Mid-pregnancy fetal growth, uteroplacental Doppler indices and maternal demographic characteristics: role in prediction of stillbirth

Fetal aortic isthmus Doppler assessment to predict the adverse perinatal outcomes associated with fetal growth restriction: systematic review and meta-analysis

PURPOSE

Fetal growth restriction (FGR) management and delivery planning is based on a multimodal approach. This meta-analysis aimed to evaluate the prognostic accuracies of the aortic isthmus Doppler to predict adverse perinatal outcomes in singleton pregnancies with FGR.

METHODS

PubMed, EMBASE, the Cochrane Library, ClinicalTrials.gov and Google scholar were searched from inception to May 2021, for studies on the prognostic accuracy of anterograde aortic isthmus flow compared with retrograde aortic isthmus flow in singleton pregnancy with FGR. The meta-analysis was registered on PROSPERO and was assessed according to PRISMA and Newcastle-Ottawa Scale. DerSimonian and Laird's random-effect model was used for relative risks, Freeman-Tukey Double Arcsine for pooled estimates and exact method to stabilize variances and CIs. Heterogeneity was quantified using I2 statistics.

RESULTS

A total of 2933 articles were identified through the electronic search, of which 6 studies (involving 240 women) were included. The quality evaluation of studies revealed an overall acceptable score for study group selection and comparability and substantial heterogeneity. The risk of perinatal death was significantly greater in fetuses with retrograde Aortic Isthmus blood flow, with a RR of 5.17 (p value 0.00001). Similarly, the stillbirth rate was found to have a RR of 5.39 (p value 0.00001). Respiratory distress syndrome had a RR of 2.64 (p value = 0.03) in the group of fetuses with retrograde Aortic Isthmus blood flow.

CONCLUSION

Aortic Isthmus Doppler study may add information for FGR management. However, additional clinical trial are required to assess its applicability in clinical practice.

Identifying risk of stillbirth using machine learning

BACKGROUND

Previous predictive models using logistic regression for stillbirth do not leverage the advanced and nuanced techniques involved in sophisticated machine learning methods, such as modeling nonlinear relationships between outcomes.

OBJECTIVE

This study aimed to create and refine machine learning models for predicting stillbirth using data available before viability (22-24 weeks) and throughout pregnancy, as well as demographic, medical, and prenatal visit data, including ultrasound and fetal genetics.

STUDY DESIGN

This is a secondary analysis of the Stillbirth Collaborative Research Network, which included data from pregnancies resulting in stillborn and live-born infants delivered at 59 hospitals in 5 diverse regions across the United States from 2006 to 2009. The primary aim was the creation of a model for predicting stillbirth using data available before viability. Secondary aims included refining models with variables available throughout pregnancy and determining variable importance.

RESULTS

Among 3000 live births and 982 stillbirths, 101 variables of interest were identified. Of the models incorporating data available before viability, the random forests model had 85.1% accuracy (area under the curve) and high sensitivity (88.6%), specificity (85.3%), positive predictive value (85.3%), and negative predictive value (84.8%). A random forests model using data collected throughout pregnancy resulted in accuracy of 85.0%; this model had 92.2% sensitivity, 77.9% specificity, 84.7% positive predictive value, and 88.3% negative predictive value. Important variables in the previability model included previous stillbirth, minority race, gestational age at the earliest prenatal visit and ultrasound, and second-trimester serum screening.

CONCLUSION

Applying advanced machine learning techniques to a comprehensive database of stillbirths and live births with unique and clinically relevant variables resulted in an algorithm that could accurately identify 85% of pregnancies that would result in stillbirth, before they reached viability. Once validated in representative databases reflective of the US birthing population and then prospectively, these models may provide effective risk stratification and clinical decision-making support to better identify and monitor those at risk of stillbirth.

