Prediction of large-for-gestational-age neonates: screening by maternal factors and biomarkers in the three trimesters of pregnancy

Establishment of a risk prediction model for large-for-gestational-age infants among Chinese women with gestational diabetes mellitus

Infants classified as large for gestational age (LGA) are often born to mothers with gestational diabetes mellitus (GDM). This study aimed to develop a prediction model to estimate the risk of LGA infants with GDM mothers. This retrospective study included 791 singletons of mothers with GDM delivered at our hospital between June 2018 and May 2020. Data was collected from the hospital's electronic information system. According to whether LGA occurred, participants were divided into two groups to analyze the related factors affecting LGA. Pregnant women were randomly divided into two groups in a 7:3 ratios to generate and validate the model. To optimize the selection of variables, the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was employed. A predictive model was subsequently constructed using multivariable logistic regression, incorporating predictors identified through LASSO regression. A nomogram was devised based on the selected variables for visual representation. The predictive model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) to assess discrimination, and calibration plots to assess calibration accuracy. Furthermore, decision curve analysis (DCA) was utilized to evaluate the clinical applicability of the models. Logistic regression analysis identified prepregnancy BMI, gestational weight gain (GWG), the 0-hour oral glucose tolerance test (OGTT0h), and parity as independent risk factors for LGA infants. The model demonstrated an area under the curve (AUC) of 0.777 in the training set and 0.744 in the validation set. The DCA illustrated that the nomogram exhibited superior net benefit within the validation cohort when the threshold probabilities were situated between 5% and 55%. Prepregnancy BMI, GWG, OGTT0h, and parity into the risk nomogram increased its usefulness for predicting LGA risk in patients with GDM.

Maternal Metabolic Health and Mother and Baby Health Outcomes (MAMBO): Protocol of a Prospective Observational Study

BACKGROUND

Metabolic disease is increasingly impacting women of reproductive age. In pregnancy, uncontrolled metabolic disease can result in offspring with major congenital anomalies, preterm birth, and abnormal fetal growth. Pregnancy also accelerates the complications of metabolic diseases in mothers resulting in an increased risk of premature cardiovascular events. Despite the convincing evidence that preconception care can largely mitigate the risks of metabolic disease in pregnancy, there are few data about how to identify the highest-risk women so that they can be connected with appropriate preconception care services.

OBJECTIVE

The aim of the study is to determine the maternal phenotype that represents the highest risk of having adverse neonatal and maternal pregnancy outcomes.

METHODS

This will be a prospective cohort study of 500 women recruited in early pregnancy. The primary outcome is a composite of offspring born small for gestational age (SGA) or large for gestational age (LGA) (customized birthweight ≤10th and ≥90th centile for gestational age). Secondary outcomes are (1) composite of adverse neonatal birth outcomes (SGA, LGA, major congenital abnormalities, preterm birth [<37 weeks' gestation]) and (2) composite of new maternal metabolic outcomes (gestational diabetes, diabetes in pregnancy, type 2 diabetes [T2D] or prediabetes; gestational hypertension, preeclampsia, eclampsia or new essential hypertension after pregnancy; and gestational weight gain ≥20kg or new overweight/obesity at the 12-18 months postpartum visit). A multivariable logistic regression analysis will be conducted to identify candidate predictors of poor pregnancy outcomes due to metabolic disease. From this model, model coefficients and the associated 95% CIs will be extracted to derive the risk score for predicting the delivery of LGA/SGA offspring (primary outcome) and composites of adverse neonatal outcomes and maternal outcomes (secondary outcomes).

RESULTS

Seed funding for the project was acquired in November 2022 and subsequent funding was acquired in May 2024. The first participant was recruited on March 23, 2023. At the time of manuscript submission, 402 participants have been recruited. Data analysis has not yet been performed. Results are expected to be published in the first half of 2027.

CONCLUSIONS

This is a prospective observational cohort study that intends to identify the metabolic disease risk factors, or combination of factors, that are most likely to cause adverse maternal and fetal health outcomes. These characteristics will be used to develop a risk calculator which will assist in identifying the highest risk women and in triaging them to appropriate services. The study has been approved by the institutional Human Research Ethics Committee (HREC/90080/MH-2022).

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12623000037606; https://tinyurl.com/yeytsxtp.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/72542.

Early Pregnancy Waist Circumference for Prediction of Fetal Macrosomia

Fetal macrosomia is associated with adverse short- and long-term outcomes for the mother and the child. Present models to predict fetal macrosomia cannot be used in all settings, and their precision could be improved. We assessed if waist circumference could replace or outperform weight for early pregnancy prediction of macrosomia. We included 5827 women in this population-based cohort study and assessed the influence of early pregnancy waist circumference and weight on the prediction of macrosomia with logistic regression analysis. We generated receiver operating characteristic (ROC) curves and calculated the area under the curve (AUC) to compare models, including waist circumference, weight, or neither of them. The odds of macrosomia increased with a larger waist circumference (adjusted odds ratio (AOR) 1.03 (95% Confidence Interval (CI) 1.02, 1.04)). For women with waist circumference between 80 and 88 cm the AOR was 1.41 (95% CI 1.09, 1.82) and women with waist circumference ≥ 88 cm had AOR 1.98 (95% CI 1.56, 2.53) for macrosomia. There was no difference in predictive capacity between waist circumference and weight in the macrosomia prediction model. The AUC was 0.75 (95% CI 0.72, 0.77) for waist circumference and 0.74 (95% CI 0.72, 0.77) for weight. The model that excluded waist circumference and weight had an AUC of 0.72 (95% CI 0.70, 0.75). The predictive capacity of the model including waist circumference was, however, higher than that of the model without waist circumference or weight (p < 0.001). In conclusion, waist circumference can replace weight in an early pregnancy macrosomia prediction model.

Impact of screening for large-for-gestational-age fetuses on maternal and neonatal outcomes: a prospective observational study

OBJECTIVES

Debates on the management of macrosomia are still current. We have to consider the consequences of screening to contribute to these discussions. Our aim is to study the consequences of the 3rd trimester fetal macrosomia screening protocols used in several centres in the same French region in order to determine whether this screening affects maternal and neonatal outcomes: mode of delivery, maternal complications (haemorrhage, perineal lesions), neonatal health (pH, Apgar score) and the occurrence of neonatal trauma during delivery.

METHODS

Prospective observational, multicenter cohort study (Reims, Châlons en Champagne and Charleville-Mézières hospitals). All women with low-risk pregnancies who could benefit from screening for fetal macrosomia were included. Neonatal macrosomia was defined as a weight above the 90th percentile according to AUDIPOG adjusted growth curves. The principal outcome was the cesarean section rate. Secondary outcomes were instrumental deliveries and maternal and neonatal morbidity and mortality.

RESULTS

2,217 women were included. Rates of cesarean section and instrumental delivery were higher if macrosomia had been screened, whether rightly, in large-for-gestational-age newborns (respectively 9,802 [1.638-190.290], p=0.038 and 3,021 [1.099-8.846], p=0.036) or wrongly, in newborns who were ultimately appropriate-for-date (respectively ORa 3.562 [1.377-10.128], p=0.01 and 3.042 [1.139-8.596], p=0.36). This screening did not reduce maternal and neonatal morbidity and mortality.

CONCLUSIONS

Screening for fetal macrosomia may be associated with increased rates of cesarean section and instrumental delivery for large-for-gestational-age and appropriate-for-date newborns. These results do not show any impact of these variations on maternal or neonatal health, and do not allow us to change practices directly. They do, however, alert us to the consequences of widespread screening for LGA and its possible side effects, which could be better targeted to high-risk populations or improved according to other criteria.

Maternal Birth Weight From Maternal and Child Health Handbooks Predicts LGA Neonates Better Than Maternal Parameters in Pregnancy

Objective: This study is aimed at evaluating maternal birth weight, recorded in Japan's Maternal and Child Health Handbooks, as a predictor for large for gestational age (LGA) neonates compared to traditional pregnancy factors. Methods: In this retrospective study, we analyzed maternal and neonatal data from 374 singleton, full-term pregnancies at Keiju General Hospital (2017-2020). Maternal birth weight was obtained from Japan's Maternal Child Health Handbooks, and fasting plasma glucose was measured during the 75-g oral glucose tolerance test (OGTT). Logistic regression models assessed the predictive contributions of maternal birth weight and fasting plasma glucose, adjusted for maternal and pregnancy factors. Results: Among 374 patients, 9.8% of neonates were classified as LGA. This group had a higher proportion of a family history of diabetes (p = 0.04) and greater maternal height (p = 0.01), pre-pregnancy weight (p = 0.004), weight before delivery (p = 0.03), and maternal birth weight (p = 0.001) than the non-LGA group. Multivariate analysis showed that maternal birth weight remained a significant predictor of neonatal birth weight after adjusting for other risk factors (odds ratios: 2.92 for maternal birth weight between 3500 and 3999 g and 4.77 for birth weight ≥ 4000 g). Conclusion: This study suggests the potential of incorporating maternal birth weight to improve LGA risk prediction. These findings provide foundational data for further research into the integration of maternal birth weight in risk assessment models and its potential clinical applications.

Prediction of large-for-gestational-age at birth using fetal biometry in type 1 and type 2 diabetes: A retrospective cohort study

OBJECTIVE

To compare ultrasound-assessed fetal head circumference (HC), abdominal circumference (AC), HC/AC ratio, and estimated fetal weight (EFW) in prediction of large-for-gestational-age (LGA) at birth in pregnancies affected by type 1 (T1DM) and type 2 (T2DM) diabetes.

METHODS

This retrospective cohort study included all women with T1DM and T2DM giving birth to singletons between 2010 and 2019 at Aalborg University Hospital, Denmark. Ultrasound scans were performed at 16, 20, 28 and 34 weeks of pregnancy. LGA was defined as birth weight deviation of 15% or greater from the expected for gestational age (≥90th centile). Prediction of LGA was assessed by logistic regression adjusted for maternal characteristics and glycated hemoglobin (HbA1c) and area under the receiver operating characteristics curve (AUC).

RESULTS

Among 180 T1DM pregnancies, 118 (66%) had an LGA neonate at birth. At 28 weeks of pregnancy, they were predicted with AUCHC/AC = 0.67, AUCAC = 0.85, and AUCEFW = 0.86. The multivariate analysis did not improve the predictive performance of the HC/AC ratio or AC. Among 87 T2DM pregnancies, 36 (41%) had an LGA neonate at birth. At 28 weeks, they were predicted with AUCHC/AC = 0.73, AUCAC = 0.83, and AUCEFW = 0.87. In T2DM, the multivariate analysis significantly improved the predictive performance for both HC/AC ratio and AC from 20 weeks of pregnancy.

