Competing-risks model for prediction of small-for-gestational-age neonate from estimated fetal weight at 19-24 weeks' gestation

External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester: multicenter cohort study

OBJECTIVES

To examine the predictive performance of the Fetal Medicine Foundation (FMF) competing-risks model for the first-trimester prediction of a small-for-gestational-age (SGA) neonate in a large, independent, unselected European cohort and to compare the competing-risks algorithm with previously published logistic-regression models.

METHODS

This was a retrospective, non-interventional, multicenter cohort study including 35 170 women with a singleton pregnancy who underwent a first-trimester ultrasound assessment between 11 + 0 and 13 + 6 weeks' gestation. We used the default FMF competing-risks model for the prediction of SGA combining maternal factors, uterine artery pulsatility index (UtA-PI), pregnancy-associated plasma protein-A (PAPP-A) and placental growth factor (PlGF) to obtain risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the predictive performance in terms of discrimination and calibration and compared it with the published data on the model's development population and with published logistic-regression equations.

RESULTS

At a 10% false-positive rate, maternal factors and UtA-PI predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 44.7% and 51.7%. Also at a 10% false-positive rate, maternal factors, UtA-PI and PAPP-A predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 46.2% and 51.7%. At a 10% false-positive rate, maternal factors, UtA-PI, PAPP-A and PlGF predicted 47.6% and 66.7% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 50.0% and 69.0%. These data were similar to those reported in the original model's development study and substantially better than those calculated using pre-existing logistic-regression models (McNemar's test, P < 0.001). The FMF competing-risks model was well calibrated.

CONCLUSIONS

The FMF competing-risks model for the first-trimester prediction of SGA is reproducible in an independent, unselected low-risk cohort and superior to logistic-regression approaches. © 2025 International Society of Ultrasound in Obstetrics and Gynecology.

The value of fetal growth trajectory during pregnancy in predicting small for gestational age neonates at term

BACKGROUND

The predictive value of trajectory identified by group-based trajectory modeling (GBTM) has been discussed but its value in predicting small for gestational age (SGA) neonates is still unclear. This study aims to describe the trajectory of fetal growth of estimated fetal weight (EFW) during pregnancy and compare its performance to growth velocity of EFW and EFW z-scores at each scan in predicting SGA neonates at term.

METHODS

The growth trajectory for EFW obtained from ultrasound scan at around 23-24, 31-32, 37-39 weeks of gestation of 1699 women from Shenzhen Birth Cohort Study was identified using GBTM. The area under receiver operating characteristics curve (AUC), Brier scores and Decision curve analysis (DCA) was used to evaluate the discrimination, calibration performance and clinical usefulness of EFW growth trajectory, EFW growth velocity between each stage and EFW z-scores at each scan.

RESULTS

Four trajectory groups of EFW which described as "very low-stable", "low-stable", "average-stable", "rising-falling" were identified. The growth trajectory performed better in discrimination and calibration than growth velocity, with AUC of 0.76 (95%CI: 0.73-0.80) and Brier score of 0.067 in predicting SGA neonates at term. When compared to the EFW z-scores, growth trajectory performed better than EFW z-scores of 23-24 weeks (AUC = 0.72, 95%CI: 0.68-0.76, Brier score = 0.073), but not as well as EFW z-scores of 37-39 weeks of gestation (AUC = 0.88, 95%CI: 0.86-0.91, Brier score = 0.060).

CONCLUSIONS

EFW z-scores of 37-39 weeks of gestation outperformed in predicting SGA neonates at term than growth trajectory and velocity. Growth trajectory has better potential for serial ultrasound examinations to describe the process of fetal growth and to predict SGA neonates at term than fetal growth velocity.

