Small for gestational age and perinatal mortality at term: An audit in a Dutch national cohort study

Maternal region of origin and Small for gestational age: a cross-sectional analysis of Victorian perinatal data

Background

Being born small for gestational age is a strong predictor of the short- and long-term health of the neonate, child, and adult. Variation in the rates of small for gestational age have been identified across population groups in high income countries, including Australia. Understanding the factors contributing to this variation may assist clinicians to reduce the morbidity and mortality associated with being born small. Victoria, in addition to New South Wales, accounts for the largest proportion of net overseas migration and births in Australia. The aim of this research was to analyse how migration was associated with small for gestational age in Victoria.

Methods

This was a cross sectional population health study of singleton births in Victoria from 2009 to 2018 (n = 708,475). The prevalence of being born small for gestational age (SGA; <10th centile) was determined for maternal region of origin groups. Multivariate logistic regression analysis was used to analyse the association between maternal region of origin and SGA.

Results

Maternal region of origin was an independent risk factor for SGA in Victoria (p < .001), with a prevalence of SGA for migrant women of 11.3% (n = 27,815) and 7.3% for Australian born women (n = 33,749). Women from the Americas (aOR1.24, 95%CI:1.14 to 1.36), North Africa, North East Africa, and the Middle East (aOR1.57, 95%CI:1.52 to 1.63); Southern Central Asia (aOR2.58, 95%CI:2.50 to 2.66); South East Asia (aOR2.02, 95%CI: 1.95 to 2.01); and sub-Saharan Africa (aOR1.80, 95%CI:1.69 to 1.92) were more likely to birth an SGA child in comparison to women born in Australia.

Conclusions

Victorian woman’s region of origin was an independent risk factor for SGA. Variation in the rates of SGA between maternal regions of origin suggests additional factors such as a woman’s pre-migration exposures, the context of the migration journey, settlement conditions and social environment post migration might impact the potential for SGA. These findings highlight the importance of intergenerational improvements to the wellbeing of migrant women and their children. Further research to identify modifiable elements that contribute to birthweight differences across population groups would help enable appropriate healthcare responses aimed at reducing the rate of being SGA.

Towards a better understanding of risk selection in maternal and newborn care: A systematic scoping review

Globally, millions of women and their children suffer due to preventable morbidity and mortality, associated with both underuse and overuse of maternal and newborn care. An effective system of risk selection that differentiates between what care should be provided and who should provide it is a global necessity to ensure women and children receive appropriate care, at the right place and the right time. Poor conceptualization of risk selection impedes evaluation and comparison of models of risk selection across various settings, which is necessary to improve maternal and newborn care. We conducted a scoping review to enhance the understanding of risk selection in maternal and newborn care. We included 210 papers, published over the past four decades, originating from 24 countries. Using inductive thematic analysis, we identified three main dimensions of risk selection: (1) risk selection as an organisational measure to optimally align women's and children's needs and resources, (2) risk selection as a practice to detect and assess risk and to make decisions about the delivery of care, and (3) risk selection as a tool to ensure safe care. We found that these three dimensions have three themes in common: risk selection (1) is viewed as both requiring and providing regulation, (2) has a provider centred focus and (3) aims to avoid underuse of care. Due to the methodological challenges of contextual diversity, the concept of risk selection needs clear indicators that capture the complexity of care to make cross-setting evaluation and comparison of risk selection possible. Moreover, a comprehensive understanding of risk selection needs to consider access disparity, women's needs, and unnecessary medicalization.

Prediction of Preeclampsia and Intrauterine Growth Restriction: Development of Machine Learning Models on a Prospective Cohort

BACKGROUND

Preeclampsia and intrauterine growth restriction are placental dysfunction-related disorders (PDDs) that require a referral decision be made within a certain time period. An appropriate prediction model should be developed for these diseases. However, previous models did not demonstrate robust performances and/or they were developed from datasets with highly imbalanced classes.