CONCLUSION

In T1DM and T2DM pregnancies, LGA is characterized by a general fetal overgrowth including both AC and HC. Therefore, AC and EFW perform better than the HC/AC ratio in the prediction of LGA. In T2DM, as opposed to T1DM, the predictive performance was improved by the inclusion of maternal characteristics and HbA1c in the analysis.

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.

First-trimester screening identifies maternal cardiac maladaptation in midgestation

OBJECTIVE

We have previously established that a logistic regression model, based on maternal demographic characteristics and blood pressure measured at 11-13 weeks' gestation, can identify about 70% of women who develop future chronic hypertension (CH) in the 3 years following pregnancy, at a screen-positive rate of 10%. Furthermore, in midgestation, women who subsequently develop hypertensive disorders of pregnancy (HDP) have increased peripheral vascular resistance and mild cardiac functional and morphological alterations and these cardiovascular abnormalities persist for at least 2 years after delivery. In this study, we set out to examine whether use of the first-trimester risk model for subsequent development of CH can help to identify women at high risk for cardiovascular maladaptation in midgestation.

METHODS

This was a prospective observational study of 3812 women with singleton pregnancy attending for a routine hospital visit at 11 + 0 to 13 + 6 weeks' gestation and again at 19 + 1 to 23 + 3 weeks at King's College Hospital, London, UK, between December 2019 and August 2020. The first-trimester visit included recording of maternal demographic characteristics and medical history and measurement of systolic and diastolic blood pressure. In midgestation, detailed maternal cardiovascular assessment was carried out. The association between risk for development of CH, determined from first-trimester assessment, and cardiovascular indices in midgestation was examined.

RESULTS

Women who were at high risk for development of future CH, compared to those at low risk, had a higher incidence of HDP. In addition, high-risk women had reduced systolic and diastolic function in midgestation. Among women with HDP, those who were at high risk for future CH, compared to those at low risk, had worse cardiac function in midgestation.

CONCLUSIONS

Use of a model for first-trimester prediction of subsequent development of CH can identify women who show evidence of cardiac maladaptation in midgestation. Further studies are needed to clarify whether women who screen as high risk for future CH, compared to those at low risk, have reduced cardiac function beyond pregnancy. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Bigger babies: what happens in real practice in a non-academic UK center? Detection accuracy and outcomes with induction

BACKGROUND

There is emerging evidence of improved outcomes with induction of labour for pregnancies in which the baby is thought to be large. This trial identifies scan accuracy and the effect of intervention for pregnancies complicated by suspected large for gestational age (LGA) on customized chart outside an academic center.

METHODS

This is a retrospective cohort study of 3 groups of induced pregnancies; women with a suspected LGA fetus, women with diabetes (DM) and a control group (C) of women that underwent induction of labour on or after 280 days gestation. Data collection and analysis were prespecified. Scan accuracy and outcomes between the cohorts were compared.

RESULTS

Over 1 year there were 845 cases: LGA (128), DM (116) and control cases (601). Mean birthweights differed significantly. PPV of EFW for birthweight >90th centile on GROW chart, WHO chart, and >4 kg was 0.35-0.40. Projected birthweight of >4 kg significantly better predicted itself (AUROC 0.70, 0.74 and 0.80). Mean scan error was -5.2% and +15.6% for DM and LGA. Shoulder dystocia and neonatal morbidity were not increased in LGA despite the significant increase in AVD 28/128, 21.9% vs. 99/601, 16.5%, aOR 2.20 (1.07-4.5). SVD was significantly less likely LGA vs. C at 69/128, 53.9% vs. 413/601, 68.7% aOR 0.38 (95% CI: 0.21-0.70).

CONCLUSIONS

Third trimester EFW for bigger babies was poorly predictive of macrosomia. Fetal outcomes were good but women selected and induced as LGA had higher rates of hemorrhage and intervention.

Reducing macrosomia-related birth complications in primigravid women: ultrasound- and magnetic resonance imaging-based models

BACKGROUND

Many complications increase with macrosomia, which is defined as birthweight of ≥4000 g. The ability to estimate when the fetus would exceed 4000 g could help to guide decisions surrounding the optimal timing of delivery. To the best of our knowledge, there is no available tool to perform this estimation independent of the currently available growth charts.

OBJECTIVE

This study aimed to develop ultrasound- and magnetic resonance imaging-based models to estimate at which gestational age the birthweight would exceed 4000 g, evaluate their predictive performance, and assess the effect of each model in reducing adverse outcomes in a prospectively collected cohort.

STUDY DESIGN

This study was a subgroup analysis of women who were recruited for the estimation of fetal weight by ultrasound and magnetic resonance imaging at 36 0/7 to 36 6/7 weeks of gestation. Primigravid women who were eligible for normal vaginal delivery were selected. Multiparous patients, patients with preeclampsia spectrum, patients with elective cesarean delivery, and patients with contraindications for normal vaginal delivery were excluded. Of note, 2 linear models were built for the magnetic resonance imaging- and ultrasound-based models to predict a birthweight of ≥4000 g. Moreover, 2 formulas were created to predict the gestational age at which birthweight will reach 4000 g (predicted gestational age); one was based on the magnetic resonance imaging model, and the second one was based on the ultrasound model. This study compared the adverse birth outcomes, such as intrapartum cesarean delivery, operative vaginal delivery, anal sphincter injury, postpartum hemorrhage, shoulder dystocia, brachial plexus injury, Apgar score of <7 at 5 minutes of life, neonatal intensive care unit admission, and intracranial hemorrhage in the group of patients who delivered after the predicted gestational age according to the magnetic resonance imaging-based or the ultrasound-based models with those who delivered before the predicted gestational age by each model, respectively.

RESULTS

Of 2378 patients, 732 (30.8%) were eligible for inclusion in the current study. The median gestational age at birth was 39.86 weeks of gestation (interquartile range, 39.00-40.57), the median birthweight was 3340 g (interquartile range, 3080-3650), and 63 patients (8.6%) had a birthweight of ≥4000 g. Prepregnancy body mass index, geographic origin, gestational age at birth, and fetal body volume were retained for the optimal magnetic resonance imaging-based model, whereas maternal age, gestational diabetes mellitus, diabetes mellitus type 1 or 2, geographic origin, fetal gender, gestational age at birth, and estimated fetal weight were retained for the optimal ultrasound-based model. The performance of the first model was significantly better than the second model (area under the curve: 0.98 vs 0.89, respectively; P<.001). The group of patients who delivered after the predicted gestational age by the first model (n=40) had a higher risk of cesarean delivery, postpartum hemorrhage, and shoulder dystocia (adjusted odds ratio: 3.15, 4.50, and 9.67, respectively) than the group who delivered before this limit. Similarly, the group who delivered after the predicted gestational age by the second model (n=25) had a higher risk of cesarean delivery and postpartum hemorrhage (adjusted odds ratio: 5.27 and 6.74, respectively) than the group who delivered before this limit.

CONCLUSION

The clinical use of magnetic resonance imaging- and ultrasound-based models, which predict a gestational age at which birthweight will exceed 4000 g, may reduce macrosomia-related adverse outcomes in a primigravid population. The magnetic resonance imaging-based model is better for the identification of the highest-risk patients.

Prediction of large-for-gestational age at 36 weeks' gestation: two-dimensional ultrasound vs three-dimensional ultrasound vs magnetic resonance imaging

OBJECTIVE

To compare the performance of two-dimensional ultrasound (2D-US), three-dimensional ultrasound (3D-US) and magnetic resonance imaging (MRI) at 36 weeks' gestation in predicting the delivery of a large-for-gestational-age (LGA) neonate, defined as birth weight ≥ 95th percentile, in patients at high and low risk for macrosomia.

METHODS

This was a secondary analysis of a prospective observational study conducted between January 2017 and February 2019. Women with a singleton pregnancy at 36 weeks' gestation underwent 2D-US, 3D-US and MRI within 15 min for estimation of fetal weight. Weight estimations and birth weight were plotted on a growth curve to obtain percentiles for comparison. Participants were considered high risk if they had at least one of the following risk factors: diabetes mellitus, estimated fetal weight ≥ 90th percentile at the routine third-trimester ultrasound examination, obesity (prepregnancy body mass index ≥ 30 kg/m2) or excessive weight gain during pregnancy. The outcome was the diagnostic performance of each modality in the prediction of birth weight ≥ 95th percentile, expressed as the area under the receiver-operating-characteristics curve (AUC), sensitivity, specificity and positive and negative predictive values.

RESULTS

A total of 965 women were included, of whom 533 (55.23%) were high risk and 432 (44.77%) were low risk. In the low-risk group, the AUCs for birth weight ≥ 95th percentile were 0.982 for MRI, 0.964 for 2D-US and 0.962 for 3D-US; pairwise comparisons were non-significant. In the high-risk group, the AUCs were 0.959 for MRI, 0.909 for 2D-US and 0.894 for 3D-US. A statistically significant difference was noted between MRI and both 2D-US (P = 0.002) and 3D-US (P = 0.002), but not between 2D-US and 3D-US (P = 0.503). In the high-risk group, MRI had the highest sensitivity (65.79%) compared with 2D-US (36.84%, P = 0.002) and 3D-US (21.05%, P < 0.001), whereas 3D-US had the highest specificity (98.99%) compared with 2D-US (96.77%, P = 0.005) and MRI (96.97%, P = 0.004).

