early identification of later occurrences of stillbirth was achieved via the combination of eleven microRNA biomarkers (upregulation of miR-1-3p, miR-16-5p, miR-17-5p, miR-20a-5p, miR-146a-5p, and miR-181a-5p and downregulation of miR-130b-3p, miR-145-5p, miR-210-3p, miR-342-3p, and miR-574-3p) or, alternatively, by the combination of just two upregulated microRNA biomarkers (miR-1-3p and miR-181a-5p). The predictive power achieved 95.83% cases at a 10.0% FPR and, alternatively, 91.67% cases at a 10.0% FPR. The models based on the combination of selected cardiovascular-disease-associated microRNAs had very high predictive potential for miscarriages or stillbirths and may be implemented in routine first-trimester screening programs.

We sought to relate the risk of antepartum stillbirth to uterine artery Doppler flow velocimetry at 22-24 weeks.Data were available from 30,519 unselected women from seven units in the UK who had uterine artery Doppler performed between 22 and 24 weeks of gestation. The risk of stillbirth (n=109) was assessed using time to event and logistic regression analysis. Stillbirths were subdivided into placental (due to abruption, preeclampsia, or growth restriction) or unexplained.The risk of placental stillbirth was increased among women with a mean pulsatility index in the top decile (adjusted hazard ratio [HR] 5.5, 95% confidence interval [CI] 2.8-10.6) and those with a bilateral notch (adjusted HR 3.9, 95% CI 2.0-7.8). The relationship between a mean pulsatility index in the top decile and the risk of unexplained stillbirth was weaker (adjusted HR 2.5, 95% CI 1.1-5.6) and there was no association with a bilateral notch. Placental stillbirths occurred at earlier gestations than unexplained stillbirths (median [interquartile range] 30 [26-36] compared with 38 [36-40], P<.001). Consequently, being in the top 5% of predicted risk of stillbirth on the basis of the combination of mean pulsatility index and notching was a good predictor (sensitivity, specificity, and positive likelihood ratio) of all cause stillbirth up to 32 weeks (58%, 95%, and 12.1, respectively) but a poor predictor of stillbirth at later gestations (7%, 95%, and 1.3, respectively).Abnormal uterine artery Doppler was a better predictor of the risk of stillbirth due to placental causes than unexplained stillbirth. Consequently, abnormal uterine artery Doppler was a good predictor of stillbirth at extreme preterm gestations but a poor predictor of stillbirth at term.II.

To evaluate the performance of screening for all stillbirths and those due to impaired placentation and unexplained or other causes using a combination of maternal factors, fetal biometry and uterine artery pulsatility index (UtA-PI) at 19-24 weeks' gestation and to compare this performance with that of screening by UtA-PI alone.This was a prospective screening study of 70 003 singleton pregnancies including 69 735 live births and 268 (0.38%) antepartum stillbirths; 159 (59%) were secondary to impaired placentation and 109 (41%) were due to other or unexplained causes. Multivariable logistic regression analysis was used to develop a model for prediction of stillbirth based on a combination of maternal factors, fetal biometry and UtA-PI.Combined screening predicted 55% of all stillbirths, including 75% of those due to impaired placentation and 23% of those that were unexplained or due to other causes, at a false-positive rate of 10%. Within the impaired placentation group, the detection rate of stillbirth < 32 weeks' gestation was higher than that of stillbirth ≥ 37 weeks (88% vs 46%; P < 0.001). The performance of screening by the combined test was superior to that of selecting the high-risk group on the basis of UtA-PI > 90 percentile for gestational age, which predicted 48% of all stillbirths, 70% of those due to impaired placentation and 15% of those that were unexplained or due to other causes.Second-trimester screening by a combination of UtA-PI with maternal factors and fetal biometry can predict a high proportion of stillbirths and, in particular, those that are due to impaired placentation. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Women of Afro-Caribbean and Asian origin are more at risk of stillbirths. However, there are limited tools built for risk-prediction models for stillbirth within sub-Saharan Africa. Therefore, we examined the predictors for stillbirth in low resource setting in Northern Uganda.

To derive models for estimating risk of miscarriage and stillbirth from maternal characteristics and findings of first‐trimester screening for aneuploidies and to define the procedure‐related risk of chorionic villus sampling (CVS) after adjusting for these factors.

