Second and third trimester fetal ultrasound population screening for risks of preterm birth and small-size and large-size for gestational age at birth: a population-based prospective cohort study

Indicated vs universal third-trimester ultrasound examination in low-risk pregnancies: a pre-post-intervention study

BACKGROUND

In low-risk pregnancies, a third-trimester ultrasound examination is indicated if fundal height measurement and gestational age discrepancy are observed. Despite potential improvement in the detection of ultrasound abnormality, prior trials to date on universal third-trimester ultrasound examination in low-risk pregnancies, compared with indicated ultrasound examination, have not demonstrated improvement in neonatal or maternal adverse outcomes.

OBJECTIVE

The primary objective was to determine if universal third-trimester ultrasound examination in low-risk pregnancies could attenuate composite neonatal adverse outcomes. The secondary objectives were to compare changes in composite maternal adverse outcomes and detection of abnormalities of fetal growth (fetal growth restriction or large for gestational age) or amniotic fluid (oligohydramnios or polyhydramnios).

STUDY DESIGN

Our pre-post intervention study at 9 locations included low-risk pregnancies, those without indication for ultrasound examination in the third trimester. Compared with indicated ultrasound in the preimplementation period, in the postimplementation period, all patients were scheduled for ultrasound examination at 36.0-37.6 weeks. In both periods, clinicians intervened on the basis of abnormalities identified. Composite neonatal adverse outcomes included any of: Apgar score ≤5 at 5 minutes, cord pH <7.00, birth trauma (bone fracture or brachial plexus palsy), intubation for >24 hours, hypoxic-ischemic encephalopathy, seizure, sepsis (bacteremia proven with blood culture), meconium aspiration syndrome, intraventricular hemorrhage grade III or IV, periventricular leukomalacia, necrotizing enterocolitis, stillbirth after 36 weeks, or neonatal death within 28 days of birth. Composite maternal adverse outcomes included any of the following: chorioamnionitis, wound infection, estimated blood loss >1000 mL, blood transfusion, deep venous thrombus or pulmonary embolism, admission to intensive care unit, or death. Using Bayesian statistics, we calculated a sample size of 600 individuals in each arm to detect >75% probability of any reduction in primary outcome (80% power; 50% hypothesized risk reduction).

RESULTS

During the preintervention phase, 747 individuals were identified during the initial ultrasound examination, and among them, 568 (76.0%) met the inclusion criteria at 36.0-37.6 weeks; during the postintervention period, the corresponding numbers were 770 and 661 (85.8%). The rate of identified abnormalities of fetal growth or amniotic fluid increased from between the pre-post intervention period (7.1% vs 22.2%; P<.0001; number needed to diagnose, 7; 95% confidence interval, 5-9). The primary outcome occurred in 15 of 568 (2.6%) individuals in the preintervention and 12 of 661 (1.8%) in the postintervention group (83% probability of risk reduction; posterior relative risk, 0.69 [95% credible interval, 0.34-1.42]). The composite maternal adverse outcomes occurred in 8.6% in the preintervention and 6.5% in the postintervention group (90% probability of risk; posterior relative risk, 0.74 [95% credible interval, 0.49-1.15]). The number needed to treat to reduce composite neonatal adverse outcomes was 121 (95% confidence interval, 40-200). In addition, the number to reduce composite maternal adverse outcomes was 46 (95% confidence interval, 19-74), whereas the number to prevent cesarean delivery was 18 (95% confidence interval, 9-31).

CONCLUSION

Among low-risk pregnancies, compared with routine care with indicated ultrasound examination, implementation of a universal third-trimester ultrasound examination at 36.0-37.6 weeks attenuated composite neonatal and maternal adverse outcomes.

Multivariable prediction models for fetal macrosomia and large for gestational age: A systematic review

BACKGROUND

The identification of large for gestational age (LGA) and macrosomic fetuses is essential for counselling and managing these pregnancies.

OBJECTIVES

To systematically review the literature for multivariable prediction models for LGA and macrosomia, assessing the performance, quality and applicability of the included model in clinical practice.

SEARCH STRATEGY

MEDLINE, EMBASE and Cochrane Library were searched until June 2022.

SELECTION CRITERIA

We included observational and experimental studies reporting the development and/or validation of any multivariable prediction model for fetal macrosomia and/or LGA. We excluded studies that used a single variable or did not evaluate model performance.