Maternal Demographic Patterns in Medication use During Pregnancy: A Nationwide Register Study

In recent years, medication use during pregnancy has increased, yet its association with maternal characteristics remains unclear. To address this gap, we aimed to investigate how maternal age, pre-gestational body mass index (BMI), smoking, parity, ethnic origin and employment status relate to medication use during pregnancy. We conducted a nationwide Danish registry study, including 698 447 clinically recognised pregnancies with a gestational age of at least 10 weeks, spanning from 2008 to 2018. Medication use was estimated based on prescription redemptions during pregnancy and stratified by the demographic factors of interest. Overall, 60.3% of pregnant women redeemed at least one prescription, while 28.9% redeemed multiple medications. Notably, higher usage was observed among women aged 35 or older, those with a BMI of 30 kg/m2 or more, smokers, multipara, Black women, and early retirees. Medication combination patterns differed with the demographic subgroups. These findings highlight notable differences in medication use among demographic groups during pregnancy, underscoring the need for tailored healthcare strategies during pregnancy.

Maternal age and body mass index and risk of labor dystocia after spontaneous labor onset among nulliparous women: A clinical prediction model

INTRODUCTION

Obstetrics research has predominantly focused on the management and identification of factors associated with labor dystocia. Despite these efforts, clinicians currently lack the necessary tools to effectively predict a woman's risk of experiencing labor dystocia. Therefore, the objective of this study was to create a predictive model for labor dystocia.

MATERIAL AND METHODS

The study population included nulliparous women with a single baby in the cephalic presentation in spontaneous labor at term. With a cohort-based registry design utilizing data from the Copenhagen Pregnancy Cohort and the Danish Medical Birth Registry, we included women who had given birth from 2014 to 2020 at Copenhagen University Hospital-Rigshospitalet, Denmark. Logistic regression analysis, augmented by a super learner algorithm, was employed to construct the prediction model with candidate predictors pre-selected based on clinical reasoning and existing evidence. These predictors included maternal age, pre-pregnancy body mass index, height, gestational age, physical activity, self-reported medical condition, WHO-5 score, and fertility treatment. Model performance was evaluated using the area under the receiver operating characteristics curve (AUC) for discriminative capacity and Brier score for model calibration.

RESULTS

A total of 12,445 women involving 5,525 events of labor dystocia (44%) were included. All candidate predictors were retained in the final model, which demonstrated discriminative ability with an AUC of 62.3% (95% CI:60.7-64.0) and Brier score of 0.24.

CONCLUSIONS

Our model represents an initial advancement in the prediction of labor dystocia utilizing readily available information obtainable upon admission in active labor. As a next step further model development and external testing across other populations is warranted. With time a well-performing model may be a step towards facilitating risk stratification and the development of a user-friendly online tool for clinicians.

Validation of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in early third trimester

OBJECTIVE

To evaluate the new 36-week Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at an earlier gestation of 30 + 0 to 34 + 0 weeks.

METHODS

This was a retrospective multicenter cohort study of prospectively collected data on 3012 women with a singleton pregnancy undergoing ultrasound examination at 30 + 0 to 34 + 0 weeks' gestation as part of a universal screening program. We used the default FMF competing-risks model for prediction of SGA at 36 weeks' gestation combining maternal factors (age, obstetric and medical history, weight, height, smoking status, race, mode of conception), estimated fetal weight (EFW) and uterine artery pulsatility index (UtA-PI) to calculate risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the accuracy of the model by means of discrimination and calibration.

RESULTS

The prediction of SGA < 3rd percentile improved with the addition of UtA-PI and with a shorter examination-to-delivery interval. For a 10% false-positive rate, maternal factors, EFW and UtA-PI predicted 88.0%, 74.4% and 72.8% of SGA < 3rd percentile delivered at < 37, < 40 and < 42 weeks' gestation, respectively. The respective values for SGA < 10th percentile were 86.1%, 69.3% and 66.2%. In terms of population stratification, if the biomarkers used are EFW and UtA-PI and the aim is to detect 90% of SGA < 10th percentile, then 10.8% of the population should be scanned within 2 weeks after the initial assessment, an additional 7.2% (total screen-positive rate (SPR), 18.0%) should be scanned within 2-4 weeks after the initial assessment and an additional 11.7% (total SPR, 29.7%) should be examined within 4-6 weeks after the initial assessment. The new model was well calibrated.