CONCLUSIONS

At 36 weeks' gestation, MRI has better performance compared with 2D-US and 3D-US in predicting birth weight ≥ 95th percentile in patients at high risk for macrosomia, whereas the performance of 2D-US and 3D-US is comparable. For low-risk patients, the three modalities perform similarly. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Combined maternal central adiposity measures in relation to infant birth size

Improvement of prenatal identification of large-for-gestational-age (LGA) infants could lower the risk for adverse outcomes. Therefore, we sought to evaluate the association of a combination of maternal waist circumference (WC) and abdominal fat depths with infant birth size. A cohort study including 1240 women was performed between 2015 and 2018 at Uppsala University Hospital, Sweden. Maternal WC was measured at the first antenatal visit, and visceral (VF) and subcutaneous (SCF) fat depths by ultrasound at the second-trimester anomaly scan. Waist circumference, VF, and SCF were categorized as low or high (cut-offs WC ≥ 88 cm, VF ≥ 54 mm, SCF ≥ 21 mm). Outcomes were birth weight standard deviation score (BWSDS) and LGA (BWSDS > 90th and > 97th percentile). Secondary outcome was small-for-gestational-age (SGA, BWSDS < 10th and < 3rd percentile). Univariate analysis of variance and logistic regression analyses were performed adjusted for maternal weight, height, parity, smoking, country of birth, pregestational diabetes, and chronic hypertension. For both high and low WC, high VF was positively associated with BWSDS and LGA. There was no association with SGA. The results did not demonstrate any value of the combination of WC and fat depth measures in predicting infant birth size but suggested VF as a marker for large infants.

Factors Affecting Clinical over and Underestimation of Fetal Weight-A Retrospective Cohort

Clinical estimation of fetal weight is an integral component of obstetric care that might dictate the timing and mode of delivery. Inaccurate fetal weight estimation might result in unnecessary interventions or in underestimating potential risks, resulting in inappropriate intrapartum care. This retrospective study assessed factors associated with under- or overestimation of birthweight and evaluated the obstetric implications. It included singleton births ≥24 w with clinically estimated fetal weight (EFW) up to 1 week before delivery, during 2014−2020. Estimates >±10% of the actual birthweight were considered inaccurate and categorized as overestimation (>10% heavier than the actual birthweight) or underestimation (>10% smaller than the birthweight). Multivariable logistic regression was performed to reveal factors associated with inaccurate EFW. Maternal characteristics and obstetric outcomes were compared. The primary outcomes for the overestimation group were the neonatal composite adverse outcome, induction of labor and cesarean delivery rates. The primary outcomes for the underestimation group were rates of shoulder dystocia, 3rd- or 4th-degree perineal lacerations, and failed vacuum extraction. Among 38,615 EFW, 5172 (13.4%) were underestimated, 6695 (17.3%) were overestimated and 27,648 (69.3%) accurate. Multivariable logistic regression found increasing gestational age as an independent risk-factor for underestimation (odds ratio (OR) 1.15 for every additional week, 95% confidence interval (CI) 1.12−1.2). Major factors independently associated with overestimation were nulliparity (OR 1.95, CI 1.76−2.16), maternal obesity (OR 1.52, CI 1.33−1.74), smoking (OR 1.6, CI 1.33−1.93), and oligohydramnios (OR 1.92, CI 1.47−2.5). Underestimation was an independent risk-factor for shoulder dystocia (OR 1.61, CI 1.05−2.46) and 3rd- or 4th-degree perineal lacerations (OR 1.59, CI 1.05−2.43). Overestimation was an independent risk-factor for neonatal composite adverse outcome (OR 1.15, CI 1.02−1.3), induced labor (OR 1.30, CI 1.21−1.40) and cesarean delivery (OR 1.59, CI 1.41−1.79). Clinicians should be aware of factors and adverse obstetric implications associated with over- or underestimation of birthweight.

A Predictive Model for Large-for-Gestational-Age Infants among Korean Women with Gestational Diabetes Mellitus Using Maternal Characteristics and Fetal Biometric Parameters

Background: With increasing incidence of gestational diabetes mellitus (GDM), newborn infants with perinatal morbidity, including large-for-gestational-age (LGA) or macrosomia, are also increasing. The purpose of this study was to develop a prediction model for LGA infants with GDM mothers. Methods: This was a retrospective case-control study of 660 women with GDM and singleton pregnancies in four tertiary care hospitals from 2006 to 2013 in Korea. Biometric parameters were obtained at diagnoses of GDM and within two weeks before delivery. These biometric data were all transformed retrospectively into Z-scores calculated using a reference. Interval changes of values between the two periods were obtained. Multivariable logistic and stepwise backwards regression analyses were performed to develop the most parsimonious predictive model. The prediction model included pre-pregnancy body mass index (BMI), head circumference (HC), Z-score at 24 + 0 to 30 + 6 weeks’ gestation, and abdominal circumference (AC) Z-score at 34 + 0 to 41 + 6 weeks within 2 weeks before delivery. The developed model was then internally validated. Results: Our model’s predictive performance (area under the curve (AUC): 0.925) was higher than estimated fetal weight (EFW) within two weeks before delivery (AUC: 0.744) and the interval change of EFW Z-score between the two periods (AUC: 0.874). It was internally validated (AUC: 0.916). Conclusions: A clinical model was developed and internally validated to predict fetal overgrowth in Korean women with GDM, which showed a relatively good performance.

Fetal magnetic resonance imaging at 36 weeks predicts neonatal macrosomia: the PREMACRO study

BACKGROUND

Large-for-gestational-age fetuses are at increased risk of perinatal morbidity and mortality. Magnetic resonance imaging seems to be more accurate than ultrasound in the prediction of macrosomia; however, there is no well-powered study comparing magnetic resonance imaging with ultrasound in routine pregnancies.

OBJECTIVE

This study aimed to prospectively compare estimates of fetal weight based on 2-dimensional ultrasound and magnetic resonance imaging with actual birthweights in routine pregnancies.

STUDY DESIGN

From May 2016 to February 2019, women received counseling at the 36-week clinic. Written informed consent was obtained for this Ethics Committee-approved study. In this prospective, single-center, blinded study, pregnant women with singleton pregnancies between 36 0/7 and 36 6/7 weeks' gestation underwent both standard evaluation of estimated fetal weight with ultrasound according to Hadlock et al and magnetic resonance imaging according to the formula developed by Baker et al, based on the measurement of the fetal body volume. Participants and clinicians were aware of the results of the ultrasound but blinded to the magnetic resonance imaging estimates. Birthweight percentile was considered as the gold standard for the ultrasound and magnetic resonance imaging-derived percentiles. The primary outcome was the area under the receiver operating characteristic curve for the prediction of large-for-gestation-age neonates with birthweights of ≥95th percentile. Secondary outcomes included the comparative prediction of large-for-gestation-age neonates with birthweights of ≥90th, 97th, and 99th percentiles and small-for-gestational-age neonates with birthweights of ≤10th, 5th, and 3rd percentiles for gestational age and maternal and perinatal complications.

RESULTS

Of 2914 women who were initially approached, results from 2378 were available for analysis. Total fetal body volume measurements were possible for all fetuses, and the time required to perform the planimetric measurements by magnetic resonance imaging was 3.0 minutes (range, 1.3-5.6). The area under the receiver operating characteristic curve for the prediction of a birthweight of ≥95th percentile was 0.985 using prenatal magnetic resonance imaging and 0.900 using ultrasound (difference=0.085, P<.001; standard error, 0.020). For a fixed false-positive rate of 5%, magnetic resonance imaging for the estimation of fetal weight detected 80.0% (71.1-87.2) of birthweight of ≥95th percentile, whereas ultrasound for the estimation of fetal weight detected 59.1% (49.0-68.5) of birthweight of ≥95th percentile. The positive predictive value was 42.6% (37.8-47.7) for the estimation of fetal weight using magnetic resonance imaging and 35.4% (30.1-41.1) for the estimation of fetal weight using ultrasound, and the negative predictive value was 99.0% (98.6-99.3) for the estimation of fetal weight using magnetic resonance imaging and 98.0% (97.6-98.4) for the estimation of fetal weight using ultrasound. For a fixed false-positive rate of 10%, magnetic resonance imaging for the estimation of fetal weight detected 92.4% (85.5-96.7) of birthweight of ≥95th percentile, whereas ultrasound for the estimation of fetal weight detected 76.2% (66.9-84.0) of birthweight of ≥95th percentile. The positive predictive value was 29.9% (27.2-32.8) for the estimation of fetal weight using magnetic resonance imaging and 26.2% (23.2-29.4) for the estimation of fetal weight using ultrasound, and the negative predictive value was 99.6 (99.2-99.8) for the estimation of fetal weight using magnetic resonance imaging and 98.8 (98.4-99.2) for the estimation of fetal weight using ultrasound. The area under the receiver operating characteristic curves for the prediction of large-for-gestational-age neonates with birthweights of ≥90th, 97th, and 99th percentiles and small-for-gestational-age neonates with birthweights of ≤10th, 5th, and 3rd percentiles was significantly larger in prenatal magnetic resonance imaging than in ultrasound (P<.05 for all).

CONCLUSION

At 36 weeks' gestation, magnetic resonance imaging for the estimation of fetal weight performed significantly better than ultrasound for the estimation of fetal weight in the prediction of large-for-gestational-age neonates with birthweights of ≥95th percentile for gestational age and all other recognized cutoffs for large-for-gestational-age and small-for-gestational-age neonates (P<.05 for all).

Accuracy of Fetal Weight Estimation by Ultrasonographic Evaluation in a Northeastern Region of India

Methods

The cross-sectional study included 100 pregnant women aged 20–45 years from the Kamrup district admitted to Guwahati Medical College and Hospital, Guwahati, Assam. The data were analyzed using Microsoft Excel and SPSS version 16. The EFW at term was calculated using Shepard's formula and Hadlock's formula. Differences in means are compared using the one-way ANOVA or Kruskal–Wallis test and paired t-test. The accuracy of the two procedures was evaluated using mean absolute error (MAE) and mean absolute percentage error (MAPE). A p value<0.05 was considered significant.

Results

The present study included 100 pregnant women aged 21–38 years with term or postterm pregnancies subjected to ultrasonographic evaluation within 72 hours of delivery. The mean (±s.d.) EFW by Shepard's formula was 2716.05 (±332.38) g and Hadlock's formula was 2740.44 (±353.23) g, respectively. For Hadlock's formula, MAE ± s.d. was found to be higher (overall 84.59 ± 76.54) specifically in the weight category less than 2500 (106.42 ± 88.11) as compared to Shepard's (overall MAE ± s.d = 79.86 ± 64.78, and among ABW < 2500 g, MAE ± s.d = 65.04 ± 61.02). The overall MAPE of Hadlock's formula was 3.14% and that for Shepard's formula was 2.91%, and the difference was not statistically significant. Both Shepard's formula and Hadlock's formula had a sensitivity of 92.85% in detecting IUGR, but Hadlock's method had higher specificity (66%), higher PPV (86.67%), and higher NPV (80%).

