Should Fetal Growth Charts Be References or Standards?

The impact of cohort inclusion/exclusion criteria on pregnancy weight gain chart percentiles

Pregnancy weight gain standards are charts describing percentiles of weight gain among participants with no risk factors that could adversely affect weight gain. This detailed information is burdensome to collect. We investigated the extent to which exclusion of various pre-pregnancy, pregnancy and postpartum factors impacted the values of pregnancy weight gain percentiles. We examined pregnancy weight gain (kg) among 3178 participants of the US nuMoM2b-Heart Health Study (HHS). We identified five groups of potential exclusion criteria for pregnancy weight gain standards: socio-economic characteristics (group 1), maternal morbidities (group 2), lifestyle/behaviour factors (group 3), adverse neonatal outcomes (group 4) and longer-term adverse outcomes (group 5). We established the impact of different exclusion criteria by comparing the median, 25th and 75th percentiles of weight gain in the full cohort with the values after applying each of the five exclusion criteria groups. Differences > 0·75 kg were considered meaningful. Excluding participants with group 1, 2, 3 or 4 exclusion criteria had no impact on the 25th, median or 75th percentiles of pregnancy weight gain. Percentiles were only meaningfully different after excluding participants in group 5 (longer-term adverse outcomes), which shifted the upper end of the weight gain distribution to lower values (e.g. 75th percentile decreased from 19·6 kg to 17·8 kg). This shift was due to exclusion of participants with excess postpartum weight retention > 5 kg or > 10 kg. Except for excess postpartum weight retention, most potential exclusion criteria for pregnancy weight gain standards did not meaningfully impact chart percentiles.

Development and validation of a prognostic model to predict birth weight: individual participant data meta-analysis

Objective

To predict birth weight at various potential gestational ages of delivery based on data routinely available at the first antenatal visit.

Design

Individual participant data meta-analysis.

Data sources

Individual participant data of four cohorts (237 228 pregnancies) from the International Prediction of Pregnancy Complications (IPPIC) network dataset.

Eligibility criteria for selecting studies

Studies in the IPPIC network were identified by searching major databases for studies reporting risk factors for adverse pregnancy outcomes, such as pre-eclampsia, fetal growth restriction, and stillbirth, from database inception to August 2019. Data of four IPPIC cohorts (237 228 pregnancies) from the US (National Institute of Child Health and Human Development, 2018; 233 483 pregnancies), UK (Allen et al, 2017; 1045 pregnancies), Norway (STORK Groruddalen research programme, 2010; 823 pregnancies), and Australia (Rumbold et al, 2006; 1877 pregnancies) were included in the development of the model.

Results

The IPPIC birth weight model was developed with random intercept regression models with backward elimination for variable selection. Internal-external cross validation was performed to assess the study specific and pooled performance of the model, reported as calibration slope, calibration-in-the-large, and observed versus expected average birth weight ratio. Meta-analysis showed that the apparent performance of the model had good calibration (calibration slope 0.99, 95% confidence interval (CI) 0.88 to 1.10; calibration-in-the-large 44.5 g, -18.4 to 107.3) with an observed versus expected average birth weight ratio of 1.02 (95% CI 0.97 to 1.07). The proportion of variation in birth weight explained by the model (R2) was 46.9% (range 32.7-56.1% in each cohort). On internal-external cross validation, the model showed good calibration and predictive performance when validated in three cohorts with a calibration slope of 0.90 (Allen cohort), 1.04 (STORK Groruddalen cohort), and 1.07 (Rumbold cohort), calibration-in-the-large of -22.3 g (Allen cohort), -33.42 (Rumbold cohort), and 86.4 g (STORK Groruddalen cohort), and observed versus expected ratio of 0.99 (Rumbold cohort), 1.00 (Allen cohort), and 1.03 (STORK Groruddalen cohort); respective pooled estimates were 1.00 (95% CI 0.78 to 1.23; calibration slope), 9.7 g (-154.3 to 173.8; calibration-in-the-large), and 1.00 (0.94 to 1.07; observed v expected ratio). The model predictions were more accurate (smaller mean square error) in the lower end of predicted birth weight, which is important in informing clinical decision making.