CONCLUSIONS

The 36-week FMF competing-risks model for SGA is also applicable and accurate at 30 + 0 to 34 + 0 weeks and provides effective risk stratification, especially for cases leading to delivery < 37 weeks of gestation. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Prediction of adverse perinatal outcome at midgestation

OBJECTIVES

First, to investigate the association between adverse neonatal outcomes and birth weight and gestational age at delivery. Second, to describe the distribution of adverse neonatal outcomes within different risk strata derived by a population stratification scheme based on the midgestation risk assessment for small-for-gestational-age (SGA) neonates using a competing-risks model.

METHODS

This was a prospective observational cohort study in women with a singleton pregnancy attending a routine hospital visit at 19 + 0 to 23 + 6 weeks' gestation. The incidence of neonatal unit (NNU) admission for ≥ 48 h was evaluated within different birth-weight-percentile subgroups. The pregnancy-specific risk of delivery with SGA < 10th percentile at < 37 weeks was estimated by the competing-risks model for SGA, combining maternal factors and the likelihood functions of Z-score of sonographically estimated fetal weight and uterine artery pulsatility index multiples of the median. The population was stratified into six risk categories: > 1 in 4, > 1 in 10 to ≤ 1 in 4, > 1 in 30 to ≤ 1 in 10, > 1 in 50 to ≤ 1 in 30, > 1 in 100 to ≤ 1 in 50 and ≤ 1 in 100. The outcome measures were admission to the NNU for a minimum of 48 h, perinatal death and major neonatal morbidity. The incidence of each adverse outcome was estimated in each risk stratum.

RESULTS

In the study population of 40 241 women, 0.8%, 2.5%, 10.8%, 10.2%, 19.0% and 56.7% were in the risk strata > 1 in 4, > 1 in 10 to ≤ 1 in 4, > 1 in 30 to ≤ 1 in 10, > 1 in 50 to ≤ 1 in 30, > 1 in 100 to ≤ 1 in 50 and ≤ 1 in 100, respectively. Women in higher-risk strata were more likely to deliver a baby that suffered an adverse outcome. The incidence of NNU admission for ≥ 48 h was highest in the > 1 in 4 risk stratum (31.9% (95% CI, 26.9-36.9%)) and it gradually decreased until the ≤ 1 in 100 risk stratum (5.6% (95% CI, 5.3-5.9%)). The mean gestational age at delivery in SGA cases with NNU admission for ≥ 48 h was 32.9 (95% CI, 32.2-33.7) weeks for risk stratum > 1 in 4 and progressively increased to 37.5 (95% CI, 36.8-38.2) weeks for risk stratum ≤ 1 in 100. The incidence of NNU admission for ≥ 48 h was highest for neonates with birth weight below the 1st percentile (25.7% (95% CI, 23.0-28.5%)) and decreased progressively until the 25th to < 75th percentile interval (5.4% (95% CI, 5.1-5.7%)). Preterm SGA neonates < 10th percentile had significantly higher incidence of NNU admission for ≥ 48 h compared with preterm non-SGA neonates (48.7% (95% CI, 45.0-52.4%) vs 40.9% (95% CI, 38.5-43.3%); P < 0.001). Similarly, term SGA neonates < 10th percentile had significantly higher incidence of NNU admission for ≥ 48 h compared with term non-SGA neonates (5.8% (95% CI, 5.1-6.5%) vs 4.2% (95% CI, 4.0-4.4%); P < 0.001).

CONCLUSIONS

Birth weight has a continuous association with the incidence of adverse neonatal outcomes, which is affected by gestational age. Pregnancies at high risk of SGA, estimated at midgestation, are also at increased risk for adverse neonatal outcomes. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

External validation of Fetal Medicine Foundation competing-risks model for midgestation prediction of small-for-gestational-age neonates in Spanish population

OBJECTIVE

To examine the external validity of the new Fetal Medicine Foundation (FMF) competing-risks model for prediction in midgestation of small-for-gestational-age (SGA) neonates.

METHODS

This was a single-center prospective cohort study of 25 484 women with a singleton pregnancy undergoing routine ultrasound examination at 19 + 0 to 23 + 6 weeks' gestation. The FMF competing-risks model for the prediction of SGA combining maternal factors and midgestation estimated fetal weight by ultrasound scan (EFW) and uterine artery pulsatility index (UtA-PI) was used to calculate risks for different cut-offs of birth-weight percentile and gestational age at delivery. The predictive performance was evaluated in terms of discrimination and calibration.