Conclusion

The ultrasonographic evaluation of fetal weight helps predict fetal birth weight precisely and can influence obstetric management decisions concerning timing and route of delivery, thus reducing perinatal morbidity and mortality.

Telomere length in healthy newborns is not affected by adverse intrauterine environments

Different intrauterine exposures are associated with different metabolic profiles leading to growth and development characteristics in children and also relate to health and disease patterns in adult life. The objective of this work was to evaluate the impact of four different intrauterine environments on the telomere length of newborns. This is a longitudinal observational study using a convenience sample of 222 mothers and their term newborns (>37 weeks of gestational age) from hospitals in Porto Alegre, Rio Grande do Sul (Brazil), from September 2011 to January 2016. Sample was divided into four groups: pregnant women with Gestational Diabetes Mellitus (DM) (n=38), smoking pregnant women (TOBACCO) (n=52), mothers with small-for-gestational age (SGA) children due to idiopathic intrauterine growth restriction (n=33), and a control group (n=99). Maternal and newborn genomic DNA were obtained from epithelial mucosal cells. Telomere length was assessed by qPCR, with the calculation of the telomere and single copy gene (T/S ratio). In this sample, there was no significant difference in telomere length between groups (p>0.05). There was also no association between childbirth weight and telomere length in children (p>0.05). For term newborns different intrauterine environments seems not to influence telomere length at birth.

Obstetric consequences of a false-positive diagnosis of large-for-gestational-age fetus

Objective

To compare delivery outcomes between true‐positive (TP) and false‐positive (FP) large‐for‐gestational‐age (LGA) fetuses, appropriate‐for‐gestational‐age (AGA) fetuses, and false‐negative (FN) LGA fetuses.

Methods

Retrospective cohort study of singleton pregnancies at risk for macrosomia without contraindication to vaginal delivery, receiving an ultrasound scan at 34–37 weeks of pregnancy.

Results

In all, 430 pregnancies were included: 155 TP LGA, 87 FP LGA, 177 AGA and 11 FN LGA newborns. Cesarean section rate during labor was significantly higher in FP LGA than in AGA (19% vs. 8.7%) but not significantly different between FP LGA and TP LGA (19% vs. 32.4%). Median birth weight z score was significantly higher in TP LGA (1.9) compared with the FP LGA and AGA (0.91 and 0.84, respectively), whereas no significant differences were found between FP LGA and AGA. Admission to a neonatal intensive care unit was significantly more frequent in TP LGA than AGA, whereas shoulder dystocia, postpartum hemorrhage, and third‐ to fourth‐degree perineal tears were similar between the different groups.

Conclusion

A false‐positive diagnosis of LGA fetus is associated with a significant increase of cesarean section during labor. Therefore, a suspicious ultrasound may result in reduction of the clinical threshold for the diagnosis of abnormal labor.

A false‐positive diagnosis of LGA fetus on ultrasound at 34–37 weeks is associated with a significant increase in cesarean section during labor.

Induction of labor for a suspected large-for-gestational-age/macrosomic fetus

Fetal macrosomia is defined as a birth weight of >4000 g, while the term large for gestational age (LGA) is defined as an estimated fetal weight >90th centile for gestational age. Current data indicate that a significant proportion of the babies are LGA. Pregnancies involving LGA babies are associated with increased maternal and perinatal morbidity including caesarean section, postpartum hemorrhage, shoulder dystocia, and birth trauma. To reduce these complications, labor induction has been suggested as a possible solution. However, despite some high-quality evidence in favor of labor induction for suspected macrosomia/LGA, existing guidelines do not support routine induction of labor in this population. The aim of this paper is to critically appraise the available evidence and clinical practice recommendations and highlight the importance of shared decision making and individualized care based on clear counselling regarding the lack of a sensitive diagnostic tool for estimating fetal weight in the third trimester.

A first trimester prediction model for large for gestational age infants: a preliminary study

Background

Large for gestational age infants (LGA) have increased risk of adverse short-term perinatal outcomes. This study aims to develop a multivariable prediction model for the risk of giving birth to a LGA baby, by using biochemical, biophysical, anamnestic, and clinical maternal characteristics available at first trimester.

Methods

Prospective study that included all singleton pregnancies attending the first trimester aneuploidy screening at the Obstetric Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019.

Results

A total of 503 consecutive women were included in the analysis. The final prediction model for LGA, included multiparity (OR = 2.8, 95% CI: 1.6–4.9, p = 0.001), pre-pregnancy BMI (OR = 1.08, 95% CI: 1.03–1.14, p = 0.002) and PAPP-A MoM (OR = 1.43, 95% CI: 1.08–1.90, p = 0.013). The area under the ROC curve was 70.5%, indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to − 1.378, which corresponds to a 20.1% probability of having a LGA infant. By using such a cut-off, the risk of LGA can be predicted in our sample with sensitivity of 55.2% and specificity of 79.0%.

Conclusion

At first trimester, a model including multiparity, pre-pregnancy BMI and PAPP-A satisfactorily predicted the risk of giving birth to a LGA infant. This promising tool, once applied early in pregnancy, would identify women deserving targeted interventions.

Trial registration

ClinicalTrials.gov NCT04838431, 09/04/2021.

The added value of umbilical vein flow in predicting fetal macrosomia at 36 weeks of gestation: A prospective cohort study

INTRODUCTION

Current models based on fetal biometry and maternal characteristics have a poor performance in predicting macrosomia. The primary aim of this study was to elucidate the diagnostic performance of fetal venous and arterial Dopplers in predicting macrosomia in the third trimester of pregnancy; the secondary aim was to build a multiparametric prediction model including pregnancy, ultrasound and Doppler characteristics able to predict macrosomia accurately.

MATERIAL AND METHODS

Prospective cohort study including 2156 singleton pregnancies scheduled for routine ultrasound assessment at 36 weeks of gestation. Fetal biometry, estimated fetal weight (EFW), pulsatility index of the uterine, umbilical, and middle cerebral arteries, cerebroplacental ratio and umbilical vein blood flow (UVBF) normalized for fetal abdominal circumference (UVBF/AC) were recorded. Primary outcome was the prediction of fetal macrosomia, defined as a birthweight >90th percentile; secondary outcome was the prediction of newborns >4000 g. Logistic regression and area under the curve (AUC) analyses were used to analyze the data.

RESULTS

Fetal macrosomia complicated 9.8% of pregnancies, and 7.7% of newborns had a birthweight >4000 g. At multivariate logistic regression analysis, maternal body mass index (adjusted odds ratio [aOR] 1.23), pregestational diabetes (aOR 1.83), a prior newborn with a birthweight >95th centile (aOR 1.49), EFW (aOR 2.23) and UVBF (aOR1.84) were independently associated with macrosomia, whereas gestational diabetes mellitus (P = .07) or any of the other Doppler parameters were not. EFW had an AUC of 0.750 and of 0.801 alone and in association with maternal characteristics for the prediction of macrosomia, respectively. The addition of UVBF to this model significantly improved the prediction of fetal macrosomia provided by maternal and ultrasound parameters with an AUC of 0.892 (De Long P = .044 and P = .0078, respectively). The predictive performance for birthweight >4000 g was similar and significantly improved when UVBF was included in the diagnostic algorithm.

CONCLUSIONS

Umbilical vein blood flow evaluation in the third trimester improves the diagnosis of fetal macrosomia. The optimal diagnostic performance for macrosomia is achieved by a multiparametric model including umbilical vein flow, maternal characteristics and EFW.

Effect of postbariatric maternal weight loss and surgery to conception interval on perinatal outcomes of nulliparous women

BACKGROUND

Bariatric surgery is associated with an increased risk of delivering a small neonate. The role of maternal weight loss and surgery to conception interval is unclear.

OBJECTIVES

To investigate the effect of maternal weight loss, as a result of bariatric surgery, and surgery to conception interval on fetal growth and birthweight (BW).

SETTING

Inner London Teaching Hospital METHODS: We studied prospectively nulliparous women with previous bariatric surgery. Information on type, time, and presurgery weight was obtained. Surgery-to-conception interval was calculated as the time between surgery and conception, defined as the fourteenth day of the pregnancy dated by first trimester ultrasound scan. In the first trimester, maternal weight was measured. Assessment of maternal weight change between presurgery and first trimester of pregnancy was defined as total weight loss (TWL) (%). Fetal ultrasound scans were performed twice; 30-32 and 35-37 weeks' gestation and estimated fetal weight (EFW) was calculated. Fetal growth rate was calculated as the ratio of EFW increase (in grams) between 30-32 and 35-37 weeks divided by the time interval (in days) between the 2 examinations. BW was recorded.

RESULTS

The study included 54 pregnant women, 26 with a restrictive procedure (gastric band or vertical sleeve gastrectomy) and 28 with a gastric bypass. Surgery to conception interval was not a significant predictor of the offspring's growth. Maternal TWL was a significant predictor of fetal growth rate (P = .04) and predictor of BW (P = .005), even after adjustment for confounders.

CONCLUSIONS

Maternal weight loss, as a result of bariatric surgery, has an inverse correlation with fetal growth rate and BW.

Fetal nondiabetic-macrosomia: risk factors for pregnancy adverse outcome and comparison of two growth curves in the prediction of cesarean section

BACKGROUND

Randomized trials reported no difference whether induction or expectant management is performed in non-diabetic women with large for gestational age babies but no tool has been validated for the prediction of high risk cases.

AIM

Assessing the performance of different growth curves in the prediction of complications.

METHODS

Data from 1066 consecutive non-diabetic women who delivered babies ≥4000 g were collected. Logistic regression analysis was used to analyze the impact of the maternal variables on: instrumental delivery, shoulder dystocia (SD), perineal tears, cesarean section (CS), and postpartum hemorrhage. Intergrowth21 curves and customized Gardosi's curves were compared in terms of prediction of adverse outcomes.

FINDINGS

Induction of labor was performed in 23.1% cases. The rate of CS was 17%. Hemorrhage, fetal distress, and SD occurred in 2%, 1.3%, and 2.7% of cases, respectively. Induction was significantly associated with instrumental delivery (p < .001), CS (p = .001), third and fourth degree perineal tears (p = .031), and post-partum hemorrhage (p = .02). The cutoff of 90th percentile according to Intergrowth21 did not show significant performance in predicting CS, while the same cutoff according to the Gardosi curves showed an OR 1.92 (CI 1.30-2.84) (p = .0009).