DATA COLLECTION AND ANALYSIS

Data were extracted using the Checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist. The model performance measures discrimination, calibration and validation were extracted. The quality and completion of reporting within each study was assessed by its adherence to the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) checklist. The risk of bias and applicability were measured using PROBAST (Prediction model Risk Of Bias Assessment Tool).

MAIN RESULTS

A total of 8442 citations were identified, with 58 included in the analysis: 32/58 (55.2%) developed, 21/58 (36.2%) developed and internally validated and 2/58 (3.4%) developed and externally validated a model. Only three studies externally validated pre-existing models. Macrosomia and LGA were differentially defined by many studies. In total, 111 multivariable prediction models were developed using 112 different variables. Model discrimination was wide ranging area under the receiver operating characteristics curve (AUROC 0.56-0.96) and few studies reported calibration (11/58, 19.0%). Only 5/58 (8.6%) studies had a low risk of bias.

CONCLUSIONS

There are currently no multivariable prediction models for macrosomia/LGA that are ready for clinical implementation.

Prognostic Accuracy of Antenatal Doppler Ultrasound Measures in Predicting Adverse Perinatal Outcomes for Pregnancies Complicated by Diabetes: A Systematic Review

OBJECTIVE

This study aimed to assess the prognostic accuracies of Doppler ultrasound measures in predicting adverse perinatal outcomes for pregnancies complicated with preexisting or gestational diabetes mellitus.

DATA SOURCES

An online database search of MEDLINE, Cochrane, Embase, CINAHL, Scopus, and Emcare from inception to April 2022 was conducted.

STUDY ELIGIBILITY CRITERIA

Studies reporting singleton, nonanomalous fetuses of women with either preexisting (type 1 or 2 diabetes mellitus) or gestational diabetes mellitus during pregnancy were included. In addition, the included studies assessed cerebroplacental ratio and middle cerebral artery and/or umbilical artery pulsatility index in the prediction of either: preterm birth, cesarean delivery for fetal distress, APGAR (Appearance, Pulse, Grimace, Activity, and Respiration) score <7 at 5 minutes, neonatal intensive care unit admission (>24 hours), acute respiratory distress syndrome, jaundice, hypoglycemia, hypocalcemia, or neonatal death.

METHODS

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed and 610 articles were identified, of which 15 were included. Two authors independently extracted prognostic data from each article and assessed the study applicability and risk of bias using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2) scoring criteria.

RESULTS

A total of 15 studies were included in the review and comprised prospective (n=10; 66%) and retrospective (n=5; 33%) cohorts. Sensitivity and positive predictive values varied widely across each Doppler measurement. Umbilical artery sensitivities were higher than those of cerebroplacental ratio and middle cerebral artery for hypoglycemia, jaundice, neonatal intensive care unit admission, respiratory distress, and preterm birth. Cerebroplacental ratio was the most reported index test; however, prognostic accuracy was worse than that of umbilical artery and middle cerebral artery Doppler across all adverse perinatal outcomes. Significant risk of bias was present in 14 (94%) studies, with substantial heterogeneity observed across studies in terms of study design and outcomes assessed.

CONCLUSION

Abnormal umbilical artery pulsatility index may be of more clinical value in predicting adverse perinatal outcomes compared with cerebroplacental ratio and middle cerebral artery pulsatility index in diabetic pregnancies. Further evaluation of umbilical artery Doppler measurements in diabetic pregnancies using standardized variables across studies is required for broader clinical application. The significant association between abnormal Doppler measurement and hypoglycemia may warrant further investigation.

Impact of Maternal Monocyte to High-density Lipoprotein Cholesterol Ratio on the Incidence of Large-for-gestational-age Newborns: An Observational Cohort Study

BACKGROUND AND OBJECTIVES

Monocyte to high-density lipoprotein cholesterol ratio (MHR) has recently been identified as a new marker of inflammation and oxidative stress. However, it is unknown whether maternal MHR is associated with fetal weight at birth. Therefore, our objective was to analyze the association between maternal MHR and the frequency of small/large for gestational age (SGA/LGA) newborns in this retrospective cohort study.

METHODS

We retrospectively analyzed hospitalization records and laboratory data and obtained results from consecutive pregnant women in whom the blood lipid level had been investigated along with the blood cell count. Linear regression and logistic regression analyses were performed to estimate the associations of maternal MHR with birth weight and SGA/LGA.