Stillbirth has a high global prevalence and has not improved despite other advances in maternal and perinatal outcomes in the last 20 years. The global applicability of research is challenged by the fact that most evidence originates from high-income countries, whereas the burden is greatest in low- and middle-income countries. Robust universally applicable evidence is therefore desired to address this problem.

To develop a model for the prediction of stillbirth that is based on a combination of maternal characteristics and medical history with first-trimester biochemical and biophysical markers and to evaluate the performance of screening with this model for all stillbirths and those due to impaired placentation and unexplained causes.This was a prospective screening study of 76 897 singleton pregnancies, including 76 629 live births and 268 (0.35%) antepartum stillbirths; 157 (59%) were secondary to impaired placentation and 111 (41%) were due to other or unexplained causes. Multivariable logistic regression analysis was used to determine if there was a significant contribution to prediction of stillbirth from the maternal factor-derived a-priori risk, fetal nuchal translucency thickness, ductus venosus pulsatility index for veins (DV-PIV), uterine artery pulsatility index (UtA-PI) and maternal serum free β-human chorionic gonadotropin and pregnancy-associated plasma protein-A (PAPP-A). The significant contributors were used to derive a model for first-trimester prediction of stillbirth.Significant contribution to prediction of stillbirth was provided by maternal factors, PAPP-A, UtA-PI and DV-PIV. A model combining these variables predicted 40% of all stillbirths and 55% of those due to impaired placentation, at a false-positive rate of 10%. Within the impaired-placentation group, the detection rate of stillbirth < 32 weeks' gestation was higher than that of stillbirth ≥ 37 weeks (64% vs 42%).A model based on maternal factors and first-trimester biomarkers can potentially predict more than half of subsequent stillbirths that occur due to impaired placentation. The extent to which such stillbirths could be prevented remains to be determined. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

To investigate whether the addition of maternal serum placental growth factor (PlGF) measured at 11-13 weeks' gestation improves the performance of screening for stillbirths that is achieved by a combination of maternal factors and first-trimester biomarkers such as maternal serum pregnancy-associated plasma protein-A (PAPP-A), fetal ductus venosus pulsatility index for veins (DV-PIV) and uterine artery pulsatility index (UtA-PI) and to evaluate the performance of screening with this model for all stillbirths and those due to impaired placentation and unexplained causes.This was a prospective screening study of 45 452 singleton pregnancies including 45 225 live births and 227 (0.49%) antepartum stillbirths; 131 (58%) were secondary to impaired placentation and 96 (42%) were due to other or unexplained causes. Multivariable logistic regression analysis was used to determine whether the addition of maternal serum PlGF improved the performance of screening that was achieved by a combination of maternal factors and PAPP-A, DV-PIV and UtA-PI.Significant contribution to the prediction of stillbirth was provided by maternal factor-derived a-priori risk and multiples of the median values of PlGF, DV-PIV and UtA-PI but not of serum PAPP-A. A model combining these variables predicted 42% of all stillbirths and 61% of those due to impaired placentation, at a false-positive rate of 10%; within the impaired placentation group the detection rate of stillbirth < 32 weeks' gestation was higher than that of stillbirth ≥ 37 weeks (71% vs 46%; P = 0.031).A high proportion of stillbirths due to impaired placentation can be identified effectively in the first trimester of pregnancy. Addition of PlGF improves the performance of screening achieved by other maternal factors and biomarkers. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