Maternal Race and Stillbirth: Cohort Study and Systematic Review with Meta-Analysis

Accurate identification of independent predictors of stillbirth is needed to define preventive strategies. We aim to examine the independent contribution of maternal race in the risk of stillbirth after adjusting for maternal characteristics and medical history. There are two components to the study: first, prospective screening in 168,966 women with singleton pregnancies coordinated by the Fetal Medicine Foundation (FMF) and second, a systematic review and meta-analysis of studies reporting on race and stillbirth. In the FMF study, logistic regression analysis found that in black women, the risk of stillbirth, after adjustment for confounders, was higher than in white women (odds ratio 1.78, 95% confidence interval 1.50 to 2.11). The risk for other racial groups was not significantly different. The literature search identified 20 studies that provided data on over 6,500,000 pregnancies, but only 10 studies provided risks adjusted for some maternal characteristics; consequently, the majority of these studies did not provide accurate contribution of different racial groups to the prediction of stillbirth. It is concluded that in women of black origin, the risk of stillbirth, after adjustment for confounders, is about twofold higher than in white women. Consequently, closer surveillance should be granted for these women.

Abnormal placental perfusion and the risk of stillbirth: a hospital-based retrospective cohort study

Background

A lack of information on specific and interventional factors for stillbirth has made designing preventive strategies difficult, and the stillbirth rate has declined more slowly than the neonatal death rate. We compared the prevalence of stillbirth among the offspring of women with or without abnormal placental perfusion (APP).

Methods

We conducted a hospital-based retrospective cohort study involving women with a singleton pregnancy between 2012 and 2016 (N = 41,632). Multivariate analysis was performed to compare the prevalence of stillbirth in infants exposed to APP (defined as any abnormality in right or left uterine artery pulsatility index or resistance index [UtA-PI, −RI] [e.g., > 95th percentile] or presence of early diastolic notching) with that in those not exposed to APP.

Results

Stillbirths were more common among women with APP than among those with normal placental perfusion (stillbirth rate, 4.3 ‰ vs 0.9 ‰; odds ratio (OR), 4.2; 95% confidence interval (CI), 2.2 to 8.0). The association strengths were consistent across groups of infants exposed to APP that separately defined by abnormality in right or left UtA-PI or -RI (OR ranged from 3.2 to 5.3; all P ≤ 0.008). The associations were slightly stronger for the unexplained stillbirths. Most of the unexplained stillbirth risk was attributed to APP (59.0%), while a foetal sex disparity existed (94.5% for males and 58.0% for females). Women with normal placental perfusion and a male foetus had higher credibility (e.g., higher specificities) in excluding stillbirths than those with APP and a female foetus at any given false negative rate from 1 to 10% (93.4% ~ 94.1% vs. 12.3% ~ 14.0%).

Conclusions

APP is associated with and accounts for most of the unexplained stillbirth risk. Different mechanisms exist between the sexes. The performance of screening for stillbirth may be improved by stratification according to sex and placental perfusion.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-03776-8.

Antenatal Antidepressant Prescription Associated With Reduced Fetal Femur Length but Not Estimated Fetal Weight: A Retrospective Ultrasonographic Study

PURPOSE/BACKGROUND

Antidepressants are among the most frequently prescribed medications during pregnancy and may affect fetal weight. Associations between antenatal antidepressant use and ultrasonographic measures of fetal development have rarely been examined. We hypothesized that the prescription of an antenatal antidepressant would be associated with lower estimated fetal weight (EFW).

METHODS/PROCEDURES

A retrospective analysis of routine ultrasonographic data extracted from electronic medical records was performed on a cohort of pregnant women with psychiatric diagnoses and grouped according to the presence of an antenatal antidepressant prescription (n = 32 antidepressant-prescribed and n = 44 antidepressant prescription-free). After stratifying for gestational age, comparisons included 13 ultrasonographic parameters, frequency of oligohydramnios and polyhydramnios and growth deceleration, and maternal serum protein markers assessed per routine care, including α-fetoprotein, free β-human chorionic gonadotropin, and unconjugated estriol levels, using t tests, nonparametric and Fisher tests, and effect sizes (ESs) were computed.