Conclusions

The IPPIC birth weight model allowed birth weight predictions for a range of possible gestational ages. The model explained about 50% of individual variation in birth weights, was well calibrated (especially in babies at high risk of fetal growth restriction and its complications), and showed promising performance in four different populations included in the individual participant data meta-analysis. Further research to examine the generalisability of performance in other countries, settings, and subgroups is required.

Trial registration

PROSPERO CRD42019135045.

The Impact of Excluding Adverse Neonatal Outcomes on the Creation of Gestational Weight Gain Charts Among Women from Low- and Middle-income Countries with Normal and Overweight BMI

BACKGROUND

Existing gestational weight gain (GWG) charts vary considerably in their choice of exclusion/inclusion criteria, and it is unclear to what extent these criteria create differences in the charts' percentile values.

OBJECTIVES

We aimed to establish the impact of including/excluding pregnancies with adverse neonatal outcomes when constructing GWG charts.

METHODS

This is an individual participant data analysis from 31 studies from low- and middle-income countries. We created a dataset that included all participants and a dataset restricted to those with no adverse neonatal outcomes: preterm < 37 wk, small or large for gestational age, low birth weight < 2500 g, or macrosomia > 4000 g. Quantile regression models were used to create GWG curves from 9 to 40 wk, stratified by prepregnancy BMI, in each dataset.

RESULTS

The dataset without the exclusion criteria applied included 14,685 individuals with normal weight and 4831 with overweight. After removing adverse neonatal outcomes, 10,479 individuals with normal weight and 3466 individuals with overweight remained. GWG distributions at 13, 27, and 40 wk were virtually identical between the datasets with and without the exclusion criteria, except at 40 wk for normal weight and 27 wk for overweight. For the 10th and 90th percentiles, the differences between the estimated GWG were larger for overweight (∼1.5 kg) compared with normal weight (<1 kg). Removal of adverse neonatal outcomes had minimal impact on GWG trajectories of normal weight. For overweight, the percentiles estimated in the dataset without the criteria were slightly higher than those in the dataset with the criteria applied. Nevertheless, differences were <1 kg and virtually nonexistent at the end of pregnancy.

CONCLUSIONS

Removing pregnancies with adverse neonatal outcomes has little or no influence on the GWG trajectories of individuals with normal and overweight.

Selection of Standards for Sonographic Fetal Head Circumference by Use of z-Scores

OBJECTIVE

This study aimed to evaluate which of five established norms should be used for sonographic assessment of fetal head circumference (HC).

STUDY DESIGN

Cross-sectional study using pooled data from four maternal-fetal medicine practices. Inclusion criteria were singleton fetus, gestational age 220/7 to 396/7 weeks, biometry measured, and fetal cardiac activity present. Five norms of HC were studied: Jeanty et al, Hadlock et al, the INTERGROWTH-21st Project (IG-21st), the World Health Organization Fetal Growth Curves (WHO), and the National Institutes of Child Health and Human Development Fetal Growth Studies unified standard (NICHD-U). The fit of our HC measurements to each norm was assessed by these criteria: mean z-score close to 0, standard deviation (SD) of z close to 1, low Kolmogorov-Smirnov D-statistic, high Youden J-statistic, close to 10% of exams >90th percentile, close to 10% of exams <10th percentile, and close to 2.28% of exams >2 SD below the mean.

RESULTS

In 23,565 ultrasound exams, our HC measurements had the best fit to the WHO standard (mean z-score 0.10, SD of z = 1.01, D-statistic <0.01, J-statistic 0.83-0.94). The SD of the Jeanty reference was much larger than all the other norms and our measurements, resulting in underdiagnosis of abnormal HC. The means of the IG-21st and NICHD-U standards were smaller than the other norms and our measurements, resulting in underdiagnosis of small HC. The means of the Hadlock reference were larger than all the other norms and our measurements, resulting in overdiagnosis of small HC. Restricting the analysis to a low-risk subgroup of 4,423 exams without risk factors for large- or small-for-gestational age produced similar results.

CONCLUSION

The WHO standard is likely best for diagnosis of abnormal HC. The Jeanty (Chervenak) reference suggested by the Society for Maternal-Fetal Medicine had poor sensitivity for microcephaly screening.

