2018
DOI: 10.1016/j.ekir.2018.02.001
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Association Between Newborn Metabolic Profiles and Pediatric Kidney Disease

Abstract: IntroductionMetabolomics offers considerable promise in early disease detection. We set out to test the hypothesis that routine newborn metabolic profiles at birth, obtained through screening for inborn errors of metabolism, would be associated with kidney disease and add incremental information to known clinical risk factors.MethodsWe conducted a population-level cohort study in Ontario, Canada, using metabolic profiles from 1,288,905 newborns from 2006 to 2015. The primary outcome was chronic kidney disease … Show more

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Cited by 13 publications
(10 citation statements)
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“…This explains our observation of attenuated CKD-3b Tyr/Cr levels. This is consistent with previous findings in adults and infants with CKD 7, 15. Moreover, in advanced CKD, gut microbiota metabolize Tyr into protein-bound p-Cresol, a phenolic compound and uremic toxin creating a further decline in Tyr, while Cr continues to rise 9 …”
Section: Discussionsupporting
confidence: 92%
“…This explains our observation of attenuated CKD-3b Tyr/Cr levels. This is consistent with previous findings in adults and infants with CKD 7, 15. Moreover, in advanced CKD, gut microbiota metabolize Tyr into protein-bound p-Cresol, a phenolic compound and uremic toxin creating a further decline in Tyr, while Cr continues to rise 9 …”
Section: Discussionsupporting
confidence: 92%
“…Unlike a recent study of early neonatal mortality among very preterm infants [4], our model was only modestly predictive of 6-month infant mortality (optimism-corrected c-statistic: 0.61). Although we have previously demonstrated varying degree to which newborn screening analytes can be used to identify infants at risk for neonatal sepsis (optimism-corrected c-statistic among term infants: 0.85) or pediatric chronic kidney disease (optimismcorrected c-statistic: 0.66) [3,11], the models for both of these specific morbidities performed better than that for mortality observed here. This discordance in predictive ability of our mortality model and our previous studies of specific morbidities may be due to inherent physiological heterogeneity of all-cause infant mortality during the first 6 months of life.…”
Section: Discussioncontrasting
confidence: 62%
“…Demographic and vital statistics information was obtained from the Ontario Registered Persons Database. Pregnancy and maternal health data were captured in the MOMBABYdataset that links administrative records of all mothers with a delivery and their newborns across Ontario [ 14 ]. Diagnostic and procedural information from all hospitalizations was determined using the Canadian Institute for Health Information (CIHI) Discharge Abstract Database (DAD).…”
Section: Methodsmentioning
confidence: 99%