DISCUSSION

Gardosi curves showed a better performance in predicting the risk of CS versus Intergrowth curves. Induction is significantly associated with adverse outcome in non-diabetic women with LGA babies.

Large-for-gestational age diagnosed during second-trimester anatomy ultrasound and association with gestational diabetes and large-for-gestational age at birth

OBJECTIVES

To determine if large-for-gestational age (LGA) diagnosed during second-trimester ultrasound examination is associated with the development of gestational diabetes mellitus (GDM) and LGA at birth.

METHODS

This was a retrospective cohort study of all pregnant women who underwent a second-trimester anatomy ultrasound examination between 18 and 22 weeks at our institution from 2012 to 2017. Patients were included in the LGA group if estimated fetal weight and/or fetal abdominal circumference was ≥ 90^th percentile for gestational age. Patients with a history of pre-GDM, multiple gestation, preterm delivery, use of betamethasone or fetal anomaly were excluded. The control group consisted of appropriate-for-gestational-age (AGA) pregnancies that were scanned at 18-22 weeks during the study period. AGA was defined as EFW > 10^th percentile and ≤ 89^th percentile. Prenatal and delivery records were reviewed and demographic and outcome variables were collected. Multivariable logistic regression models were applied to assess the impact of LGA diagnosed in the second trimester on the development of GDM and LGA at birth (birth weight ≥ 90^th percentile).

RESULTS

The study population included 756 patients with a LGA fetus and 756 with an AGA fetus on second-trimester ultrasound examination. In patients with a LGA fetus diagnosed during the second-trimester ultrasound examination, the incidence of GDM was 6.0% and the incidence of LGA at birth was 14.9%. Among patients with a LGA fetus in the second trimester, those who developed GDM or LGA at birth were significantly older and were more likely to be obese. Moreover, parity was associated with neonatal LGA (P = 0.0003) but not with GDM (P = 0.82). On multivariable logistic regression analysis with adjustment for age, parity, change in gestational body mass index, obesity, ethnicity and neonatal sex, LGA diagnosed during the second trimester was associated significantly with GDM (adjusted odds ratio (aOR), 2.54; 95% CI, 1.29-5.03; P = 0.007) and LGA at birth (aOR, 6.85; 95% CI, 3.60-13.05; P < 0.0001).

CONCLUSIONS

LGA diagnosed during second-trimester ultrasound examination is associated with the development of GDM and LGA at birth, independent of known risk factors, and could be used to identify these women earlier for intervention. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Prediction of Large for Gestational Age by Ultrasound at 35 Weeks and Impact of Ultrasound-Delivery Interval: Comparison of 6 Standards

OBJECTIVE

The aim of the study was to assess the predictive ability of the ultrasound estimated percentile weight (EPW) at 35 weeks to predict large for gestational age (LGA) at term delivery according to 6 growth standards, including population, population-customized, and international references. The secondary objectives were to determine its predictive ability to detect adverse perinatal outcomes (APOs) and whether the ultrasound-delivery interval influences the detection rate of LGA newborns.

METHODS

This was a retrospective cohort study of 9,585 singleton pregnancies. Maternal clinical characteristics, fetal ultrasound data obtained at 35 weeks, and pregnancy and perinatal outcomes were used to calculate EPWs to predict LGAs at delivery according to the customized and the non-customized (NC) Miguel Servet University Hospital (MSUH), the customized Figueras, the NC Fetal Medicine Foundation (FMF), the NC INTERGROWTH-21st, and the NC World Health Organization (WHO) standards.

RESULTS

For a 10% false-positive rate, detection rates for total LGAs at delivery ranged from 31.2% with the WHO (area under the curve [AUC] 0.77; 95% confidence interval [CI], 0.76-0.79) to 56.5% with the FMF standard (AUC 0.85; 95% CI, 0.84-0.86). Detection rates and values of AUCs to predict LGAs by ultrasound-delivery interval (range 1-6 weeks) show higher detection rates as the interval decreases. APO detection rates ranged from 2.5% with the WHO to 12.6% with the Figueras standard.

CONCLUSION

The predictive ability of ultrasound estimated fetal weight at 35 weeks to detect LGA infants is significantly greater for FMF and MSUH NC standards. In contrast, the APO detection rate is significantly greater for customized standards. The shorter ultrasound-delivery interval relates to better prediction rates.

Role of first-trimester umbilical vein blood flow in predicting large-for-gestational age at birth

OBJECTIVES

To describe umbilical vein (UV) hemodynamics at 11 + 0 to 13 + 6 weeks of gestation in pregnancies delivering a large-for-gestational-age (LGA) neonate, and to build a multiparametric model, including pregnancy and ultrasound characteristics in the first trimester, that is able to predict LGA at birth.

METHODS

This was a matched case-control study, of singleton pregnancies that underwent ultrasound examination at 11 + 0 to 13 + 6 weeks for aneuploidy screening, at a single center over a 4-year period. Cases were women who delivered a neonate with birth weight (BW) > 90th centile for gestational age and sex, according to local birth-weight standards, while controls were those who delivered a neonate with BW ranging between the 10th and 90th centiles, matched for maternal and gestational age, at a ratio of 1:3. Each included case underwent Doppler assessment of the uterine arteries and UV, including measurement of its diameter, time-averaged maximum velocity (TAMXV) and UV blood flow (UVBF). UVBF and its components were expressed as Z-scores. Fisher's exact test and Mann-Whitney U-test were used to compare differences in maternal biomarkers and ultrasound characteristics between pregnancies complicated by LGA and controls. Logistic regression and receiver-operating-characteristics (ROC) curve analyses were carried out to identify independent predictors of LGA and to build a multiparametric prediction model integrating different maternal, pregnancy and ultrasound characteristics. Subgroup analysis was also performed, considering women who delivered a neonate with BW > 4000 g.

RESULTS

In total, 964 pregnancies (241 with LGA at birth and 723 without) were included in the study. In LGA pregnancies compared with controls, UV-TAMXV Z-score (0.8 (interquartile range (IQR), 0.4-1.5) vs 0.0 (IQR, -0.3 to 0.5); P ≤ 0.001) and UVBF Z-score (1.3 (IQR, 0.8-1.9) vs 0.1 (IQR, -0.4 to 0.4); P ≤ 0.001) were higher, while there was no difference in median UV diameter Z-score (P = 0.56). Median uterine artery pulsatility index multiples of the median (MoM; 0.94 (IQR, 0.78-1.12) vs 1.02 (IQR, 0.84-1.19); P = 0.04) was significantly lower in LGA pregnancies. On multivariate logistic regression analysis, maternal body mass index (BMI; adjusted odds ratio (aOR), 1.2 (95% CI, 1.1-1.7); P < 0.001), parity (aOR, 1.4 (95% CI, 1.2-1.6); P < 0.001), pregnancy-associated plasma protein-A (PAPP-A) MoM (aOR, 1.1 (95% CI, 1.0-1.6); P = 0.04) and UVBF Z-score (aOR, 1.6 (95% CI, 1.1-1.9); P < 0.001) were associated independently with LGA. A multiparametric model integrating parity, BMI and PAPP-A MoM provided an area under the ROC curve (AUC) of 0.72 (95% CI, 0.67-0.76) for the prediction of LGA. The addition of UVBF Z-score to this model significantly improved the prediction of LGA provided by maternal and biochemical factors, with an AUC of 0.79 (95% CI, 0.75-0.83; P = 0.03). Similarly, the model incorporating UVBF Z-score predicted BW > 4000 g with an AUC of 0.83 (95% CI, 0.75-0.93).

CONCLUSIONS

UVBF measured at the time of the 11-14-week scan is associated independently with, and is predictive of, LGA and BW > 4000 g. Adding measurement of UVBF to a multiparametric model that includes maternal (parity and BMI) and biochemical (PAPP-A) parameters improves the diagnostic accuracy of prenatal screening for LGA at birth. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

The value of fetal growth biometry velocities to predict large for gestational age (LGA) infants

Objective: The use of growth velocities derived from fetal biometrics have been suggested to improve prediction of large for gestational age (LGA). Our objective was to determine if ultrasonographic growth velocities (GV) for abdominal circumference (AC) and estimated fetal weight (EFW) improve the prediction of LGA infants when compared to Hadlock EFW.Methods: This was a secondary analysis of data from a prospective study of women referred for growth ultrasounds during the 3rd trimester. Growth velocities (GV) for AC (AC - GV) and EFW (EFW - GV) were derived from the difference in Z-scores between measurements at the time of anatomy survey (18-24 week) and third trimester ultrasound (26-36 weeks). Change in AC - GV and EFW - GV >90th %ile alone or in combination with Hadlock EFW >90th%ile were compared for prediction of a LGA neonate. The primary outcome was the sensitivity and specificity of the (1) Hadlock EFW >90%ile, (2) AC - GV, (3) EFW - GV, (4) Hadlock EFW + AC - GV, and (5) Hadlock EFW + EFW - GV for the prediction of neonatal LGA. Test characteristics and area under the ROC curve (AUC) were determined. The association between the ultrasound predicted growth and adverse neonatal outcome was assessed using logistic regression.Results: Of 630 women meeting inclusion criteria, 85 (13.5%) had LGA neonates. Hadlock EFW showed a better NPV (98.0%) and sensitivity (71.1%) when compared to AC - GV (NPV 87.5%, sensitivity 17.7%) and EFW - GV (NPV 88.0%, sensitivity 22.6%). Combining Hadlock EFW and AC-GV or EFW - GV did little to improve the test characteristics for the prediction of LGA (AUC 0.65 and 0.64, respectively). All five measurements were unable to predict a composite of adverse neonatal outcome or need for maternal cesarean delivery. Adjustment of the growth velocities for gestational age at anatomy scan or 3rd trimester growth scan did not change these results.Conclusion: AC and EFW growth velocities do not appear to improve the prediction of LGA infants when compared to using the third trimester Hadlock EFW.

Are there specific factors associated with prenatally undiagnosed foetal macrosomia?

OBJECTIVE

Fetal macrosomia is known to increase maternal and neonatal complications, but 20%-50% of the macrosomic fetuses are prenatally undiagnosed. Our objective was to identify specific factors associated with undiagnosed fetal macrosomia in women without diabetes.

METHODS

Retrospective case-control study in a tertiary maternity unit between January 1st and December 31st, 2016. Inclusion of all women delivering after 37 weeks of a single live-born macrosomic infant, i.e., with a birth weight ≥ 90th percentile for gestational age (GA). Women with pre-existing or gestational diabetes were excluded. To identify specific factors associated with undiagnosed foetal macrosomia, we compared risk factors for macrosomia, maternal characteristics, father's body mass index (BMI) and prenatal follow up between two groups depending on whether macrosomia was prenatally diagnosed or not.