FINDINGS/RESULTS

No statistically significant EFW differences between groups at any time point were detected (P > 0.05). Antenatal antidepressant prescription was associated with lower femur length at weeks 33 to 40 (P = 0.046, ES = 0.75) and greater left ventricular diameter at weeks 25 to 32 (P = 0.04, ES = 1.18). No differences for frequency of oligohydramnios or polyhydramnios or growth deceleration were observed (P > 0.05). We did not detect group differences for maternal proteins (P > 0.05).

IMPLICATIONS/CONCLUSIONS

Our evidence suggested a lack of association between antenatal antidepressant prescription and lower EFW but indicated an association with lower femur length and greater left ventricular diameter in mid-late gestation. Future research should examine the clinical implications of these findings.

Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models

BACKGROUND

Stillbirth prevention is an international priority - risk prediction models could individualise care and reduce unnecessary intervention, but their use requires evaluation.

OBJECTIVES

To identify risk prediction models for stillbirth, and assess their potential accuracy and clinical benefit in practice.

SEARCH STRATEGY

MEDLINE, Embase, DH-DATA and AMED databases were searched from inception to June 2019 using terms relevant to stillbirth, perinatal mortality and prediction models. The search was compliant with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines.

SELECTION CRITERIA

Studies developing and/or validating prediction models for risk of stillbirth developed for application during pregnancy.

DATA COLLECTION AND ANALYSIS

Study screening and data extraction were conducted in duplicate, using the CHARMS checklist. Risk of bias was appraised using the PROBAST tool.

RESULTS

The search identified 2751 citations. Fourteen studies reporting development of 69 models were included. Variables consistently included were: ethnicity, body mass index, uterine artery Doppler, pregnancy-associated plasma protein and placental growth factor. For almost all models there were significant concerns about risk of bias. Apparent model performance (i.e. in the development dataset) was highest in models developed for use later in pregnancy and including maternal characteristics, and ultrasound and biochemical variables, but few were internally validated and none were externally validated.

CONCLUSIONS

Almost all models identified were at high risk of bias. There are first-trimester models of possible clinical benefit in early risk stratification; these require validation and clinical evaluation. There were few later pregnancy models but, if validated, these could be most relevant to individualised discussions around timing of birth.

TWEETABLE ABSTRACT

Prediction models using maternal factors, blood tests and ultrasound could individualise stillbirth prevention, but existing models are at high risk of bias.

Maternal cardiovascular function and risk of intrapartum fetal compromise in women undergoing induction of labor: pilot study

OBJECTIVE

Identification of the fetus at risk of intrapartum compromise has many benefits. Impaired maternal cardiovascular function is associated with placental hypoperfusion predisposing to intrapartum fetal distress. The aim of this study was to assess the predictive accuracy of maternal hemodynamics for the risk of operative delivery due to presumed fetal compromise in women undergoing induction of labor (IOL).

METHODS

In this prospective cohort study, patients were recruited between November 2018 and January 2019. Women undergoing IOL were invited to participate in the study. A non-invasive ultrasonic cardiac output monitor (USCOM-1A®) was used for cardiovascular assessment. The study outcome was operative delivery due to presumed fetal compromise, which included Cesarean or instrumental delivery for abnormal fetal heart monitoring. Regression analysis was used to test the association between cardiovascular markers, as well as the maternal characteristics, and the risk of operative delivery due to presumed fetal compromise. Receiver-operating-characteristics-curve analysis was used to assess the predictive accuracy of the cardiovascular markers for the risk of operative delivery for presumed fetal compromise.