RESULTS

The validation cohort was significantly different in composition compared with the FMF cohort in which the model was developed. In the validation cohort, at a 10% false-positive rate (FPR), maternal factors, EFW and UtA-PI yielded detection rates of 69.6%, 38.7% and 31.7% for SGA < 10th percentile with delivery at < 32, < 37 and ≥ 37 weeks' gestation, respectively. The respective values for SGA < 3rd percentile were 75.7%, 48.2% and 38.1%. Detection rates in the validation cohort were similar to those reported in the FMF study for SGA with delivery at < 32 weeks but lower for SGA with delivery at < 37 and ≥ 37 weeks. Predictive performance in the validation cohort was similar to that reported in a subgroup of the FMF cohort consisting of nulliparous and Caucasian women. Detection rates in the validation cohort at a 15% FPR were 77.4%, 50.0% and 41.5% for SGA < 10th percentile with delivery at < 32, < 37 and ≥ 37 weeks, respectively, which were similar to the respective values reported in the FMF study at a 10% FPR. The model had satisfactory calibration.

CONCLUSION

The new competing-risks model for midgestation prediction of SGA developed by the FMF performs well in a large independent Spanish population. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Personalized stratification of pregnancy care for small for gestational age neonates from biophysical markers at midgestation

BACKGROUND

Antenatal identification of pregnancies at high risk of delivering small for gestational age neonates may improve the management of the condition and reduce the associated adverse perinatal outcomes. In a series of publications, we have developed a new competing-risks model for small for gestational age prediction, and we demonstrated that the new approach has a superior performance to that of the traditional methods. The next step in shaping the appropriate management of small for gestational age is the timely assessment of these high-risk pregnancies according to an antenatal stratification plan.

OBJECTIVE

This study aimed to demonstrate the stratification of pregnancy care based on individual patient risk derived from the application of the competing-risks model for small for gestational age that combines maternal factors with sonographic estimated fetal weight and uterine artery pulsatility index at midgestation.

STUDY DESIGN

This was a prospective observational study of 96,678 singleton pregnancies undergoing routine ultrasound examination at 19 to 24 weeks of gestation, which included recording of estimated fetal weight and measurement of uterine artery pulsatility index. The competing-risks model for small for gestational age was used to create a patient-specific stratification curve capable to define a specific timing for a repeated ultrasound examination after 24 weeks. We examined different stratification plans with the intention of detecting approximately 80%, 85%, 90%, and 95% of small for gestational age neonates with birthweight <3rd and <10th percentiles at any gestational age at delivery until 36 weeks; all pregnancies would be offered a routine ultrasound examination at 36 weeks.

RESULTS

The stratification of pregnancy care for small for gestational age can be based on a patient-specific stratification curve. Factors from maternal history, low estimated fetal weight, and increased uterine artery pulsatility index shift the personalized risk curve toward higher risks. The degree of shifting defines the timing for assessment for each pregnancy. If the objective of our antenatal plan was to detect 80%, 85%, 90%, and 95% of small for gestational age neonates at any gestational age at delivery until 36 weeks, the median (range) proportions (percentages) of population examined per week would be 3.15 (1.9-3.7), 3.85 (2.7-4.5), 4.75 (4.0-5.4), and 6.45 (3.7-8.0) for small for gestational age <3rd percentile and 3.8 (2.5-4.6), 4.6 (3.6-5.4), 5.7 (3.8-6.4), and 7.35 (3.3-9.8) for small for gestational age <10th percentile, respectively.

CONCLUSION

The competing-risks model provides an effective personalized continuous stratification of pregnancy care for small for gestational age which is based on individual characteristics and biophysical marker levels recorded at the midgestation scan.

Competing-risks model for prediction of small-for-gestational-age neonate at 36 weeks' gestation

OBJECTIVES

To develop further a competing-risks model for the prediction of a small-for-gestational-age (SGA) neonate by including sonographically estimated fetal weight (EFW) and biomarkers of impaired placentation at 36 weeks' gestation, and to compare the performance of the new model with that of the traditional EFW < 10^th percentile cut-off.

