An application of group-based trajectory modeling to define fetal growth phenotypes among small-for-gestational-age births in the LIFECODES Fetal Growth Study

Abstract

Reductions in fetal growth are associated with adverse outcomes at birth and later in life. However, identifying fetuses with pathologically small growth remains challenging. Definitions of small-for-gestational age are often used as a proxy to identify those experiencing pathologic growth (ie, fetal growth restriction). However, this approach is subject to limitation as most newborns labeled small-for-gestational age are constitutionally, not pathologically, small. Incorporating repeated ultrasound measures to examine fetal growth trajectories may help distinguish pathologic deviations in growth from normal variability, beyond a simple definition of small-for-gestational age. This study aimed to characterize phenotypes of growth using ultrasound trajectories of fetal growth among small-for-gestational-age births. This study identified and described trajectories of fetal growth among small-for-gestational-age births (<10th percentile weight for gestational age; n=245) in the LIFECODES Fetal Growth Study using univariate and multivariate trajectory modeling approaches. Available ultrasound measures of fetal growth (estimated fetal weight, head circumference, abdominal circumference, and femur length) from health records were abstracted. First, univariate group-based trajectory modeling was used to define trajectories of estimated fetal weight z scores during gestation. Second, group-based multi-trajectory modeling was used to identify trajectories based on concurrent measures of head circumference, abdominal circumference, and femur length z scores. Last, how these trajectories were related to patient demographics, pregnancy characteristics, and birth outcomes compared with those observed among appropriate-for-gestational-age controls was described. Of note, 3 univariate trajectories of estimated fetal weight and 4 multivariate trajectories of fetal growth among small-for-gestational-age births were identified. In our univariate approach, infants with the smallest estimated fetal weight trajectory throughout pregnancy had poorer outcomes, including the highest risk of neonatal intensive care unit admission. The remaining univariate trajectory groups did not have an elevated risk of adverse birth outcomes relative to appropriate-for-gestational-age controls. In our multivariate approach, 2 groups at increased or moderately increased risk of neonatal intensive care unit admission were identified, including infants that remained extremely small for all parameters throughout pregnancy and those who had disproportionately smaller femur length and abdominal circumference compared with head circumference. The remaining multivariate trajectory groups did not have an elevated risk of adverse birth outcome relative to appropriate-for-gestational-age controls. Latent class group-based trajectory modeling applied to ultrasound measures of fetal growth may help distinguish pathologic vs constitutional growth profiles among newborns born small-for-gestational age. Although trajectories cannot be fully characterized until delivery, limiting the direct clinical application of these methods, they may still contribute to the development of approaches for separating growth restriction from constitutional smallness.