Fetal growth and gestational age improve outcome predictions in neonatal heart surgery.

Objective: Current risk adjustment models for congenital heart surgery do not fully incorporate multiple factors unique to neonates such as granular gestational age (GA) and birth weight (BW) z score data. This study sought to develop a Neonatal Risk Adjustment Model for congenital heart surgery to address these deficiencies.

Methods: Cohort study of neonates undergoing cardiothoracic surgery during the neonatal period captured in the Pediatric Cardiac Critical Care Consortium database between 2014 and 2020. Candidate predictors were included in the model if they were associated with mortality in the univariate analyses. GA and BW z score were both added as multicategory variables. Mortality probabilities were predicted for different GA and BW z scores while keeping all other variables at their mean value.

Results: The C statistic for the mortality model was 0.8097 (95% confidence interval, 0.7942-0.8255) with excellent calibration. Mortality prediction for a neonate at 40 weeks GA and a BW z score 0 to 1 was 3.5% versus 9.8% for the same neonate at 37 weeks GA and a BW z score -2 to -1. For preterm infants the mortality prediction at 34 to 36 weeks with a BW z score 0 to 1 was 10.6%, whereas it was 36.1% for the same infant at <32 weeks with a BW z score of -2 to -1.

Conclusions: This Neonatal Risk Adjustment Model incorporates more granular data on GA and adds the novel risk factor BW z score. These 2 factors refine mortality predictions compared with traditional risk models. It may be used to compare outcomes across centers for the neonatal population.