METHODS

This was a prospective observational study in 29 035 women with a singleton pregnancy undergoing routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation. A competing-risks model for the prediction of a SGA neonate was used. The parameters included in the prior-history model were provided in previous studies. An interaction continuous model was used for the EFW likelihood. A folded plane regression model was fitted to describe likelihoods of biomarkers of impaired placentation. Stratification plans were also developed. The new model was evaluated and compared with EFW percentile cut-offs.

RESULTS

The performance of the model was better for predicting SGA neonates delivered closer to the point of assessment. The prediction provided by maternal factors alone was improved significantly by the addition of EFW, uterine artery pulsatility index (UtA-PI) and placental growth factor (PlGF) but not by mean arterial pressure or soluble fms-like tyrosine kinase-1. At a 10% false-positive rate, maternal factors and EFW predicted 77.6% and 65.8% of SGA neonates < 10^th percentile delivered before 38 and 42 weeks, respectively. The respective figures for SGA < 3^rd percentile were 85.5% and 74.2%. Addition of UtA-PI and PlGF resulted in marginal improvement in prediction of SGA < 3^rd percentile requiring imminent delivery. A competing-risks approach that combines maternal factors and EFW performed better when compared with fixed EFW percentile cut-offs at predicting a SGA neonate, especially with increasing time interval between assessment and delivery. The new model was well-calibrated.

CONCLUSIONS

A competing-risks model provides effective risk stratification for a SGA neonate at 35 + 0 to 36 + 6 weeks' gestation and is superior to EFW percentile cut-offs. The use of biomarkers of impaired placentation in addition to maternal factors and fetal biometry results in small improvement of the predictive performance for a neonate with severe SGA. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Third trimester uterine artery Doppler for prediction of adverse perinatal outcomes

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Use of a Feed-Forward Back Propagation Network for the Prediction of Small for Gestational Age Newborns in a Cohort of Pregnant Patients with Thrombophilia

(1) Background: Fetal growth restriction is a relatively common disorder in pregnant patients with thrombophilia. New artificial intelligence algorithms are a promising option for the prediction of adverse obstetrical outcomes. The aim of this study was to evaluate the predictive performance of a Feed-Forward Back Propagation Network (FFBPN) for the prediction of small for gestational age (SGA) newborns in a cohort of pregnant patients with thrombophilia. (2) Methods: This observational retrospective study included all pregnancies in women with thrombophilia who attended two tertiary maternity hospitals in Romania between January 2013 and December 2020. Bivariate associations of SGA and each predictor variable were evaluated. Clinical and paraclinical predictors were further included in a FFBPN, and its predictive performance was assessed. (3) Results: The model had an area under the curve (AUC) of 0.95, with a true positive rate of 86.7%, and a false discovery rate of 10.5%. The overall accuracy of our model was 90%. (4) Conclusion: This is the first study in the literature that evaluated the performance of a FFBPN for the prediction of pregnant patients with thrombophilia at a high risk of giving birth to SGA newborns, and its promising results could lead to a tailored prenatal management.

Second-trimester contingent screening for small-for-gestational-age neonate

OBJECTIVES

First, to investigate the additive value of second-trimester placental growth factor (PlGF) for the prediction of a small-for-gestational-age (SGA) neonate. Second, to examine second-trimester contingent screening strategies.

METHODS

This was a prospective observational study in women with singleton pregnancy undergoing routine ultrasound examination at 19-24 weeks' gestation. We used the competing-risks model for prediction of SGA. The parameters for the prior model and the likelihoods for estimated fetal weight (EFW) and uterine artery pulsatility index (UtA-PI) were those presented in previous studies. A folded-plane regression model was fitted in the dataset of this study to describe the likelihood of PlGF. We compared the prediction of screening by maternal risk factors against the prediction provided by a combination of maternal risk factors, EFW, UtA-PI and PlGF. We also examined the additive value of PlGF in a policy that uses maternal risk factors, EFW and UtA-PI.