RESULTS

Among 428 macrosomic newborns, 224 (52.3 %) were prenatally undiagnosed. Known risk factors for macrosomia, maternal characteristics (such as low socio-economic level, low education level) and father's BMI were similar between the two groups. The prenatal follow up was comparable between the two groups. Ultrasound estimated foetal weight during the 3rd trimester was lower in the undiagnosed macrosomic foetuses compared to diagnosed macrosomic foetuses (2130±279 vs 2445±333, p<0.001).

CONCLUSIONS

No specific factor of undiagnosed macrosomia was identified, and women with prenatally undiagnosed fetal macrosomia had the same risk factors than women with diagnosed macrosomia. Our study suggests that our groups have different growth curves. This hypothesis has yet to be studied.

Association between false positive glucose challenge test results and large-for-gestational-age infants: a retrospective cohort study

OBJECTIVES

There is no consensus regarding a possible relation between false positive glucose challenge test (GCT) results and large-for-gestational-age (LGA) infants. This study aimed to clarify the association between false positive GCT results and LGA, after adjusting for potential confounding factors, using a large clinical dataset.

DESIGN

Retrospective cohort study.

SETTING

National Hospital Organisation Kofu National Hospital, which is a community hospital, between January 2012 and August 2019.

PARTICIPANTS

Japanese women who underwent GCT between 24 and 28 weeks of gestation at the hospital were included. After excluding those with gestational diabetes mellitus, diabetes in pregnancy and multiple pregnancies, subjects were divided into a false positive GCT group (≥140 mg/dL) and a GCT negative group (<140 mg/dL).

METHODS

Obstetric records of patients were examined. The χ²-test and multivariable logistic regression analysis were used to investigate the association between false positive GCT results and LGA.

PRIMARY AND SECONDARY OUTCOME MEASURES

Incidence of LGA and the association between false positive GCT results and LGA.

RESULTS

The mean subject age was 31.4±5.5 years, with 43.3% nulliparity (n=974) and 2160 (96.1%) term deliveries. The incidence of LGA was 9.4% (211/2248) and 11.4% (257/2248) of the women had false positive GCT results. False positive GCT results were significantly associated with an increased risk of LGA (OR, 1.51; 95% CI, 1.02 to 2.23), after controlling for maternal age, prepregnancy maternal weight, maternal weight gain during pregnancy and parity.

CONCLUSIONS

It appears that there is a significant association between false positive GCT results and LGA. Additional research is required to confirm these results and to investigate appropriate interventions for women with abnormal screens for gestational diabetes mellitus.

Prediction of large-for-gestational-age neonate by routine third-trimester ultrasound

OBJECTIVES

First, to evaluate and compare the performance of routine ultrasonographic estimated fetal weight (EFW) and fetal abdominal circumference (AC) at 31 + 0 to 33 + 6 and 35 + 0 to 36 + 6 weeks' gestation in the prediction of a large-for-gestational-age (LGA) neonate born at ≥ 37 weeks' gestation. Second, to assess the additive value of fetal growth velocity between 32 and 36 weeks' gestation to the performance of EFW at 35 + 0 to 36 + 6 weeks' gestation for prediction of a LGA neonate. Third, to define the predictive performance for a LGA neonate of different EFW cut-offs on routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation. Fourth, to propose a two-stage strategy for identifying pregnancies with a LGA fetus that may benefit from iatrogenic delivery during the 38^th gestational week.

METHODS

This was a retrospective study. First, data from 21 989 singleton pregnancies that had undergone routine ultrasound examination at 31 + 0 to 33 + 6 weeks' gestation and 45 847 that had undergone routine ultrasound examination at 35 + 0 to 36 + 6 weeks were used to compare the predictive performance of EFW and AC for a LGA neonate with birth weight > 90^th and > 97^th percentiles born at ≥ 37 weeks' gestation. Second, data from 14 497 singleton pregnancies that had undergone routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation and had a previous scan at 30 + 0 to 34 + 6 weeks were used to determine, through multivariable logistic regression analysis, whether addition of growth velocity, defined as the difference in EFW Z-score or AC Z-score between the early and late third-trimester scans divided by the time interval between the scans, improved the performance of EFW at 35 + 0 to 36 + 6 weeks in the prediction of delivery of a LGA neonate at ≥ 37 weeks' gestation. Third, in the database of the 45 847 pregnancies that had undergone routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation, the screen-positive and detection rates for a LGA neonate born at ≥ 37 weeks' gestation and ≤ 10 days after the initial scan were calculated for different EFW percentile cut-offs between the 50^th and 90^th percentiles.

RESULTS

First, the areas under the receiver-operating characteristics curves (AUC) of screening for a LGA neonate were significantly higher using EFW Z-score than AC Z-score and at 35 + 0 to 36 + 6 than at 31 + 0 to 33 + 6 weeks' gestation (P < 0.001 for all). Second, the performance of screening for a LGA neonate achieved by EFW Z-score at 35 + 0 to 36 + 6 weeks was not significantly improved by addition of EFW growth velocity or AC growth velocity. Third, in screening by EFW > 90^th percentile at 35 + 0 to 36 + 6 weeks' gestation, the predictive performance for a LGA neonate born at ≥ 37 weeks' gestation was modest (65% and 46% for neonates with birth weight > 97^th and > 90^th percentiles, respectively, at a screen-positive rate of 10%), but the performance was better for prediction of a LGA neonate born ≤ 10 days after the scan (84% and 71% for neonates with birth weight > 97^th and > 90^th percentiles, respectively, at a screen-positive rate of 11%). Fourth, screening by EFW > 70^th percentile at 35 + 0 to 36 + 6 weeks' gestation predicted 91% and 82% of LGA neonates with birth weight > 97^th and > 90^th percentiles, respectively, born at ≥ 37 weeks' gestation, at a screen-positive rate of 32%, and the respective values of screening by EFW > 85^th percentile for prediction of a LGA neonate born ≤ 10 days after the scan were 88%, 81% and 15%. On the basis of these results, it was proposed that routine fetal biometry at 36 weeks' gestation is a screening rather than diagnostic test for fetal macrosomia and that EFW > 70^th percentile should be used to identify pregnancies in need of another scan at 38 weeks, at which those with EFW > 85^th percentile should be considered for iatrogenic delivery during the 38^th  week.

CONCLUSIONS

First, the predictive performance for a LGA neonate by routine ultrasonographic examination during the third trimester is higher if the scan is carried out at 36 than at 32 weeks, the method of screening is EFW than fetal AC, the outcome measure is birth weight > 97^th than > 90^th percentile and if delivery occurs within 10 days than at any stage after assessment. Second, prediction of a LGA neonate by EFW > 90^th percentile is modest and this study presents a two-stage strategy for maximizing the prenatal prediction of a LGA neonate. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Maternal and neonatal complications of fetal macrosomia: systematic review and meta-analysis

OBJECTIVE

To determine accurate estimates of risks of maternal and neonatal complications in pregnancies with fetal macrosomia by performing a systematic review of the literature and meta-analysis.

METHODS

A search of MEDLINE, EMBASE, CINAHL and The Cochrane Library was performed to identify relevant studies reporting on maternal and/or neonatal complications in pregnancies with macrosomia having a birth weight (BW) > 4000 g and/or those with birth weight > 4500 g. Prospective and retrospective cohort and population-based studies that provided data regarding both cases and controls were included. Maternal outcomes assessed were emergency Cesarean section (CS), postpartum hemorrhage (PPH) and obstetric anal sphincter injury (OASIS). Neonatal outcomes assessed were shoulder dystocia, obstetric brachial plexus injury (OBPI) and birth fractures. Meta-analysis using a random-effects model was used to estimate weighted pooled estimates of summary statistics (odds ratio (OR) and 95% CI) for each complication, according to birth weight. Heterogeneity between studies was estimated using Cochran's Q, I2 statistic and funnel plots.

RESULTS

Seventeen studies reporting data on maternal and/or neonatal complications in pregnancy with macrosomia were included. In pregnancies with macrosomia having a BW > 4000 g, there was an increased risk of the maternal complications: emergency CS, PPH and OASIS, which had OR (95% CI) of 1.98 (1.80-2.18), 2.05 (1.90-2.22) and 1.91 (1.56-2.33), respectively. The corresponding values for pregnancies with BW > 4500 g were: 2.55 (2.33-2.78), 3.15 (2.14-4.63) and 2.56 (1.97-3.32). Similarly, in pregnancies with a BW > 4000 g, there was an increased risk of the neonatal complications: shoulder dystocia, OBPI and birth fractures, which had OR (95% CI) of 9.54 (6.76-13.46), 11.03 (7.06-17.23) and 6.43 (3.67-11.28), respectively. The corresponding values for pregnancies with a BW > 4500 g were: 15.64 (11.31-21.64), 19.87 (12.19-32.40) and 8.16 (2.75-24.23).

CONCLUSION

Macrosomia is associated with serious maternal and neonatal adverse outcomes. This study provides accurate estimates of these risks, which can be used for decisions on pregnancy management. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

The use of magnetic resonance imaging in the prediction of birthweight

Extremes of fetal growth can increase adverse pregnancy outcomes, and this is equally applicable to single and multiple gestations. Traditionally, these cases have been identified using simple two-dimensional ultrasound which is quite limited by its low precision. Magnetic resonance imaging (MRI) has now been used for many years in obstetrics, mainly as an adjunct to ultrasound for congenital abnormalities and increasingly as part of the post-mortem examination. However, MRI can also be used to accurately assess fetal weight as first demonstrated by Baker et al in 1994, using body volumes rather than standard biometric measurements. This publication was followed by several others, all of which confirmed the superiority of MRI; however, despite this initial promise, the technique has never been successfully integrated into clinical practice. In this review, we provide an overview of the literature, detail the various techniques and formulas currently available, discuss the applicability to specific high-risk groups and present our vision for the future of MRI within clinical obstetrics.