RESULTS

Monocyte counts and MHR were positively associated with birth weight/LGA risk (monocyte [1-109/L increase] for birth weight: β: 170.24, 95% confidence interval [CI]: 41.72-298.76, LGA: odds ratio [OR]: 7.67; 95% CI: 2.56-22.98; MHR [1-109/mmol increase] for birth weight: β: 294.84, 95% CI: 170.23-419.44, LGA: OR: 7.97; 95% CI: 3.06-20.70), whereas high-density lipoprotein cholesterol (HDL-C) levels were negatively associated with birth weight/LGA risk [1 mmol/L increase for birth weight (β: -99.83, 95% CI: -130.47 to -69.19), for LGA: (OR: 0.57, 95% CI: 0.45-0.73). Obese pregnant women (body mass index [BMI] ≥30 kg/m2) with higher MHR (tertile 3: >0.33 109/mmol) significantly increased LGA risk by 6.39 fold (95% CI: 4.81, 8.49) compared to those with low MHR (tertile 1-2: ≤0.33 109/mmol) and normal weight (BMI <25 kg/m2).

CONCLUSION

Maternal MHR is associated with LGA risk, and this association might be further modified by BMI.

Relationship between Platelet-to-Lymphocyte Ratio and Lymphocyte-to-Monocyte Ratio with Spontaneous Preterm Birth: A Systematic Review and Meta-analysis

Background

Spontaneous preterm birth is one of the most common pregnancy complications in obstetric clinical practice, and its etiology is complex. The problems of low survival and high morbidity rates of premature infants need to be solved urgently. The platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) are two novel biomarkers of inflammation, and several studies have linked PLR and LMR to spontaneous preterm birth. These systematic review and meta-analysis are aimed at analyzing the relationship between PLR and LMR in patients with spontaneous preterm birth to provide new ideas for the early prevention and treatment of spontaneous preterm births.

Methods

Cochrane Library, EMBASE, PubMed, and China National Knowledge Infrastructure databases were inspected to gather PLR and LMR in patients with spontaneous preterm birth, all from the database to February 2022. Interstudy heterogeneity was evaluated using Cochran's Q test and I 2 statistic. Differences in PLR and LMR between patients with spontaneous preterm birth and full-term controls were evaluated by computing standardized mean differences and 95% confidence intervals. Publication bias and sensitivity analyses were also performed.

Results

Nine studies were included in the meta-analysis based on the inclusion and exclusion criteria. The meta-analysis showed that serum PLR values were remarkably larger for patients with spontaneous preterm birth than for full-term controls (SMD = 0.49, 95% CI: 0.13 to 0.84, P = 0.007), whereas the difference between serum LMR in patients with spontaneous preterm birth and full-term controls was not statistically significant (SMD: 0.35, 95% CI: -0.18, 0.88, P = 0.199). The results of Begg's and Egger's tests revealed that the publication bias of the meta-analysis was not significant. The outcomes of the sensitivity analysis showed that the individual studies did not influence the meta-analysis results.

Conclusions

Current evidence shows that PLR is strongly associated with spontaneous preterm birth, whereas LMR is not. PLR has a certain clinical value in diagnosing and treating spontaneous preterm births, and our research will provide strong theoretical support for clinical work. In the future, it will be necessary to further explore the reasons for the increased PLR in the serum of patients with spontaneous preterm birth and other mechanisms inducing spontaneous preterm birth.

Predicting preterm births from electrohysterogram recordings via deep learning

About one in ten babies is born preterm, i.e., before completing 37 weeks of gestation, which can result in permanent neurologic deficit and is a leading cause of child mortality. Although imminent preterm labor can be detected, predicting preterm births more than one week in advance remains elusive. Here, we develop a deep learning method to predict preterm births directly from electrohysterogram (EHG) measurements of pregnant mothers recorded at around 31 weeks of gestation. We developed a prediction model, which includes a recurrent neural network, to predict preterm births using short-time Fourier transforms of EHG recordings and clinical information from two public datasets. We predicted preterm births with an area under the receiver-operating characteristic curve (AUC) of 0.78 (95% confidence interval: 0.76-0.80). Moreover, we found that the spectral patterns of the measurements were more predictive than the temporal patterns, suggesting that preterm births can be predicted from short EHG recordings in an automated process. We show that preterm births can be predicted for pregnant mothers around their 31st week of gestation, prompting beneficial treatments to reduce the incidence of preterm births and improve their outcomes.