KEY POINTS

· There are >30 norms for fetal HC.. · It is unknown which norm should be used.. · The WHO standard fits our data best.. · The Chervenak reference is not sensitive for microcephaly..

Selection of Standards for Sonographic Fetal Femur Length by Use of z-scores

OBJECTIVES

This study aimed to evaluate which of four established norms should be used for sonographic assessment of fetal femur length (FL).

STUDY DESIGN

Cross-sectional study using pooled data from four maternal-fetal medicine practices. Inclusion criteria were singleton fetus, gestational age (GA) 220/7 to 396/7 weeks, biometry measured, and fetal cardiac activity present. Four norms of FL were studied: Hadlock et al, the INTERGROWTH-21st Project (IG-21st), the World Health Organization Fetal Growth Curves (WHO), and the National Institutes of Child Health and Human Development Fetal Growth Studies, unified standard (NICHD-U). The fit of our FL measurements to each norm was assessed by these criteria: mean z-score close to 0, standard deviation (SD) of z close to 1, Kolmogorov-Smirnov D-statistic close to zero, Youden J-statistic close to 1, approximately 5% of exams <5th percentile, and approximately 5% of exams >95th percentile.

RESULTS

In 26,177 ultrasound exams, our FL measurements had the best fit to the WHO standard (mean z-score 0.15, SD of z 1.02, D-statistic <0.01, J-statistic 0.95, 3.4% of exams <5th percentile, 7.0% of exams >95th percentile). The mean of the IG-21st standard was smaller than the other norms and smaller than our measurements, resulting in underdiagnosis of short FL. The mean of the Hadlock reference was larger than the other norms and larger than our measurements, resulting in overdiagnosis of short FL. The SD of the NICHD-U standard was larger than the other norms and larger than our observations, resulting in underdiagnosis of both short and long FL. Restricting the analysis to a subgroup of 7,144 low-risk patients without risk factors for large- or small-for- GA produced similar results.

CONCLUSION

Of the norms studied, the WHO standard is likely best for diagnosis of abnormal FL.

KEY POINTS

· There are >30 norms for fetal FL.. · It is unknown which norm should be used.. · Our data fit the World Health Organization standard better than the other norms..

The impact of different growth charts on birthweight prediction: obstetrical ultrasound vs magnetic resonance imaging

BACKGROUND

The estimation of fetal weight by fetal magnetic resonance imaging is a simple and rapid method with a high sensitivity in predicting birthweight in comparison with ultrasound. Several national and international growth charts are currently in use, but there is substantial heterogeneity among these charts due to variations in the selected populations from which they were derived, in methodologies, and in statistical analysis of data.

OBJECTIVE

This study aimed to compare the performance of magnetic resonance imaging and ultrasound for the prediction of birthweight using 3 commonly used fetal growth charts: the INTERGROWTH-21st Project, World Health Organization, and Fetal Medicine Foundation charts.

STUDY DESIGN

Data derived from a prospective, single-center, blinded cohort study that compared the performance of magnetic resonance imaging and ultrasound between 36+0/7 and 36+6/7 weeks of gestation for the prediction of birthweight ≥95th percentile were reanalyzed. Estimated fetal weight was categorized as above or below the 5th, 10th, 90th, and 95th percentile according to the 3 growth charts. Birthweight was similarly categorized according to the birthweight standards of each chart. The performances of ultrasound and magnetic resonance imaging for the prediction of birthweight <5th, <10th, >90th, and >95th percentile using the different growth charts were compared. Data were analyzed with R software, version 4.1.2. The comparison of sensitivity and specificity was done using McNemar and exact binomial tests. P values <.05 were considered statistically significant.

