Background
Standards for fetal weight are typically derived from birth weights of neonates born at different gestational ages [
1,
2]. However, births at early gestations are frequently affected by pathologies that restrict growth [
3‐
5]. Therefore standards of growth derived from birth weights will tend to under-estimate the weight of unborn fetuses of the same gestation, thereby under-estimating the degree of growth restriction in infants born preterm [
6]. Such situations may lead to inappropriate counselling and planning for preterm delivery [
6]. This dilemma is insurmountable by studies considering only birth weight since if preterm births were excluded no estimate of growth would be available at early gestational ages.
Optimal weight may be interpreted as a result of growth achieved in the absence of any factors that pathologically affect growth. We have previously reported a method of assessing the appropriateness of fetal growth using the proportion of optimal birth weight [
7]. With that approach the measure of growth was the ratio of the observed birth weight to the estimated optimal birth weight given the neonate’s non-pathologic determinants of growth. In that study ‘optimal’ weight was defined as the weight achieved by neonatal survivors not exposed to any of the exposures associated with intrauterine growth anomaly commonly occurring in our population; namely: maternal smoking, vascular disease, diabetes (pre-existing or gestational), TORCH infections (toxoplasmosis, rubella, CMV, herpes) in pregnancy, multiple pregnancy and birth defects in the fetus. Gestation of delivery was not a criterion for optimal growth. As anticipated, a far greater proportion of preterm births were excluded by these criteria than were term births, but we had no compelling reason for excluding other preterm births on the grounds of growth anomaly, despite their preterm birth suggesting experience of suboptimal exposures. However the assumption that neonatally surviving preterm births not exposed to common causes of growth anomaly are optimally grown was untested.
The aim of this study was to validate a model for optimal birth weight derived from neonatal records, and to query the assumption that preterm births may be considered optimally grown if they are not exposed to common factors that perturb fetal growth.
Discussion
Our study made use of a large prospectively collected sample of serial ultrasounds to derive an estimate of the optimal fetal weight and thereby also a method to ascertain the adequacy of fetal growth. We adopted a multi-faceted approach: weight was derived from ultrasound scans taken at multiple occasions during pregnancy and supplemented with weight measured at the time of birth, rather than sole reliance on birth weights and we excluded fetuses subsequently (i) born preterm, (ii) that died before 28 days of life, or (iii) that experienced pathologies affecting growth. We found that estimates of optimal weight based on a population of birth weights also subject to exclusions (ii) and (iii) but not (i) were systematically lower than fetal weight estimated using biometric ultrasounds prior to 30 weeks gestation.
It is plausible that the difference between OW
US and OW
BW (Figure
2, Figure
3) suggests an increasing proportion of unusual causes of growth restriction with decreasing gestation of delivery before 28 to 30 weeks gestation, but very few such causes of growth restriction for births after 30 weeks. We re-examined those in the original cohort used to derive OW
BW that were born at or before 28 weeks gestation (N = 101). Among this group, the recorded antepartum factors that might have contributed to growth restriction but were not excluded as common causes of growth restriction were: threatened abortion (antepartum haemorrhage before 30 weeks gestation), N = 13; urinary tract infection, N = 2; antepartum haemorrhage (not attributed to placenta previa or abruption), N = 39; asthma, N = 12; genital tract infection, N = 9; vaginitis, N = 4; significant psychological morbidity, N = 11; anaemia, N = 5; neoplasms, N = 7. Approximately 63% of this cohort experienced at least one of these factors. Among all term neonates in Western Australia, the prevalence of asthma was 9.7% and neoplasms (cervical cancer and cervical dysplasia) was 0.02%, which were both lower than the prevalence in this cohort. Further studies are required to confirm whether maternal asthma, cervical cancers and depression are disproportionately stronger risk factors for growth restriction at such early gestations in other populations. It remains to be demonstrated that preterm births, particularly very preterm births, can be considered optimally grown if they are not exposed to common factors that perturb fetal growth.