OBJECTIVE

In this study, we developed a predictive model of PDDs by machine learning that uses features at 24-37 weeks' gestation, including maternal characteristics, uterine artery (UtA) Doppler measures, soluble fms-like tyrosine kinase receptor-1 (sFlt-1), and placental growth factor (PlGF).

METHODS

A public dataset was taken from a prospective cohort study that included pregnant women with PDDs (66/95, 69%) and a control group (29/95, 31%). Preliminary selection of features was based on a statistical analysis using SAS 9.4 (SAS Institute). We used Weka (Waikato Environment for Knowledge Analysis) 3.8.3 (The University of Waikato, Hamilton, NZ) to automatically select the best model using its optimization algorithm. We also manually selected the best of 23 white-box models. Models, including those from recent studies, were also compared by interval estimation of evaluation metrics. We used the Matthew correlation coefficient (MCC) as the main metric. It is not overoptimistic to evaluate the performance of a prediction model developed from a dataset with a class imbalance. Repeated 10-fold cross-validation was applied.

RESULTS

The classification via regression model was chosen as the best model. Our model had a robust MCC (.93, 95% CI .87-1.00, vs .64, 95% CI .57-.71) and specificity (100%, 95% CI 100-100, vs 90%, 95% CI 90-90) compared to each metric of the best models from recent studies. The sensitivity of this model was not inferior (95%, 95% CI 91-100, vs 100%, 95% CI 92-100). The area under the receiver operating characteristic curve was also competitive (0.970, 95% CI 0.966-0.974, vs 0.987, 95% CI 0.980-0.994). Features in the best model were maternal weight, BMI, pulsatility index of the UtA, sFlt-1, and PlGF. The most important feature was the sFlt-1/PlGF ratio. This model used an M5P algorithm consisting of a decision tree and four linear models with different thresholds. Our study was also better than the best ones among recent studies in terms of the class balance and the size of the case class (66/95, 69%, vs 27/239, 11.3%).

CONCLUSIONS

Our model had a robust predictive performance. It was also developed to deal with the problem of a class imbalance. In the context of clinical management, this model may improve maternal mortality and neonatal morbidity and reduce health care costs.

Adverse perinatal outcomes in 665,244 term and post-term deliveries-a Norwegian population-based study

OBJECTIVE

To assess the prevalence and risk of adverse perinatal outcomes in early-term (37⁺⁰-38⁺⁶ weeks), full-term (39⁺⁰-40⁺⁶ weeks), late-term (41⁺⁰-41⁺⁶ weeks), and post-term (>42⁺⁰ weeks) deliveries with spontaneous labor onset.

STUDY DESIGN

A population-based cohort with data from the Medical Birth Registry Norway (MBRN) and Statistics Norway (SSB) was conducted. The study population consisted of 665,244 women with cephalic singleton live births at term or post-term with spontaneous labor onset during the period of 1999-2014 in Norway. Maternal, obstetric, and fetal characteristics were obtained from the MBRN. Maternal education data were obtained from the SSB. The prevalence rates of adverse perinatal outcomes for each gestational age (GA) group were estimated. Inter-group differences were detected with Chi square tests. Multivariable regression analysis adjusted for maternal age, educational level, smoking, parity, maternal diabetes, and preeclampsia was used to assess adverse outcome prevalence for early- late-, and post-term births compared to full-term births.

RESULTS

Deliveries at early-term were associated with an increased prevalence of neonatal jaundice, polyhydramnios, small for gestational age (SGA) status, respiratory support, and neonatal intensive care unit (NICU) admission compared with deliveries at GAs of 39-43 weeks (p < 0.001). Low 5-min Apgar scores and newborn antibiotic treatment occurred at an increased prevalence in both early-term and post-term infants, relative to the full-term group (p < 0.001). The prevalence of oligohydramnios, meconium-stained amniotic fluid, and newborn birth injuries increased with increasing GA.