RESULTS

A total of 2378 women were eligible for final analysis. Ultrasound and magnetic resonance imaging were performed at a median gestational age of 36+3/7 weeks, delivery occurred at a median gestational age of 39+3/7 weeks, and median birthweight was 3380 g. The incidences of birthweight <5th and <10th percentiles were highest with the Fetal Medicine Foundation chart and lowest with the INTERGROWTH-21st chart, whereas the incidences of birthweight >90th and >95th percentiles were lowest with the Fetal Medicine Foundation chart and highest with the INTERGROWTH-21st chart. The sensitivity of magnetic resonance imaging with an estimated fetal weight >95th percentile in the prediction of birthweight >95th percentile was significantly higher than that of ultrasound across the 3 growth charts; however, its specificity was slightly lower than that of ultrasound. In contrast, the sensitivity of magnetic resonance imaging with an estimated fetal weight <10th percentile for predicting birthweight <10th percentile was significantly lower than that of ultrasound in the INTERGROWTH-21st and Fetal Medicine Foundation charts, whereas the specificity and positive predictive value of magnetic resonance imaging were significantly higher than those of ultrasound for all 3 charts. Findings for the prediction of birthweight >90th percentile were close to those of birthweight >95th percentile, and findings for the prediction of birthweight <5th percentile were close to those of birthweight <10th percentile.

CONCLUSION

The sensitivity of magnetic resonance imaging is superior to that of ultrasound for the prediction of large for gestational age fetuses and inferior to that of ultrasound for the prediction of small for gestational age fetuses across the 3 different growth charts. The reverse is true for the specificity of magnetic resonance imaging in comparison with that of ultrasound.

Choice of standards for sonographic fetal abdominal circumference percentile

BACKGROUND

The diagnosis of abnormal fetal abdominal circumference is based on values >90th or <10th percentile. There are dozens of established norms that can be used to determine the percentile of a given abdominal circumference measurement, but there is no established method to determine which norms should be used.

OBJECTIVE

This study aimed to evaluate the applicability of 5 established abdominal circumference norms to our measurements and to determine which, if any, should be used for the diagnosis of abnormal fetal abdominal circumference.

STUDY DESIGN

Data were pooled from 6 maternal-fetal medicine practices to conduct a cross-sectional study. The inclusion criteria were a singleton fetus at 22.0 to 39.9 weeks of gestation with cardiac activity present, complete fetal biometry measured, and examination from 2019 or 2020. For patients with >1 eligible examination during the study period, a single examination was chosen at random for inclusion. Five norms of abdominal circumference were studied: the Hadlock formula, the World Health Organization Fetal Growth Curves, the International Fetal and Newborn Growth Consortium for the 21st-Century Project; and the National Institutes of Child Health and Human Development Fetal Growth Studies (fetuses of White patients and unified standard). Using formulas relating abdominal circumference to gestational age, we calculated the z scores of abdominal circumference (standard deviations from the mean), standard deviation of the z score, Kolmogorov-Smirnov D statistic, and relative mean squared error. The 5 norms were assessed for fit to our data based on 6 criteria: mean z score close to 0, standard deviation of the z score close to 1, low D statistic, low mean squared error, fraction of values >90th percentile close to 10%, and fraction of values <10th percentile close to 10%.

RESULTS

The inclusion criteria were met in 40,684 ultrasound examinations in 15,042 patients. Considering the 6 evaluation criteria, observed abdominal circumferences had the best fit to the World Health Organization standard (mean z score of 0.11±1.05, D statistic of 0.041, mean squared error of 0.84±1.46, 13% of examinations >90th percentile, and 7% of examinations <10th percentile). The Hadlock reference had an anomaly in its assumption of a constant standard deviation, resulting in the underdiagnosis of abnormal values at early gestational ages and overdiagnosis at late gestational ages. The International Fetal and Newborn Growth Consortium for the 21st-Century Project standard had a mean circumference smaller than all the other norms, resulting in the underdiagnosis of small circumferences and the overdiagnosis of large circumferences. Similar results were observed when restricting the analyses to a low-risk subgroup of 5487 examinations without identified risk factors for large for gestational age or small for gestational age.

CONCLUSION

The diagnosis of abnormal abdominal circumference depends on the norms used to define abdominal circumference percentiles. The World Health Organization standard had the best fit for our data.

Variation in Fetal Weight Percentile Estimates

OBJECTIVES

Weight percentiles are generally reported without any indication of error. This variation can lead a fetus being mistakenly classified erroneously as having intrauterine growth restriction (IUGR) or macrosomia. The goal of this study was to compare estimated weight percentiles with the actual observed weight percentile for each gestational age in a large cohort of fetuses being scanned in our institution.