RESULTS

The study population included 40 241 singleton pregnancies. Overall, the prediction of SGA improved with increasing degree of prematurity, with increasing severity of smallness and in the presence of coexisting pre-eclampsia. The combination of maternal risk factors, EFW, UtA-PI and PlGF improved significantly the prediction provided by maternal risk factors alone for all the examined cut-offs of birth weight and gestational age at delivery. Screening by a combination of maternal risk factors and serum PlGF improved the prediction of SGA when compared to screening by maternal risk factors alone. However, the incremental improvement in prediction was decreased when PlGF was added to screening by a combination of maternal risk factors, EFW and UtA-PI. If first-line screening for a SGA neonate with birth weight < 10^th percentile delivered at < 37 weeks' gestation was by maternal risk factors and EFW, the same detection rate of 90%, at an overall false-positive rate (FPR) of 50%, as that achieved by screening with maternal risk factors, EFW, UtA-PI and PlGF in the whole population can be achieved by reserving measurements of UtA-PI and PlGF for only 80% of the population. Similarly, in screening for a SGA neonate with birth weight < 10^th percentile delivered at < 30 weeks, the same detection rate of 90%, at an overall FPR of 14%, as that achieved by screening with maternal risk factors, EFW, UtA-PI and PlGF in the whole population can be achieved by reserving measurements of UtA-PI and PlGF for only 70% of the population. The additive value of PlGF in reducing the FPR to about 10% with a simultaneous detection rate of 90% for a SGA neonate with birth weight < 3^rd percentile born < 30 weeks, is gained by measuring PlGF in only 50% of the population when first-line screening is by maternal factors, EFW and UtA-PI.

CONCLUSIONS

The combination of maternal risk factors, EFW, UtA-PI and PlGF provides effective second-trimester prediction of SGA. Serum PlGF is useful for predicting a SGA neonate with birth weight < 3^rd percentile born < 30 weeks after an inclusive assessment by maternal risk factors and biophysical markers. Similar detection rates and FPRs can be achieved by application of contingent screening strategies. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Predictive performance for placental dysfunction related stillbirth of the competing risks model for small for gestational age fetuses

OBJECTIVES

First, to examine the predictive performance for placental dysfunction related stillbirths of the competing risks model for small for gestational age (SGA) fetuses based on a combination of maternal risk factors, estimated fetal weight (EFW) and uterine artery pulsatility index (UtA-PI); and second, to compare the performance of this model to that of stillbirth-specific model utilizing the same biomarkers and to the Royal College of Obstetricians and Gynecologists (RCOG) guideline for the investigation and management of the SGA fetus.

DESIGN

Prospective observational study.

SETTING

Two UK maternity hospitals.

POPULATION

131,514 women with singleton pregnancies attending for routine ultrasound examination at 19-24 weeks' gestation.

METHODS

The predictive performance for stillbirth achieved by three models was compared. Main outcome measure Placental dysfunction related stillbirth.

RESULTS

At 10% false positive rate, the competing risks model predicted 59%, 66% and 71% of placental dysfunction related stillbirths, at any gestation, at <37 weeks and at <32 weeks, respectively, which were similar to the respective figures of 62%, 70% and 73% for the stillbirth-specific model. At a screen positive rate of 21.8 %, as defined by the RCOG guideline, the competing risks model predicted 71%, 76% and 79% of placental dysfunction related stillbirths at any gestation, at <37 weeks and at <32 weeks, respectively, and the respective figures for the RCOG guideline were 40%, 44% and 42%.

CONCLUSION

The predictive performance for placental dysfunction related stillbirths by the competing risks model for SGA was similar to the stillbirth-specific model and superior to the RCOG guideline.

