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Using newborn screening analytes to identify cases of neonatal sepsis

Neonatal sepsis is associated with high mortality and morbidity, yet challenges with available diagnostic approaches can lead to delays in therapy. Our study assessed whether newborn screening analytes could be utilized to identify associations with neonatal sepsis. We linked a newborn screening reg...

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Autores principales: Fell, Deshayne B., Hawken, Steven, Wong, Coralie A., Wilson, Lindsay A., Murphy, Malia S. Q., Chakraborty, Pranesh, Lacaze-Masmonteil, Thierry, Potter, Beth K., Wilson, Kumanan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740154/
https://www.ncbi.nlm.nih.gov/pubmed/29269842
http://dx.doi.org/10.1038/s41598-017-18371-1
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author Fell, Deshayne B.
Hawken, Steven
Wong, Coralie A.
Wilson, Lindsay A.
Murphy, Malia S. Q.
Chakraborty, Pranesh
Lacaze-Masmonteil, Thierry
Potter, Beth K.
Wilson, Kumanan
author_facet Fell, Deshayne B.
Hawken, Steven
Wong, Coralie A.
Wilson, Lindsay A.
Murphy, Malia S. Q.
Chakraborty, Pranesh
Lacaze-Masmonteil, Thierry
Potter, Beth K.
Wilson, Kumanan
author_sort Fell, Deshayne B.
collection PubMed
description Neonatal sepsis is associated with high mortality and morbidity, yet challenges with available diagnostic approaches can lead to delays in therapy. Our study assessed whether newborn screening analytes could be utilized to identify associations with neonatal sepsis. We linked a newborn screening registry with health databases to identify cases of sepsis among infants born in Ontario from 2010–2015. Correlations between sepsis and screening analytes were examined within three gestational age groups (early preterm: <34 weeks; late preterm: 34–36 weeks; term: ≥37 weeks), using multivariable logistic regression models. We started with a model containing only clinical factors, then added groups of screening analytes. Among 793,128 infants, 4,794 were diagnosed with sepsis during the neonatal period. Clinical variables alone or in combination with hemoglobin values were not strongly predictive of neonatal sepsis among infants born at term or late preterm. However, model fit improved considerably after adding markers of thyroid and adrenal function, acyl-carnitines, and amino acids. Among infants born at early preterm gestation, neither clinical variables alone nor models incorporating screening analytes adequately predicted neonatal sepsis. The combination of clinical variables and newborn screening analytes may have utility in identifying term or late preterm infants at risk for neonatal sepsis.
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spelling pubmed-57401542018-01-03 Using newborn screening analytes to identify cases of neonatal sepsis Fell, Deshayne B. Hawken, Steven Wong, Coralie A. Wilson, Lindsay A. Murphy, Malia S. Q. Chakraborty, Pranesh Lacaze-Masmonteil, Thierry Potter, Beth K. Wilson, Kumanan Sci Rep Article Neonatal sepsis is associated with high mortality and morbidity, yet challenges with available diagnostic approaches can lead to delays in therapy. Our study assessed whether newborn screening analytes could be utilized to identify associations with neonatal sepsis. We linked a newborn screening registry with health databases to identify cases of sepsis among infants born in Ontario from 2010–2015. Correlations between sepsis and screening analytes were examined within three gestational age groups (early preterm: <34 weeks; late preterm: 34–36 weeks; term: ≥37 weeks), using multivariable logistic regression models. We started with a model containing only clinical factors, then added groups of screening analytes. Among 793,128 infants, 4,794 were diagnosed with sepsis during the neonatal period. Clinical variables alone or in combination with hemoglobin values were not strongly predictive of neonatal sepsis among infants born at term or late preterm. However, model fit improved considerably after adding markers of thyroid and adrenal function, acyl-carnitines, and amino acids. Among infants born at early preterm gestation, neither clinical variables alone nor models incorporating screening analytes adequately predicted neonatal sepsis. The combination of clinical variables and newborn screening analytes may have utility in identifying term or late preterm infants at risk for neonatal sepsis. Nature Publishing Group UK 2017-12-21 /pmc/articles/PMC5740154/ /pubmed/29269842 http://dx.doi.org/10.1038/s41598-017-18371-1 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Fell, Deshayne B.
Hawken, Steven
Wong, Coralie A.
Wilson, Lindsay A.
Murphy, Malia S. Q.
Chakraborty, Pranesh
Lacaze-Masmonteil, Thierry
Potter, Beth K.
Wilson, Kumanan
Using newborn screening analytes to identify cases of neonatal sepsis
title Using newborn screening analytes to identify cases of neonatal sepsis
title_full Using newborn screening analytes to identify cases of neonatal sepsis
title_fullStr Using newborn screening analytes to identify cases of neonatal sepsis
title_full_unstemmed Using newborn screening analytes to identify cases of neonatal sepsis
title_short Using newborn screening analytes to identify cases of neonatal sepsis
title_sort using newborn screening analytes to identify cases of neonatal sepsis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740154/
https://www.ncbi.nlm.nih.gov/pubmed/29269842
http://dx.doi.org/10.1038/s41598-017-18371-1
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