Magnetic resonance imaging for prenatal estimation of birthweight in pregnancy: review of available data, techniques, and future perspectives

Fetuses at the extremes of growth abnormalities carry a risk of perinatal morbidity and death. Their identification traditionally is done by 2-dimensional ultrasound imaging, the performance of which is not always optimal. Magnetic resonance imaging superbly depicts fetal anatomy and anomalies and has contributed largely to the evaluation of high-risk pregnancies. In 1994, magnetic resonance imaging was introduced for the estimation of fetal weight, which is done by measuring the fetal body volume and converting it through a formula to fetal weight. Approximately 10 studies have shown that magnetic resonance imaging is more accurate than 2-dimensional ultrasound imaging in the estimation of fetal weight. Yet, despite its promise, the magnetic resonance imaging technique currently is not implemented clinically. Over the last 5 years, this technique has evolved quite rapidly. Here, we review the literature data, provide details of the various measurement techniques and formulas, consider the application of the magnetic resonance imaging technique in specific populations such as patients with diabetes mellitus and twin pregnancies, and conclude with what we believe could be the future perspectives and clinical application of this challenging technique. The estimation of fetal weight by ultrasound imaging is based mainly on an algorithm that takes into account the measurement of biparietal diameter, head circumference, abdominal circumference, and femur length. The estimation of fetal weight by magnetic resonance imaging is based on one of the 2 formulas: (1) magnetic resonance imaging-the estimation of fetal weight (in kilograms)=1.031×fetal body volume (in liters)+0.12 or (2) magnetic resonance imaging-the estimation of fetal weight (in grams)=1.2083×fetal body volume (in milliliters)ˆ0.9815. Comparison of these 2 formulas for the detection of large-for-gestational age neonates showed similar performance for preterm (P=.479) and for term fetuses (P=1.000). Literature data show that the estimation of fetal weight with magnetic resonance imaging carries a mean or median relative error of 2.6 up to 3.7% when measurements were performed at <1 week from delivery; whereas for the same fetuses, the relative error at 2-dimensional ultrasound imaging varied between 6.3% and 11.4%. Further, in a series of 270 fetuses who were evaluated within 48 hours from birth and for a fixed false-positive rate of 10%, magnetic resonance imaging detected 98% of large-for-gestational age neonates (≥95th percentile for gestation) compared with 67% with ultrasound imaging estimates. For the same series, magnetic resonance imaging applied to the detection of small-for-gestational age neonates ≤10th percentile for gestation, for a fixed 10% false-positive rate, reached a detection rate of 100%, compared with only 78% for ultrasound imaging. Planimetric measurement has been 1 of the main limitations of magnetic resonance imaging for the estimation of fetal weight. Software programs that allow semiautomatic segmentation of the fetus are available from imaging manufacturers or are self-developed. We have shown that all of them perform equally well for the prediction of large-for-gestational age neonates, with the advantage of the semiautomatic methods being less time-consuming. Although many challenges remain for this technique to be generalized, a 2-step strategy after the selection of a group who are at high risk of the extremes of growth abnormalities is the most likely scenario. Results of ongoing studies are awaited (ClinicalTrials.gov Identifier # NCT02713568).

Fetal weight estimation at term - ultrasound versus clinical examination with Leopold's manoeuvres: a prospective blinded observational study

BACKGROUND

Fetal weight estimation is of key importance in the decision-making process for obstetric planning and management. The literature is inconsistent on the accuracy of measurements with either ultrasound or clinical examination, known as Leopold's manoeuvres, shortly before term. Maternal BMI is a confounding factor because it is associated with both the fetal weight and the accuracy of fetal weight estimation. The aim of our study was to compare the accuracy of fetal weight estimation performed with ultrasound and with clinical examination with respect to BMI.

METHODS

In this prospective blinded observational study we investigated the accuracy of clinical examination as compared to ultrasound measurement in fetal weight estimation, taking the actual birth weight as the gold standard. In a cohort of all consecutive patients who presented in our department from January 2016 to May 2017 to register for delivery at ≥37 weeks, examination was done by ultrasound and Leopold's manoeuvres to estimate fetal weight. All examiners (midwives and physicians) had about the same level of professional experience. The primary aim was to compare overall absolute error, overall absolute percent error, absolute percent error > 10% and absolute percent error > 20% for weight estimation by ultrasound and by means of Leopold's manoeuvres versus the actual birth weight as the given gold standard, namely separately for normal weight and for overweight pregnant women.

RESULTS

Five hundred forty-three patients were included in the data analysis. The accuracy of fetal weight estimation was significantly better with ultrasound than with Leopold's manoeuvres in all absolute error calculations made in overweight pregnant women. For all error calculations performed in normal weight pregnant women, no statistically significant difference was seen in the accuracy of fetal weight estimation between ultrasound and Leopold's manoeuvres.

CONCLUSIONS

Data from our prospective blinded observational study show a significantly better accuracy of ultrasound for fetal weight estimation in overweight pregnant women only as compared to Leopold's manoeuvres with a significant difference in absolute error. We did not observe significantly better accuracy of ultrasound as compared to Leopold's manoeuvres in normal weight women. Further research is needed to analyse the situation in normal weight women.

Protocol for the prospective observational clinical study: estimation of fetal weight by MRI to PREdict neonatal MACROsomia (PREMACRO study) and small-for-gestational age neonates

INTRODUCTION

Macrosomia refers to growth beyond a specific threshold, regardless of gestational age. These fetuses are also frequently referred to as large for gestational age (LGA). Various cut-offs have been used but for research purposes, a cut-off above the 95th centile for birth weight is often preferred because it defines 90% of the population as normal weight. The use of centiles, rather than estimated weights, also accommodates preterm macrosomic infants, although most of the complications, maternal and fetal, arise during the delivery of large babies at term. This means that accurate identification of LGA fetuses (≥95th centile) may play an important role in guiding obstetric interventions, such as induction of labour or caesarean section. Traditionally, identification of fetuses suspected of macrosomia has been based on biometric measurements using two-dimensional (2D) ultrasound (US), yet this method is rather sub-optimal. We present a protocol (V.2.1, date 19 May 2016) for the estimation of fetal weight (EFW) by MRI to PREdict neonatal MACROsomia (PREMACRO study), which is a prospective observational clinical study designed to determine whether MRI at 36 + 0 to 36 + 6 weeks of gestation, as compared with 2D US, can improve the identification of LGA neonates ≥95th centile.

METHODS AND ANALYSIS

All eligible women attending the 36-week clinic will be invited to participate in the screening study for LGA fetuses ≥95th centile and will undergo US-EFW and MRI-EFW within minutes of each other. From these estimations, a centile will be derived which will be compared with the centile of birth weight used as the gold standard. Besides birth weight, other pregnancy and neonatal outcomes will be collected and analysed. The first enrolment for the study was in May 2016. As of September 2018, 2004 women have been screened and recruited to the study. The study is due to end in April 2019.

ETHICS AND DISSEMINATION

The study will be conducted in accordance with the International Conference on Harmonisation for good clinical practice and the appropriate regulatory requirement(s). A favourable ethical opinion was obtained from the Ethics Committee of the University Hospital Brugmann, reference number CE2016/44. Results will be published in peer-reviewed journals and disseminated at international conferences.

TRIAL REGISTRATION NUMBER

NCT02713568.

Prediction of large-for-gestational-age infants in pregnancies complicated by obesity: A population-based cohort study

INTRODUCTION

Infants born large for gestational age (LGA) have increased risks of adverse perinatal outcomes. Maternal obesity, defined as body mass index (BMI) ≥30 kg/m² , is one of the most prevalent risk factors for LGA and the proportion of pregnancies complicated by obesity is increasing. Early identification of women with BMI ≥30 kg/m² at increased risk of giving birth to an LGA infant may open possibilities for prevention, aiming at decreasing the incidence of LGA.

MATERIAL AND METHODS

A population-based cohort study using information from the first-trimester screening database, which was cross-linked with the Swedish Medical Birth Register. The database included 139 277 full-term singletons without fetal anomalies born between 2006 and 2015 to mothers without prepregnancy diabetes. Of these, 9.1% (n = 12 704) were infants of mothers with BMI ≥30 kg/m² . For all women with BMI ≥30 kg/m² , a prediction model for LGA to be used in early pregnancy was constructed based on information on biochemical markers and maternal characteristics. A similar model, as well as a prepregnancy prediction model, were constructed for parous women with BMI ≥30 kg/m² . In parous women, data from the previous pregnancy were also used. Receiver operating characteristic curve and area under curve (AUC) were calculated.

RESULTS

The predictive models for LGA in parous women with BMI ≥30 kg/m² prepregnancy and in early pregnancy had AUCs of 0.80 (95% CI 0.78-0.82) and 0.81 (95% CI 0.79-0.82), respectively. For all women with BMI ≥30 kg/m² , the prediction of LGA in early pregnancy had an AUC of 0.66 (95% CI 0.64-0.67).

CONCLUSIONS

Performance of the prepregnancy and early pregnancy prediction models for LGA in parous women with BMI ≥30 kg/m² was good. The predictive capacity was largely driven by previous child's birthweight. First-trimester measurements of fetal size did not improve the predictive capacity in parous women. Predictions of LGA in all women with BMI ≥30 kg/m² in early pregnancy, without taking previous child's birthweight into account, remain difficult.

External validation and clinical usefulness of first-trimester prediction models for small- and large-for-gestational-age infants: a prospective cohort study

Objective

To assess the external validity of all published first‐trimester prediction models based on routinely collected maternal predictors for the risk of small‐ and large‐for‐gestational‐age (SGA and LGA) infants. Furthermore, the clinical potential of the best‐performing models was evaluated.

Design

Multicentre prospective cohort.

Setting

Thirty‐six midwifery practices and six hospitals (in the Netherlands).

Population

Pregnant women were recruited at <16 weeks of gestation between 1 July 2013 and 31 December 2015.

Methods

Prediction models were systematically selected from the literature. Information on predictors was obtained by a web‐based questionnaire. Birthweight centiles were corrected for gestational age, parity, fetal sex, and ethnicity.

Main outcome measures

Predictive performance was assessed by means of discrimination (C‐statistic) and calibration.

Results

The validation cohort consisted of 2582 pregnant women. The outcomes of SGA <10th percentile and LGA >90th percentile occurred in 203 and 224 women, respectively. The C‐statistics of the included models ranged from 0.52 to 0.64 for SGA (n = 6), and from 0.60 to 0.69 for LGA (n = 6). All models yielded higher C‐statistics for more severe cases of SGA (<5th percentile) and LGA (>95th percentile). Initial calibration showed poor‐to‐moderate agreement between the predicted probabilities and the observed outcomes, but this improved substantially after recalibration.