Impact of Isolation measures on pregnancy outcome during the COVID-19 pandemic

This study aims to explore the impact of isolation measures implemented during the COVID-19 pandemic on childbirth outcomes in pregnant women. The design was a retrospective cohort study. The pregnant women during the outbreak lockdown and isolation from February 1 to April 30, 2020, were defined as the exposed population, and the pregnant women in the same time frame in 2019 as the non-exposed population. All data for the study were obtained from the National Health Care Data Platform of Shandong University. Generalized linear regression models were used to analyze the differences in pregnancy outcomes between the two study groups. A total of 34,698 pregnant women from Shandong Province, China in the data platform met the criteria and were included in the study. The proportions were 11.53% and 8.93% for macrosomia in the exposed and the non-exposed groups and were 3.47% and 4.37% for low birth weight infants, respectively, which were significantly different. They were 22.55% and 25.94% attributed to average exposed effect for macrosomia and low birth weight infants. Meanwhile, the mean weight and standard deviation of full-term infants in the exposure group were 3414.80 ± 507.43 g, which were significantly higher than in the non-exposed group (3347.22 ± 502.57 g, P < 0.001). The effect of exposure was significant in the third trimester. In conclusion, the isolation during the COVID-19 pandemic increases the birth weight of infants and the probability of macrosomia, regardless of which trimester in isolation a pregnant woman was, while the third trimester is the sensitive window of exposure. Our findings provide a basis for health care and policy development during pregnancy in COVID-19, due to COVID-19 still showing a pandemic trend around the world in 2022.

Third trimester uterine artery Doppler for prediction of adverse perinatal outcomes

PURPOSE OF REVIEW

Abnormal uterine artery Doppler (UtAD) studies early in gestation have been associated with adverse pregnancy outcomes. However, their association with complications in the third trimester is weak. We aim to review the prediction ability for perinatal complications of these indices in the third trimester.

RECENT FINDINGS

Abnormal UtAD waveforms in the third trimester are associated with preeclampsia, small-for-gestational age infants (SGA), preterm birth, perinatal death, and other perinatal complications, such as cesarean section for fetal distress, 5 min low Apgar score, low umbilical artery pH, and neonatal admission to the ICU, particularly in SGA infants. UtAD prediction performance is improved by the addition of maternal characteristics as well as biochemical markers to prediction models and is more precise if the evaluation is made closer to delivery or diagnosis.

SUMMARY

This review shows that the prediction accuracy of UtAD for adverse pregnancy outcomes during the third trimester is moderate at best. UtAD have limited additive value to prediction models that include PlGF and sFlt-1. Serial assessments rather than a single third trimester evaluation may enhance the prediction performance of the UtAD combined models.

Prediction of small-for-gestational-age neonates at 33-39 weeks' gestation in China: logistic regression modeling of the contributions of second- and third-trimester ultrasound data and maternal factors

Objectives

A screening model for prediction of small-for-gestational-age (SGA) neonates (SGAp) was established by logistic regression using ultrasound data and maternal factors (MF). We aimed to evaluate the ability of SGAp as well as abdominal circumference (AC) and estimated fetal weight (EFW) measurements to predict SGA neonates at 33–39 weeks’ gestation.

Methods

This retrospective study evaluated 5298 singleton pregnancies that had involved three ultrasound examinations at 21⁺⁰–27⁺⁶, 28⁺⁰–32⁺⁶, and 33⁺⁰–39⁺⁶ weeks. All ultrasound data were transformed to MoM values (multiple of the median). Multivariate logistic regression was used to analyze the correlation between SGA status and various variables (ultrasound data and MF) during pregnancy to build the SGAp model. EFW was calculated according to the Hadlock formula at 33–39 weeks of gestation. The predictive performance of SGAp, AC MoM value at 33⁺⁰–39⁺⁶ weeks (AC-M), EFW MoM value (EFW-M), EFW-M plus MF, AC value at 33⁺⁰–39⁺⁶ weeks (AC), AC growth velocity, EFW, and EFW plus MF was evaluated using ROC curves. The detection rate (DR) of SGA neonate with SGAp, AC-M, EFW-M, and EFW-M plus MF at false positive rate (FPR) of 5% and 10%, and the FPR at DR of 85%, 90%, and 95% were observed.

