4.6 Article

Newborn metabolic vulnerability profile identifies preterm infants at risk for mortality and morbidity

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PEDIATRIC RESEARCH
卷 89, 期 6, 页码 1405-1413

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SPRINGERNATURE
DOI: 10.1038/s41390-020-01148-0

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  1. California Preterm Birth Initiative within the University of California, San Francisco (UCSF)

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The study demonstrated that metabolites from routine newborn screening can be used to create a metabolic vulnerability profile to evaluate the risk of neonatal mortality and major morbidity in preterm infants. The model showed exceptional performance for predicting mortality or major morbidity outcomes, and could potentially improve clinical monitoring and research into biological pathways associated with preterm birth complications.
Background Identifying preterm infants at risk for mortality or major morbidity traditionally relies on gestational age, birth weight, and other clinical characteristics that offer underwhelming utility. We sought to determine whether a newborn metabolic vulnerability profile at birth can be used to evaluate risk for neonatal mortality and major morbidity in preterm infants. Methods This was a population-based retrospective cohort study of preterm infants born between 2005 and 2011 in California. We created a newborn metabolic vulnerability profile wherein maternal/infant characteristics along with routine newborn screening metabolites were evaluated for their association with neonatal mortality or major morbidity. Results Nine thousand six hundred and thirty-nine (9.2%) preterm infants experienced mortality or at least one complication. Six characteristics and 19 metabolites were included in the final metabolic vulnerability model. The model demonstrated exceptional performance for the composite outcome of mortality or any major morbidity (AUC 0.923 (95% CI: 0.917-0.929). Performance was maintained across mortality and morbidity subgroups (AUCs 0.893-0.979). Conclusions Metabolites measured as part of routine newborn screening can be used to create a metabolic vulnerability profile. These findings lay the foundation for targeted clinical monitoring and further investigation of biological pathways that may increase the risk of neonatal death or major complications in infants born preterm. Impact We built a newborn metabolic vulnerability profile that could identify preterm infants at risk for major morbidity and mortality. Identifying high-risk infants by this method is novel to the field and outperforms models currently in use that rely primarily on infant characteristics. Utilizing the newborn metabolic vulnerability profile for precision clinical monitoring and targeted investigation of etiologic pathways could lead to reductions in the incidence and severity of major morbidities associated with preterm birth.

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