Conclusion

The clinical relevance of the models is limited because of their moderate predictive performance, and because the definitions of SGA and LGA do not exclude constitutionally small or large infants. As most clinically relevant fetal growth deviations are related to ‘vascular’ or ‘metabolic’ factors, models predicting hypertensive disorders and gestational diabetes are likely to be more specific.

Tweetable abstract

The clinical relevance of prediction models for the risk of small‐ and large‐for‐gestational‐age is limited.

The clinical relevance of prediction models for the risk of small‐ and large‐for‐gestational‐age is limited.

FIGO analysis of research priorities in hyperglycemia in pregnancy

Hyperglycemia in pregnancy (HIP) is recognized as a major underlying cause of pregnancy complications and a contributing cause to health risks throughout the subsequent life of both mothers and babies, with amplification of the global epidemic of non-communicable diseases. Although some aspects of these associations are well described, detailed understanding of basic pathophysiologic mechanisms is lacking. Improved fundamental scientific knowledge must be developed to allow logical strategies for prevention and treatment. During pregnancy, much work is required to replace current empirical approaches to diagnosis and treatment of HIP with evidence based protocols, pragmatically adapted to differing health care and health economic contexts. Further, a life cycle approach to HIP, the risk of immediate pregnancy complications and later health risks to mother and baby must be developed and implemented across a wide range of health care environments. This document aims to outline key focus areas for further basic, epidemiologic, clinical and implementation research in this important area.

Prenatal prediction of postnatal large-for-dates neonates using a simplified MRI method: comparison with conventional 2D ultrasound estimates

OBJECTIVE

To evaluate the performance of a simple semi-automated method for estimation of fetal weight (EFW) using magnetic resonance imaging (MRI) as compared with two-dimensional (2D) ultrasound (US) for the prediction of large-for-dates neonates.

METHODS

Data of two groups of women with singleton pregnancy between March 2011 and May 2016 were retrieved from our database and evaluated retrospectively: the first group included women who underwent US-EFW and MRI-EFW within 48 h before delivery and the second group included women who had these evaluations between 35 + 0 weeks and 37 + 6 weeks of gestation, more than 48 h before delivery. US-EFW was based on Hadlock et al. and MRI-EFW on the formula described by Baker et al. For MRI-EFW, planimetric measurement of the fetal body volume (FBV) was performed using a semi-automated method and the time required for measurement was noted. Outcome measure was the performance of MRI-EFW vs US-EFW in the prediction of large-for-dates neonates, both ≤ 48 h and > 48 h before delivery. Receiver-operating characteristics (ROC) curves for each method were compared using the DeLong method.

RESULTS

Of the 270 women included in the first group, 48 (17.8%) newborns had birth weight ≥ 90^th centile and 30 (11.1%) ≥ 95^th centile. The second group included 83 women, and nine (10.8%) newborns had birth weight ≥ 95^th centile. Median time needed for FBV planimetric measurements in all 353 fetuses was 3.5 (range, 1.5-5.5) min. The area under the ROC curve (AUC) for prediction of large-for-dates neonates by prenatal MRI performed within 48 h before delivery was significantly higher than that by US (for birth weight ≥ 90^th centile, difference between AUCs = 0.085, standard error (SE) = 0.020, P < 0.001; for birth weight ≥ 95^th centile, difference between AUCs = 0.036, SE = 0.014, P = 0.01). Similarly, MRI-EFW was better than US-EFW in predicting birth weight ≥ 95^th centile when both examinations were performed > 48 h prior to delivery (difference between AUCs = 0.077, SE = 0.039, P = 0.045).

CONCLUSION

MRI planimetry using our purpose-designed semi-automated method is not time-consuming. The predictive performance of MRI-EFW performed immediately prior to or remote from delivery is significantly better than that of US-EFW for the prediction of large-for-dates neonates. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Accelerated fetal growth in early pregnancy and risk of severe large-for-gestational-age and macrosomic infant: a cohort study in a low-risk population

INTRODUCTION

Our objective was to examine the association between fetal growth in early pregnancy and risk of severe large-for-gestational-age (LGA) and macrosomia at birth in a low-risk population.

MATERIAL AND METHODS

Cohort study that included 68 771 women with non-anomalous singleton pregnancies, without history of diabetes or hypertension, based on an electronic database on pregnancies and deliveries in Stockholm-Gotland Region, Sweden, 2008-2014. We performed multivariable logistic regression to estimate the association between accelerated fetal growth occurring in the first through early second trimester as measured by ultrasound and LGA and macrosomia at birth. Restricted analyses were performed in the groups without gestational diabetes and with normal body mass index (18.5-24.9 kg/m² ).

RESULTS

When adjusting for confounders, the odds of having a severely LGA or macrosomic infant were elevated in mothers with fetuses that were at least 7 days larger than expected as compared with mothers without age discrepancy at the second-trimester scan (adjusted odds ratio 1.80; 95% CI 1.23-2.64 and adjusted odds ratio 2.15; 95% CI 1.55-2.98, respectively). Additionally, mothers without gestational diabetes and mothers with normal weight had an elevated risk of having a severely LGA or macrosomic infant when the age discrepancy by second-trimester ultrasound was at least 7 days.

CONCLUSIONS

In a low-risk population, ultrasound-estimated accelerated fetal growth in early pregnancy was associated with an increased risk of having a severely LGA or macrosomic infant.

Clinical, ultrasound and molecular biomarkers for early prediction of large for gestational age infants in nulliparous women: An international prospective cohort study

Objective

To develop a prediction model for term infants born large for gestational age (LGA) by customised birthweight centiles.

Methods

International prospective cohort of nulliparous women with singleton pregnancy recruited to the Screening for Pregnancy Endpoints (SCOPE) study. LGA was defined as birthweight above the 90^th customised centile, including adjustment for parity, ethnicity, maternal height and weight, fetal gender and gestational age. Clinical risk factors, ultrasound parameters and biomarkers at 14–16 or 19–21 weeks were combined into a prediction model for LGA infants at term using stepwise logistic regression in a training dataset. Prediction performance was assessed in a validation dataset using area under the Receiver Operating Characteristics curve (AUC) and detection rate at fixed false positive rates.

Results

The prevalence of LGA at term was 8.8% (n = 491/5628). Clinical and ultrasound factors selected in the prediction model for LGA infants were maternal birthweight, gestational weight gain between 14–16 and 19–21 weeks, and fetal abdominal circumference, head circumference and uterine artery Doppler resistance index at 19–21 weeks (AUC 0.67; 95%CI 0.63–0.71). Sensitivity of this model was 24% and 49% for a fixed false positive rate of 10% and 25%, respectively. The addition of biomarkers resulted in selection of random glucose, LDL-cholesterol, vascular endothelial growth factor receptor-1 (VEGFR1) and neutrophil gelatinase-associated lipocalin (NGAL), but with minimal improvement in model performance (AUC 0.69; 95%CI 0.65–0.73). Sensitivity of the full model was 26% and 50% for a fixed false positive rate of 10% and 25%, respectively.

Conclusion

Prediction of LGA infants at term has limited diagnostic performance before 22 weeks but may have a role in contingency screening in later pregnancy.

Implications of maternal obesity on fetal growth and the role of ultrasound

Over fifty percent of women entering pregnancy are overweight or obese. This has a significant impact on short and long term maternal and infant health outcomes, and the intergenerational effects of obesity are now a major public health problem globally. Areas covered: There are two major pathways contributing to fetal growth. Glucose and insulin directly affect growth, while other substrates such as leptin, adiponectin and insulin-like growth factors indirectly influence growth through structural and morphological effects on the placenta, uteroplacental blood flow, and regulation of placental transporters. Advances in ultrasonography over the past decade have led to interest in the prediction of the fetus at risk of overgrowth and adiposity utilizing both standard ultrasound biometry and fetal body composition measurements. However, to date there is no consensus regarding the definition of fetal overgrowth, its reporting, and clinical management. Expert commentary: Maternal dietary intervention targeting the antenatal period appear to be too late to sufficiently affect fetal growth. The peri-conceptual period and early pregnancy are being evaluated to determine if the intergenerational effects of maternal obesity can be altered to improve newborn, infant and child health.

Maternal cardiac function at 35-37 weeks' gestation: relationship with birth weight

OBJECTIVE

To evaluate the relationship between maternal cardiovascular parameters and neonatal birth weight and examine the potential value of these parameters in improving the prediction of small-for-gestational-age (SGA) and large-for-gestational-age (LGA) neonates provided by maternal characteristics and medical history.

METHODS

In 2835 singleton pregnancies maternal characteristics and medical history were recorded and maternal cardiovascular parameters were measured. The observed measurements of cardiovascular parameters were expressed as multiples of the normal median (MoM) values after adjustment for those characteristics found to provide a substantial contribution to their measurement. Regression analysis was used to determine the significance of association between the normalized values of the cardiovascular parameters with birth-weight Z-score. Multivariable logistic regression analysis was then used to determine if the maternal factors, fetal biometry and maternal cardiovascular parameters had a significant contribution to predicting SGA and LGA neonates. The performance of screening was determined by the area under receiver-operating characteristics curves (AUC).

RESULTS

In the study population there were significant positive associations between maternal cardiac output and heart rate with neonatal birth-weight Z-score, and significant negative associations between total peripheral resistance and mean arterial pressure (MAP) with neonatal birth-weight Z-score. In pregnancies delivering SGA neonates (n = 249 (8.8%)), cardiac output and heart rate were lower and total peripheral resistance and MAP were higher, whereas in pregnancies delivering LGA neonates (n = 292 (10.3%)) cardiac output and heart rate were higher and total peripheral resistance and MAP were lower. The performance of screening for delivery of SGA neonates achieved by maternal characteristics and fetal biometry was not improved by the measurement of maternal cardiovascular parameters. There was a small but significant improvement in the performance of screening for delivery of LGA neonates by maternal factors and fetal biometry with the addition of maternal heart rate (comparison of AUC, P = 0.0095).

CONCLUSIONS

There are significant associations between maternal cardiac output, heart rate, total peripheral resistance and MAP and neonatal birth-weight Z-score; such findings reflect the close relationship between maternal cardiac function and fetal demands. However, assessment of these parameters at 35-37 weeks' gestation is unlikely to improve substantially the performance of screening for SGA or LGA neonates provided by a combination of maternal factors and fetal biometry. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.