RESULTS

A total of 99 women were recruited, however four women were later excluded from the analysis due to semi-elective Cesarean section (n = 2) and failed IOL (n = 2). The rate of operative delivery due to presumed fetal compromise was 28.4% (27/95). Women who delivered without suspected fetal compromise (controls) were more likely to be parous, compared to those who had operative delivery due to fetal compromise (52.9% vs 18.5%; P = 0.002). Women who underwent operative delivery due to presumed fetal compromise had a significantly lower cardiac index (median, 2.50 vs 2.60 L/min/m² ; P = 0.039) and a higher systemic vascular resistance (SVR) (median, 1480 vs 1325 dynes × s/cm⁵ , P = 0.044) compared to controls. The baseline model (being parous only) showed poor predictive accuracy, with an area under the curve of 0.67 (95% CI, 0.58-0.77). The addition of stroke volume index (SVI) < 36 mL/m² , SVR > 7.2 logs or SVR index (SVRI) > 7.7 logs improved significantly the predictive accuracy of the baseline model (P = 0.012, P = 0.026 and P = 0.012, respectively).

CONCLUSION

In this pilot study, we demonstrated that prelabor maternal cardiovascular assessment in women undergoing IOL could be useful for assessing the risk of intrapartum fetal compromise necessitating operative delivery. The addition of SVI, SVR or SVRI improved significantly the predictive accuracy of the baseline antenatal model. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

The prediction of early preeclampsia: Results from a longitudinal proteomics study

OBJECTIVES

To identify maternal plasma protein markers for early preeclampsia (delivery <34 weeks of gestation) and to determine whether the prediction performance is affected by disease severity and presence of placental lesions consistent with maternal vascular malperfusion (MVM) among cases.

STUDY DESIGN

This longitudinal case-control study included 90 patients with a normal pregnancy and 33 patients with early preeclampsia. Two to six maternal plasma samples were collected throughout gestation from each woman. The abundance of 1,125 proteins was measured using high-affinity aptamer-based proteomic assays, and data were modeled using linear mixed-effects models. After data transformation into multiples of the mean values for gestational age, parsimonious linear discriminant analysis risk models were fit for each gestational-age interval (8-16, 16.1-22, 22.1-28, 28.1-32 weeks). Proteomic profiles of early preeclampsia cases were also compared to those of a combined set of controls and late preeclampsia cases (n = 76) reported previously. Prediction performance was estimated via bootstrap.

RESULTS

We found that 1) multi-protein models at 16.1-22 weeks of gestation predicted early preeclampsia with a sensitivity of 71% at a false-positive rate (FPR) of 10%. High abundance of matrix metalloproteinase-7 and glycoprotein IIbIIIa complex were the most reliable predictors at this gestational age; 2) at 22.1-28 weeks of gestation, lower abundance of placental growth factor (PlGF) and vascular endothelial growth factor A, isoform 121 (VEGF-121), as well as elevated sialic acid binding immunoglobulin-like lectin 6 (siglec-6) and activin-A, were the best predictors of the subsequent development of early preeclampsia (81% sensitivity, FPR = 10%); 3) at 28.1-32 weeks of gestation, the sensitivity of multi-protein models was 85% (FPR = 10%) with the best predictors being activated leukocyte cell adhesion molecule, siglec-6, and VEGF-121; 4) the increase in siglec-6, activin-A, and VEGF-121 at 22.1-28 weeks of gestation differentiated women who subsequently developed early preeclampsia from those who had a normal pregnancy or developed late preeclampsia (sensitivity 77%, FPR = 10%); 5) the sensitivity of risk models was higher for early preeclampsia with placental MVM lesions than for the entire early preeclampsia group (90% versus 71% at 16.1-22 weeks; 87% versus 81% at 22.1-28 weeks; and 90% versus 85% at 28.1-32 weeks, all FPR = 10%); and 6) the sensitivity of prediction models was higher for severe early preeclampsia than for the entire early preeclampsia group (84% versus 71% at 16.1-22 weeks).

CONCLUSION

We have presented herein a catalogue of proteome changes in maternal plasma proteome that precede the diagnosis of preeclampsia and can distinguish among early and late phenotypes. The sensitivity of maternal plasma protein models for early preeclampsia is higher in women with underlying vascular placental disease and in those with a severe phenotype.

