The clinical performance and population health impact of birthweight-for-gestational age indices at term gestation.

Abstract

The assessment of birthweight for gestational age and the identification of small- and large-for-gestational age (SGA and LGA) infants remain contentious, despite the recent creation of the Intergrowth 21st Project and World Health Organisation (WHO) birthweight-for-gestational age standards. We carried out a study to identify birthweight-for-gestational age cut-offs, and corresponding population-based, Intergrowth 21st and WHO centiles associated with higher risks of adverse neonatal outcomes, and to evaluate their ability to predict serious neonatal morbidity and neonatal mortality (SNMM) at term gestation. The study population was based on non-anomalous, singleton live births between 37 and 41 weeks' gestation in the United States from 2003 to 2017. SNMM included 5-min Apgar score <4, neonatal seizures, need for assisted ventilation, and neonatal death. Birthweight-specific SNMM was modelled by gestational week using penalised B-splines. The birthweights at which SNMM odds were minimised (and higher by 10%, 50% and 100%) were estimated,and the corresponding population, Intergrowth 21st, and WHO centiles were identified. The clinical performance and population impact of these cut-offs for predicting SNMM were evaluated. The study included 40,179,663 live births and 991,486 SNMM cases. Among female singletons at 39 weeks' gestation, SNMM odds was lowest at 3203 g birthweight, and 10% higher at 2835 g and 3685 g (population centiles 11th and 82nd, Intergrowth centiles 17th and 88th and WHO centiles 15th and 85th). Birthweight cut-offs were poor predictors of SNMM, for example, the cut-offs associated with 10% and 50% higher odds of SNMM among female singletons at 39 weeks' gestation resulted in a sensitivity, specificity, and population attributable fraction of 12.5%, 89.4%, and 2.1%, and 2.9%, 98.4% and 1.3%, respectively. Reference- and standard-based birthweight-for-gestational age indices and centiles perform poorly for predicting adverse neonatal outcomes in individual infants, and their associated population impact is also small.