CONCLUSIONS

More perinatal morbidity was observed among early-term infants compared to infants with later term deliveries, underscoring the need for cautious management of low-risk early-term deliveries.

Complex, coordinated and highly regulated changes in placental signaling and nutrient transport capacity in IUGR

The most common cause of intrauterine growth restriction (IUGR) in the developed world is placental insufficiency, a concept often used synonymously with reduced utero-placental and umbilical blood flows. However, placental insufficiency and IUGR are associated with complex, coordinated and highly regulated changes in placental signaling and nutrient transport including inhibition of insulin and mTOR signaling and down-regulation of specific amino acid transporters, Na+/K+-ATPase, the Na+/H+-exchanger, folate and lactate transporters. In contrast, placental glucose transport capacity is unaltered and Ca2+-ATPase activity and the expression of proteins involved in placental lipid transport are increased in IUGR. These findings are not entirely consistent with the traditional view that the placenta is dysfunctional in IUGR, but rather suggest that the placenta adapts to reduce fetal growth in response to an inability of the mother to allocate resources to the fetus. This new model has implications for the understanding of the mechanisms underpinning IUGR and for the development of intervention strategies.

Cerebral-placental-uterine ratio as novel predictor of late fetal growth restriction: prospective cohort study

OBJECTIVE

Fetal growth restriction (FGR) is a major risk factor for stillbirth and most commonly arises from uteroplacental insufficiency. Despite clinical examination and third-trimester fetal biometry, cases of FGR often remain undetected antenatally. Placental insufficiency is known to be associated with altered blood flow resistance in maternal, placental and fetal vessels. The aim of this study was to evaluate the performance of individual and combined Doppler blood flow resistance measurements in the prediction of term small-for-gestational age and FGR.

METHODS

This was a prospective study of 347 nulliparous women with a singleton pregnancy at 36 weeks' gestation in which fetal growth and Doppler measurements were obtained. Pulsatility indices (PI) of the uterine arteries (UtA), umbilical artery (UA) and fetal vessels were analyzed, individually and in combination, for prediction of birth weight < 10^th , < 5^th and < 3^rd centiles. Doppler values were converted into centiles or multiples of the median (MoM) for gestational age. The sensitivities, positive and negative predictive values and odds ratios (OR) of the Doppler parameters for these birth weights at ∼ 90% specificity were assessed. Additionally, the correlations between Doppler measurements and other measures of placental insufficiency, namely fetal growth velocity and neonatal body fat measures, were analyzed.

RESULTS

The Doppler combination most strongly associated with placental insufficiency was a newly generated parameter, which we have named the cerebral-placental-uterine ratio (CPUR). CPUR is the cerebroplacental ratio (CPR) (middle cerebral artery PI/UA-PI) divided by mean UtA-PI. CPUR MoM detected FGR better than did mean UtA-PI MoM or CPR MoM alone. At ∼ 90% specificity, low CPUR MoM had sensitivities of 50% for birth weight < 10^th centile, 68% for < 5^th centile and 89% for < 3^rd centile. The respective sensitivities of low CPR MoM were 26%, 37% and 44% and those of high UtA-PI MoM were 34%, 47% and 67%. Low CPUR MoM was associated with birth weight < 10^th centile with an OR of 9.1, < 5^th centile with an OR of 17.3 and < 3^rd centile with an OR of 57.0 (P < 0.0001 for all). CPUR MoM was also correlated most strongly with fetal growth velocity and neonatal body fat measures, as compared with CPR MoM or UtA-PI MoM alone.

CONCLUSIONS

In this cohort, a novel Doppler variable combination, the CPUR (CPR/UtA-PI), had the strongest association with indicators of placental insufficiency. CPUR detected more cases of FGR than did any other Doppler parameter measured. If these results are replicated independently, this new parameter may lead to better identification of fetuses at increased risk of stillbirth that may benefit from obstetric intervention. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.