Population versus Customized Growth Curves: Prediction of Composite Neonatal Morbidity.

Objective: To assess the ability of customized and population growth nomograms in identifying newborns with composite neonatal morbidity (CNM).

Study Design: This study included women who participated in the 10 Maternal-Fetal Medicine Units (MFMU) trials and delivered a nonanomalous singleton with a known gestational age (GA) of 24 weeks or more and documented birthweight. Population nomograms were based on Alexander's nomogram, whereas customized nomograms used publicly available softwares. Random-effect logistic regression was used to estimate the adjusted odds ratio (aOR). Positive and negative likelihood ratios (LRs) were calculated to assess nomogram performance.

Results: Of 92,225 women, 85% met the inclusion criteria. Using the population nomogram, 12% were small for gestational age (SGA) and 10% were large for gestational age (LGA), and using customized nomograms, 15% were SGA and 16% LGA. SGA newborns had a higher likelihood of CNM (aOR: 2.62; 95% confidence interval [CI]: 2.48-2.76) for population nomograms and 3.22 (95% CI: 3.07-3.39) for customized nomograms. LGA newborns had a similar CNM with population nomogram but significantly higher with customized nomogram (aOR: 1.42; 95% CI: 1.34-1.50). For the adverse outcomes among SGA and LGA, the positive LRs for the two nomograms were similar with overlapping 95% CI.

Conclusion: Though both SGA and LGA are associated with adverse perinatal outcomes, the detection using both nomograms was similar.