Results

The AUCs of SGAp, AC-M, EFW-M, EFW-M plus MF, AC, AC growth velocity, EFW, and EFW plus MF for SGA neonates screening were 0.933 (95%CI: 0.916–0.950), 0.906 (95%CI: 0.887–0.925), 0.920 (95%CI: 0.903–0.936), 0.925 (95%CI: 0.909–0.941), 0.818 (95%CI: 0.791–0.845), 0.786 (95%CI: 0.752–0.821), 0.810 (95%CI: 0.782–0.838), and 0.834 (95%CI: 0.807–0.860), respectively. The screening efficiency of SGAp, AC-M, EFW-M, and EFW-M plus MF are significantly higher than AC, AC growth velocity, EFW, and EFW plus MF. The DR of SGAp, AC-M, EFW-M, and EFW-M plus MF for SGA neonates were 80.4%, 69.6%, 73.8% and 74.3% at 10% FPR. The AUCs of SGAp, AC-M, EFW-M, and EFW-M plus MF 0.950 (95%CI: 0.932–0.967), 0.929 (95%CI: 0.909–0.948), 0.938 (95%CI: 0.921–0.956) and 0.941 (95%CI: 0.924–0.957), respectively for screening SGA neonates delivered within 2 weeks after the assessment. The DR for these births increased to 85.8%, 75.8%, 80.0%, and 82.5%, respectively.

Conclusion

The rational use of ultrasound data can significantly improve the prediction of SGA statuses.

The effect of snakehead fish (Channa striata) cookies supplementation on fetal growth and birth outcomes: A randomized clinical trial

BACKGROUND: An estimated 15–20% of all births worldwide are low birth weight (LBW). In Indonesia, the LBW incidence reached more than 10% in 2013. Improved maternal nutrition is needed by providing high-calorie-protein supplementation for pregnant women to prevent intrauterine growth retardation and LBW. OBJECTIVES: To observe the effect of snakehead fish (Channa striata) cookies supplementation during pregnancy on fetal growth and birth outcomes. METHODS: A total of 50 pregnant women were included in this randomized controlled trial study and were randomly allocated into two groups: treatment and controls. Subjects in the treatment group received supplementation of snakehead fish cookies during pregnancy until giving birth as much as 75 g per day, while subjects in the control group received standard cookies. The snakehead fish cookies underwent a formulation process and were tested for nutrient content and microbial contamination to ensure safety before being given to the subjects. Fetal growth was monitored monthly using 2-dimensional ultrasonography. RESULTS: The average intake of cookies did not differ between the two groups (Control 69.6 (16.8)% vs Snakehead fish 64.6 (15.3)%, p = 0.278). There were no significant differences in fetal estimated fetal weight, biparietal diameter, abdominal circumference, femur length, birth weight, and birth length between the treatment and control groups (p >  0.05). However, the fetal growth measurements on the subjects who consumed snakehead fish cookies were practically higher than those who ate standard cookies. CONCLUSION: The snakehead fish cookies did improve the fetal growth measurements but the results were not significantly different when compared to standard cookies.

Risk scores for predicting small for gestational age infants in Japan: The TMM birthree cohort study

This study aimed to construct a prediction model for small-for-gestational-age (SGA) infants in Japan by creating a risk score during pregnancy. A total of 17,073 subjects were included in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study, a prospective cohort study. A multiple logistic regression model was used to construct risk scores during early and mid-gestational periods (11–17 and 18–21 weeks of gestation, respectively). The risk score during early gestation comprised the maternal age, height, body mass index (BMI) during early gestation, parity, assisted reproductive technology (ART) with frozen-thawed embryo transfer (FET), smoking status, blood pressure (BP) during early gestation, and maternal birth weight. The risk score during mid-gestation also consisted of the maternal age, height, BMI during mid-gestation, weight gain, parity, ART with FET, smoking status, BP level during mid-gestation, maternal birth weight, and estimated fetal weight during mid-gestation. The C-statistics of the risk scores during early- and mid-gestation were 0.658 (95% confidence interval [CI]: 0.642–0.675) and 0.725 (95% CI: 0.710–0.740), respectively. In conclusion, the predictive ability of the risk scores during mid-gestation for SGA infants was acceptable and better than that of the risk score during early gestation.