A reference range of fetal abdominal circumference growth velocity between 20 and 36 weeks' gestation

OBJECTIVE

To create a single equation and reference range for abdominal circumference growth velocity (ACGV) between 20 and 36 weeks in singleton pregnancies.

METHOD

Observational study of pregnant women having routine scans for abdominal circumference (AC) at 20 and 36 weeks' gestation. Exclusion criteria were multiple pregnancy, abnormal karyotype, major fetal abnormalities, and absent data on first-trimester dating. Scan image quality and AC measurement reliability were assessed according to INTERGROWTH-21st criteria. Regression models for the AC mean and standard deviation were fitted separately at 20 and 36 weeks, and z scores were calculated. Abdominal circumference growth velocity was defined as the z score difference between 20 and 36 weeks divided by the interval in days and multiplied by 100.

RESULTS

The study population included 3334 fetuses. The equation for ACGV is (((AC₃₆  - 53.090 - 1.081*GA₃₆ )/(0.057638*GA₃₆  + 0.622741)) - ((AC₂₀  + 68.349 - 1.571*GA₂₀ )/(0.06265*GA₂₀  - 2.55361)))*100/(GA₃₆  - GA₂₀ ), where AC is expressed in millimeters and GA is gestational age in days. The 3rd, 5th, 10th, 50th, 90th, 95th, and 97th centiles are -1.8997, -1.6785, -1.3091, -0.0069, 1.3255, 1.7279, 1.9973, respectively.

CONCLUSION

We have defined ACGV between 20 and 36 weeks, and we have established its reference range. Further studies are needed to evaluate the clinical significance of growth patterns in the tail ends of this distribution.

Improved pregnancy outcomes in women with type 1 and type 2 diabetes but substantial clinic-to-clinic variations: a prospective nationwide study

AIMS/HYPOTHESIS

The aim of this prospective nationwide study was to examine antenatal pregnancy care and pregnancy outcomes in women with type 1 and type 2 diabetes, and to describe changes since 2002/2003.

METHODS

This national population-based cohort included 3036 pregnant women with diabetes from 155 maternity clinics in England and Wales who delivered during 2015. The main outcome measures were maternal glycaemic control, preterm delivery (before 37 weeks), infant large for gestational age (LGA), and rates of congenital anomaly, stillbirth and neonatal death.

RESULTS

Of 3036 women, 1563 (51%) had type 1, 1386 (46%) had type 2 and 87 (3%) had other types of diabetes. The percentage of women achieving HbA1c < 6.5% (48 mmol/mol) in early pregnancy varied greatly between clinics (median [interquartile range] 14.3% [7.7-22.2] for type 1, 37.0% [27.3-46.2] for type 2). The number of infants born preterm (21.7% vs 39.7%) and LGA (23.9% vs 46.4%) were lower for women with type 2 compared with type 1 diabetes (both p < 0.001). The prevalence rates for congenital anomaly (46.2/1000 births for type 1, 34.6/1000 births for type 2) and neonatal death (8.1/1000 births for type 1, 11.4/1000 births for type 2) were unchanged since 2002/2003. Stillbirth rates are almost 2.5 times lower than in 2002/2003 (10.7 vs 25.8/1000 births for type 1, p = 0.0012; 10.5 vs 29.2/1000 births for type 2, p = 0.0091).

CONCLUSIONS/INTERPRETATION

Stillbirth rates among women with type 1 and type 2 diabetes have decreased since 2002/2003. Rates of preterm delivery and LGA infants are lower in women with type 2 compared with type 1 diabetes. In women with type 1 diabetes, suboptimal glucose control and high rates of perinatal morbidity persist with substantial variations between clinics.

DATA AVAILABILITY

Further details of the data collection methodology, individual clinic data and the full audit reports for healthcare professionals and service users are available from http://content.digital.nhs.uk/npid .