To investigate whether the addition of maternal serum placental growth factor (PlGF) measured at 19-24 weeks' gestation improves the performance of screening for stillbirth that is achieved by a combination of maternal factors, fetal biometry and uterine artery pulsatility index (UtA-PI) and to evaluate the performance of screening with this model for all stillbirths and those due to impaired placentation and unexplained or other causes.This was a prospective screening study of 70 003 singleton pregnancies including 268 stillbirths, carried out in two phases. The first phase included prospective measurement of UtA-PI and fetal biometry, which were available in all cases. The second phase included prospective measurement of maternal serum PlGF, which was available for 9870 live births and 86 antepartum stillbirths. The values of PlGF obtained from this screening study were simulated in the remaining cases based on bivariate Gaussian distributions, defined by the mean and standard deviations. Multivariable logistic regression analysis was used to determine whether the addition of maternal serum PlGF improved the performance of screening that was achieved by a combination of maternal factors, fetal biometry and UtA-PI.Significant contribution to the prediction of stillbirth was provided by maternal factor-derived a-priori risk, multiples of the median values of PlGF, UtA-PI and fetal biometry Z-scores. A model combining these variables predicted 58% of all stillbirths and 84% of those due to impaired placentation, at a false-positive rate of 10%. Within the impaired-placentation group, the detection rate of stillbirth < 32 weeks' gestation was higher than that of stillbirth ≥ 37 weeks (97% vs 61%; P < 0.01).A high proportion of stillbirths due to impaired placentation can be identified effectively in the second trimester of pregnancy using a combination of maternal factors, fetal biometry, uterine artery Doppler and maternal serum PlGF. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

To estimate gestational age-specific risks of fetal death in pregnancies complicated by preeclampsia.Population-based cohort study comprising all singleton births (N=554,333) without preexisting chronic hypertension recorded in the Norwegian Medical Birth Registry from 1999 to 2008. Additional data come from a subset of preeclamptic pregnancies enrolled in the Norwegian Mother and Child Cohort Study with available medical records (n=3,037). The risk of fetal death, expressed per 1,000 fetuses exposed to preeclampsia, was calculated using a life table approach.Preeclampsia was recorded in 3.8% (n=21,020) of all pregnancies. Risk of stillbirth was 3.6 per 1,000 overall and 5.2 per 1,000 among pregnancies with preeclampsia (relative risk 1.45, 95% confidence interval [CI] 1.20-1.76). However, relative risk of stillbirth was markedly elevated with preeclampsia in early pregnancy. At 26 weeks of gestation, there were 11.6 stillbirths per 1,000 pregnancies with preeclampsia compared with 0.1 stillbirths per 1,000 pregnancies without (relative risk 86, 95% CI 46-142). Fetal risk with preeclampsia declined as pregnancy advanced, but at 34 weeks of gestation remained more than sevenfold higher than pregnancies without preeclampsia.For clinical purposes, the fetal risk of death associated with preeclampsia begins when preeclampsia becomes clinically apparent. Using a method that takes into account the clinical diagnosis of preeclampsia and the population of fetuses at risk, we find a remarkably high relative risk of fetal death among pregnancies diagnosed with preeclampsia in the preterm period.II.

To evaluate the accuracy of combined models of maternal biophysical factors, ultrasound, and biochemical markers for predicting stillbirths.A retrospective cohort study of pregnant women undergoing first-trimester pre-eclampsia screening at 11-13 gestational weeks was conducted. Maternal characteristics and history, mean arterial pressure (MAP) measurement, uterine artery pulsatility index (UtA-PI) ultrasound, maternal ophthalmic peak ratio Doppler, and placental growth factor (PlGF) serum were collected during the visit. Stillbirth was classified as placental dysfunction-related when it occurred with pre-eclampsia or birth weight <10th percentile. Combined prediction models were developed from significant variables in stillbirths, placental dysfunction-related, and controls. We used the area under the receiver-operating-characteristics curve (AUC), sensitivity, and specificity based on a specific cutoff to evaluate the model's predictive performance by measuring the capacity to distinguish between stillbirths and live births.There were 13 (0.79%) cases of stillbirth in 1643 women included in the analysis. The combination of maternal factors, MAP, UtA-PI, and PlGF, significantly contributed to the prediction of stillbirth. This model was a good predictor for all (including controls) types of stillbirth (AUC 0.879, 95% CI: 0.799-0.959, sensitivity of 99.3%, specificity of 38.5%), and an excellent predictor for placental dysfunction-related stillbirth (AUC 0.984, 95% CI: 0.960-1.000, sensitivity of 98.5, specificity of 85.7).Screening at 11-13 weeks' gestation by combining maternal factors, MAP, UtA-PI, and PlGF, can predict a high proportion of stillbirths. Our model has good accuracy for predicting stillbirths, predominantly placental dysfunction-related stillbirths.© 2024 The Author(s). International Journal of Gynecology & Obstetrics published by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics.

Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta‐analysis to assess their predictive performance.