Personalized Model to Predict Small for Gestational Age at Delivery Using Fetal Biometrics, Maternal Characteristics, and Pregnancy Biomarkers: A Retrospective Cohort Study of Births Assisted at a Spanish Hospital

Small for gestational age (SGA) is defined as a newborn with a birth weight for gestational age < 10th percentile. Routine third-trimester ultrasound screening for fetal growth assessment has detection rates (DR) from 50 to 80%. For this reason, the addition of other markers is being studied, such as maternal characteristics, biochemical values, and biophysical models, in order to create personalized combinations that can increase the predictive capacity of the ultrasound. With this purpose, this retrospective cohort study of 12,912 cases aims to compare the potential value of third-trimester screening, based on estimated weight percentile (EPW), by universal ultrasound at 35−37 weeks of gestation, with a combined model integrating maternal characteristics and biochemical markers (PAPP-A and β-HCG) for the prediction of SGA newborns. We observed that DR improved from 58.9% with the EW alone to 63.5% with the predictive model. Moreover, the AUC for the multivariate model was 0.882 (0.873−0.891 95% C.I.), showing a statistically significant difference with EPW alone (AUC 0.864 (95% C.I.: 0.854−0.873)). Although the improvements were modest, contingent detection models appear to be more sensitive than third-trimester ultrasound alone at predicting SGA at delivery.

Preconception and early-pregnancy risk prediction for birth complications: development of prediction models within a population-based prospective cohort

Background

Suboptimal maternal health already from preconception onwards is strongly linked to an increased risk of birth complications. To enable identification of women at risk of birth complications, we aimed to develop a prediction model for birth complications using maternal preconception socio-demographic, lifestyle, medical history and early-pregnancy clinical characteristics in a general population.

Methods

In a population-based prospective cohort study among 8340 women, we obtained information on 33 maternal characteristics at study enrolment in early-pregnancy. These characteristics covered the preconception period and first half of pregnancy (< 21 weeks gestation). Preterm birth was < 37 weeks gestation. Small-for-gestational-age (SGA) and large-for-gestational-age (LGA) at birth were gestational-age-adjusted birthweight in the lowest or highest decile, respectively. Because of their co-occurrence, preterm birth and SGA were combined into a composite outcome.

Results

The basic preconception model included easy obtainable maternal characteristics in the preconception period including age, ethnicity, parity, body mass index and smoking. This basic preconception model had an area under the receiver operating characteristics curve (AUC) of 0.63 (95% confidence interval (CI) 0.61 to 0.65) and 0.64 (95% CI 0.62 to 0.66) for preterm birth/SGA and LGA, respectively. Further extension to more complex models by adding maternal socio-demographic, lifestyle, medical history and early-pregnancy clinical characteristics led to small, statistically significant improved models. The full model for prediction of preterm birth/SGA had an AUC 0.66 (95% CI 0.64 to 0.67) with a sensitivity of 22% at a 90% specificity. The full model for prediction of LGA had an AUC of 0.67 (95% CI 0.65 to 0.69) with sensitivity of 28% at a 90% specificity. The developed models had a reasonable level of calibration within highly different socio-economic subsets of our population and predictive performance for various secondary maternal, delivery and neonatal complications was better than for primary outcomes.

Conclusions

Prediction of birth complications is limited when using maternal preconception and early-pregnancy characteristics, which can easily be obtained in clinical practice. Further improvement of the developed models and subsequent external validation is needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04497-2.

World Health Organization fetal growth charts applied in a French birth cohort

OBJECTIVE

To evaluate the applicability of World Health Organization (WHO) fetal growth charts for abdominal circumference (AC), femur length (FL) and estimated fetal weight (EFW) at the second and third trimester ultrasounds in a French birth cohort.

MATERIALS AND METHODS

Using the ELFE cohort of live births after 33 weeks' gestation in France in 2011, we selected 7747 singletons with fetal biometric measurements at the second (20-25 weeks) and third (30-35 weeks) trimester routine ultrasounds. We calculated proportions of fetuses <3rd and <10th percentiles and >90th and >97th percentiles for AC, FL and EFW using WHO charts and two international (Intergrowth and Hadlock) and two national (Salomon and CFEF) charts. Analyses were also carried out in a subsample of 4427 low-risk births.