METHODS

After IRB approval the radiology information system data base was retrospectively searched for all obstetrical US reports obtained during the late second and third trimesters from July 1, 2014, until July 1, 2020. Demographic information, fetal weight, and weight percentile information were obtained from these reports. Quantile-quantile plots were created for all gestational ages and all ethnicities.

RESULTS

Our study included 6259 ultrasounds in 4060 patients. Mean maternal age of the total group was 31.68 years (ranging 15-53 years). When all subjects were considered, the median values in our QQ plots approximated the line of identity. However, there was considerable variation for a given estimate, implying that estimated fetal weight percentiles are only very rough predictors of the actual percentile.

CONCLUSION

Estimated fetal weight percentiles are only very rough predictors of the actual percentile. We therefore suggest that estimates of the weight percentile should be reported along with an estimate of the expected variation. Recognition of variations in weight percentile should be considered in the greater clinical context, and could potentially prevent misdiagnosis of growth restriction and macrosomia as well as the subsequent overutilization of resources, unnecessary interventions, and maternal stress.

Birth weight for gestational age: standard growth charts for the Polish population

Introduction. Birth weight is one of the most important factors determining neonatal well-being. From an epidemiological viewpoint, a neonatal reference chart provides a picture of the health status of a population. Global customized growth charts seem to be the most practical in multicultural settings, allowing adjustment for ethnicity. However, regional charts might be a valuable contribution to reliable growth assessment. Our study aims to establish a reference tool for growth assessment and visualize the local potential, by creating standard charts based on the data from the tertiary center with the highest number of deliveries per year in Poland. Material and Methods. We retrospectively analysed  31,353 records from the electronic database of singleton births from a five-year period from a tertiary hospital in Poznań, Poland. We excluded pre-term deliveries and high-risk pregnancies basing on well-known factors influencing fetal growth, bringing the number of records to  21,379. The data were processed separately by gender (females n=10,312, 48.2% and males n=11,067, 51.8%). Percentiles were calculated for each week of gestational age. Means and standard deviations were determined. Results. Standard growth charts (including 3rd, 10th, 25th, 50th, 75th, 90th and 97th percentiles) are presented. Descriptive data of population distribution are shown. Conclusions. In conclusion, obtaining standard growth charts for mature newborns has created the opportunity for a more actual and adequate assessment of the Polish neonatal population. It should allow for the implementation of new standards in future research on perinatal care.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Comparison of the performance of estimated fetal weight charts for the detection of small- and large-for-gestational age newborns with adverse outcomes: a French population-based study

OBJECTIVE

To compare the performance of estimated fetal weight (EFW) charts at the third trimester ultrasound for detecting small- and large-for-gestational age (SGA/LGA) newborns with adverse outcomes.

DESIGN

Nationally representative observational study.

SETTING

French maternity units in 2016.

POPULATION

9940 singleton live births with an ultrasound between 30 and 35 weeks of gestation.

METHODS

We compared three prescriptive charts (INTERGROWTH-21st, World Health Organization (WHO), Eunice Kennedy Shriver National Institute of Child Health and Human Development [NICHD]), four descriptive charts (Hadlock, Fetal Medicine Foundation, two French charts) and a French customised growth model (Epopé).

MAIN OUTCOME MEASURES

SGA and LGA (birthweights <10th and >90th percentiles) associated with adverse outcomes (low Apgar score, delivery-room resuscitation, neonatal unit admission).

RESULTS

2.1% and 1.1% of infants had SGA and LGA and adverse outcomes, respectively. The sensitivity and specificity for detecting these infants with an EFW <10th and >90th percentile varied from 29-65% and 84-96% for descriptive charts versus 27-60% and 83-96% for prescriptive charts. WHO and French charts were closest to the EFW distribution, yielding a balance between sensitivity and specificity for SGA and LGA births. INTERGROWTH-21st and Epopé had low sensitivity for SGA with high sensitivity for LGA. Areas under the receiving operator characteristics curve ranged from 0.62 to 0.74, showing low to moderate predictive ability, and diagnostic odds ratios varied from 7 to 16.

CONCLUSION

Marked differences in the performance of descriptive as well as prescriptive EFW charts highlight the importance of evaluating them for their ability to detect high-risk fetuses.

TWEETABLE ABSTRACT

Choice of growth chart strongly affected identification of high-risk fetuses at the third trimester ultrasound.