Although it is plausible that there is an increasing proportion of unusual causes of growth restriction with decreasing gestation of delivery before 28 to 30 weeks gestation, there are other explanations for the findings. Radiographers may have systematically over or under-estimated fetal biometric measurements. However, the measurements were taken by a limited number of experienced radiographers at a tertiary obstetric hospital. While both Hadlock’s and Scott’s models were selected because they performed favourably compared to alternative formulae, it is possible that both of these methods used to estimate fetal weight from ultrasound measurements systematically over-estimated true fetal weight in our study. Few ultrasound scans were taken within a week of birth among early low-risk preterm births before 28 weeks gestation. This meant that a formal validation of the model used to estimate fetal weight from ultrasound measurements could not be conducted. However, we confirmed that results were not sensitive to the choice of Hadlock’s versus Scott’s method to estimate fetal weight from ultrasound measurements. Before 27 weeks gestation, Scott’s method and Hadlock’s method to estimate fetal weight from ultrasound measurements differed by only 10 g, whereas the difference between estimates obtained from Scott’s method and the model for optimal weight derived from birth weight measurements was almost 200 g.
A further alternative explanation for the findings of this study is that the model developed using a combination of fetal weights derived from ultrasound scans and birth weights fits the data better at earlier gestations than the published model derived from birth weights due to the small number of births at early gestations. The model for OW
BW was developed predominantly on a sample of births from 33 weeks gestation whereas the model for OW
US was based on measurements from ultrasounds that start typically from much earlier gestations (Table
2). Therefore, the model for OW
US is recommended for the estimation of fetal weight instead of OW
BW, particularly before 30 weeks gestation.
Our results support the overall findings of Salomon et al (2007) who reported that the median of the fetal weight distribution provided an upper bound for the median of the birth weight distribution between 25 and 35 weeks of gestation [
6]. However, their inclusion of individuals subsequently born pre-term, those exposed to maternal smoking during pregnancy, and those with known growth restricting pathologies would have deflated the true discrepancy. Not accounting for known non-pathological determinants of growth such as birth order and maternal stature would have introduced further error. Moreover, the proportional difference between the two approaches may be of greater interest than the absolute difference as it is a measure of difference relative to the fetal size. Our results indicate that the proportional deviation of OW
BW from OW
US was statistically significant prior to 28 weeks gestation, after accounting for individualised growth potential and excluding those with diagnosed growth restriction or known growth restricting pathologies. From 30 weeks of completed gestation the estimates of fetal weight based on a population of birth weights not exposed to common causes of growth anomaly yielded similar estimates of optimal weight.
The methodology that we applied differs from those suggested by others in that centiles and z-scores were not produced [
14]. However, the aim of our study was to compute and compare the mean optimal fetal weight derived from both ultrasounds and neonatal measurements to that derived from only birth weights, rather than produce reference charts and compare the entire distributions. Nonetheless, we responded to the recommendations of Altman et al (1994) as we fully accounted for the non-constant variance of the residuals with increasing gestational age [
15]. Albeit small in magnitude, the temporal autocorrelation among the fetal weights was statistically significant after accounting for gestational age, birth order, infant sex and maternal height. Therefore, past studies that ignored the temporal autocorrelation violated this requirement for regression. A limitation of our approach is the increased complexity of modelling the error variance. A further limitation of our study was that the exclusion criteria restricted the sample size from 9,222 scans to 2,848 scans. However, this meant that the expected optimal fetal weight estimates were less likely to be influenced by individuals with pathologically affected growth. The prospective design also allowed the retention of multiple scans per individual despite these exclusions.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
GP participated in the design of the study, performed the statistical analysis, and wrote the initial manuscript and later revisions. EB conceived the study, participated in its design and helped to draft and revise the manuscript. DL participated in the design of the study and helped to revise the manuscript. All authors read and approved the final manuscript.