RESULTS

WHO charts classified 2,3% and 8-10% of fetuses <3rd and <10th percentiles respectively, for AC and FL in the second and third trimesters and EFW in the third trimester. Similarly, about 3 and 10% of fetuses had AC, FL and EFW >97th and >90th percentile in both trimesters. Hadlock and CFEF charts also provided a good fit for third-trimester EFW <10th percentile. For most measures, Intergrowth yielded low proportions <3rd and <10th percentile, and high proportions >90th and >97th percentiles. Proportions were slightly lower for low-risk pregnancies.

CONCLUSION

WHO charts provided a good description of the distribution of French fetal biometric measures. Further research is needed to assess the impact of using WHO charts on obstetrical management and perinatal outcomes.

First-trimester screening model for small-for-gestational-age using maternal clinical characteristics, serum screening markers, and placental volume: prospective cohort study

OBJECTIVE

To examine predictive value of first trimester placental volume, maternal clinical characteristics, and serum biomarkers in predicting small-for-gestational-age (SGA) singleton pregnancy.

METHODS

We conducted a prospective study to determine whether SGA is associated with maternal clinical factors. Between November 2016 to May 2018, 351 women were enrolled. We included pregnant women who underwent an integrated test for aneuploidy screening. Placental volume, maternal clinical characteristics, and maternal serum pregnancy-associated plasma protein A (PAPP-A) levels in the first trimester (at 10⁺⁰-13⁺⁶weeks) and maternal serum biomarkers after 15⁺⁰-22⁺⁶weeks were measured. We measured the width, height, and thickness of the placenta and calculated the placental volume using an established mathematical formula; then, we analyzed the association between SGA at delivery, estimated placental volume (EPV), maternal clinical characteristics, and maternal serum biomarkers by multiple logistic regression analysis.

RESULTS

In this study, 12.3% (43/351) neonates were delivered before 37 weeks of gestation, and the birth weight of 23.6% (83/351) was below the 10th percentile according to gestational age. On multivariate logistic regression, the MSAFP multiples of the median (MoM) showed the strongest association with SGA in singleton pregnancy (p < .01), and the PAPP-A MoM showed a weaker association in the multiple logistic regression than in the univariate regression (p = .0073 and .0068, respectively). Our prediction model using maternal age, maternal smoking, PAPP-A, and EPV achieved an area under the curve of 0.668 in singleton pregnancy.

CONCLUSION

During the first trimester, maternal clinical characteristics, serum biomarkers, and EPV may be used for predicting the risk of SGA in singleton pregnancy.

Maternal metabolic profiling to assess fetal gestational age and predict preterm delivery: a two-centre retrospective cohort study in the US

OBJECTIVES

The aim of this study was to develop a single blood test that could determine gestational age and estimate the risk of preterm birth by measuring serum metabolites. We hypothesised that serial metabolic modelling of serum analytes throughout pregnancy could be used to describe fetal gestational age and project preterm birth with a high degree of precision.

STUDY DESIGN

A retrospective cohort study.

SETTING

Two medical centres from the USA.

PARTICIPANTS

Thirty-six patients (20 full-term, 16 preterm) enrolled at Stanford University were used to develop gestational age and preterm birth risk algorithms, 22 patients (9 full-term, 13 preterm) enrolled at the University of Alabama were used to validate the algorithms.

OUTCOME MEASURES

Maternal blood was collected serially throughout pregnancy. Metabolic datasets were generated using mass spectrometry.

RESULTS

A model to determine gestational age was developed (R²=0.98) and validated (R²=0.81). 66.7% of the estimates fell within ±1 week of ultrasound results during model validation. Significant disruptions from full-term pregnancy metabolic patterns were observed in preterm pregnancies (R²=-0.68). A separate algorithm to predict preterm birth was developed using a set of 10 metabolic pathways that resulted in an area under the curve of 0.96 and 0.92, a sensitivity of 0.88 and 0.86, and a specificity of 0.96 and 0.92 during development and validation testing, respectively.

CONCLUSIONS

In this study, metabolic profiling was used to develop and test a model for determining gestational age during full-term pregnancy progression, and to determine risk of preterm birth. With additional patient validation studies, these algorithms may be used to identify at-risk pregnancies prompting alterations in clinical care, and to gain biological insights into the pathophysiology of preterm birth. Metabolic pathway-based pregnancy modelling is a novel modality for investigation and clinical application development.