Competing Risks Model for Prediction of Small for Gestational Age Neonates and the Role of Second Trimester Soluble Fms-like Tyrosine Kinase-1

Small for gestational age (SGA) fetuses/neonates are characterized by the increased risk for adverse outcomes that can be reduced if the condition is identified antenatally. We have recently developed a new approach in SGA prediction that considers SGA a spectrum condition that is reflected in two dimensions: gestational age at delivery and Z score in birth weight for gestational age. The new method has a better predictive ability than the traditionally used risk-scoring systems and logistic regression models. In this prospective study in 40241 singleton pregnancies, at 19–24 weeks’ gestation, we examined the potential value of the antiangiogenic soluble fms-like tyrosine kinase-1 (sFlt-1) and the ratio of sFlt-1 to the angiogenic placental growth factor (PlGF) in the prediction of SGA. We found that first, sFlt-1 did not improve the performance of screening by maternal risk factors, and second, the ratio of sFlt-1/PlGF had a worse performance than PlGF alone in the prediction of SGA. Consequently, second trimester sFlt-1 and sFlt-1/PlGF are not useful in screening for SGA.

Evaluation of the RCOG guideline for the prediction of neonates that are small for gestational age and comparison with the competing risks model

OBJECTIVE

To examine the predictive performance of the relevant guideline by the Royal College of Obstetricians and Gynaecologists (RCOG) for neonates that are small for gestational age (SGA), and to compare the performance of the RCOG guideline with that of our competing risks model for SGA.

DESIGN

Prospective observational study.

SETTING

Obstetric ultrasound departments in two UK maternity hospitals.

POPULATION

A total of 96 678 women with singleton pregnancies attending for routine ultrasound examination at 19-24 weeks of gestation.

METHODS

Risks for SGA for different thresholds were computed, according to the competing risks model using maternal history, second-trimester estimated fetal weight, uterine artery pulsatility index and mean arterial pressure. The detection rates by the RCOG guideline scoring system and the competing risks model for SGA were compared, at the screen positive rate (SPR) derived from the RCOG guideline.

MAIN OUTCOME MEASURES

Small for gestational age (SGA), <10th or <3rd percentile, for different gestational age thresholds.

RESULTS

At an SPR of 22.5%, as defined by the RCOG guideline, the competing risks model predicted 56, 72 and 81% of cases of neonates that are SGA, with birthweights of <10th percentile, delivered at ≥37, <37 and <32 weeks of gestation, respectively, which were significantly higher than the respective figures of 36, 44 and 45% achieved by the application of the RCOG guideline. The respective figures for neonates that were SGA with birthweights of <3rd percentile were 66, 79, 85 and 41, 45, 44%.

CONCLUSION

The detection rate for neonates that were SGA with the competing risk approach is almost double than that obtained with the RCOG guideline.

TWEETABLE ABSTRACT

The competing risks approach for the prediction of SGA performs better than the existing RCOG guideline.

Epidemiological evidence that severe obese women (pre-pregnancy BMI ≥40 kg/m2) should lose weight during their pregnancy

OBJECTIVES

Defining the optimal gestational weight gain (optGWG) allowing to have "normal shaped" babies (10% of Small for gestational age, SGA, and10% of large LGA babies) in severe obese women (pre-pregnancy BMI ≥40 kg/m²).

STUDY DESIGN

South-Reunion University's maternity (Reunion Island, Indian Ocean). 20 year-observational cohort study (2001-2019). Epidemiological perinatal data base with information on obstetrical and neonatal risk factors. All consecutive term (37-42 weeks gestation) singleton pregnancies (>21 weeks) live birth pregnancies delivered in the maternity.

MAIN OUTCOME MEASURES

OptGWG to obtain newborns as close as possible of the 10% SGA/LGA goal for each BMI categories, 15-19.9, 20-24.9 …, as well as severe obese ≥40 kg/m².

RESULTS

Of the 71,318 singleton term live births (37 weeks onward), we could define the maternal pre-pregnancy body mass index and the GWG in of 61,764 patients (86.6%). Severe obese 40 kg/m² losing 5-9.9 kg have 12.9% of LGA and 11.9% of SGA babies. Those losing 10 kg and more 12.7% of LGA and 7.3% of SGA. Our formerly proposed linear equation (validated from 15 to 40 kg/m²) may be prolonged at 45 kg/m².   opGWG(kg)=-1.2pp BMI(Kg/m2)+42±2kg.

CONCLUSION

In our population, a 32 kg/m² obese should gain 3.6 kg (instead of 5-9 kg, IOM 2009). A very obese 40 kg/m² should lose 6 kg, and a severe obese 45 kg/m² lose 12 kg.