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Metabolic gestational age assessment in low resource settings: a validation protocol

Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings...

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Autores principales: Bota, A. Brianne, Ward, Victoria, Hawken, Stephen, Wilson, Lindsay A., Lamoureux, Monica, Ducharme, Robin, Murphy, Malia S. Q., Denize, Kathryn M., Henderson, Matthew, Saha, Samir K., Akther, Salma, Otieno, Nancy A., Munga, Stephen, Atito, Raphael O., Stringer, Jeffrey S. A., Mwape, Humphrey, Price, Joan T., Mujuru, Hilda Angela, Chimhini, Gwendoline, Magwali, Thulani, Mudawarima, Louisa, Chakraborty, Pranesh, Darmstadt, Gary L., Wilson, Kumanan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801859/
https://www.ncbi.nlm.nih.gov/pubmed/33501414
http://dx.doi.org/10.12688/gatesopenres.13155.2
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author Bota, A. Brianne
Ward, Victoria
Hawken, Stephen
Wilson, Lindsay A.
Lamoureux, Monica
Ducharme, Robin
Murphy, Malia S. Q.
Denize, Kathryn M.
Henderson, Matthew
Saha, Samir K.
Akther, Salma
Otieno, Nancy A.
Munga, Stephen
Atito, Raphael O.
Stringer, Jeffrey S. A.
Mwape, Humphrey
Price, Joan T.
Mujuru, Hilda Angela
Chimhini, Gwendoline
Magwali, Thulani
Mudawarima, Louisa
Chakraborty, Pranesh
Darmstadt, Gary L.
Wilson, Kumanan
author_facet Bota, A. Brianne
Ward, Victoria
Hawken, Stephen
Wilson, Lindsay A.
Lamoureux, Monica
Ducharme, Robin
Murphy, Malia S. Q.
Denize, Kathryn M.
Henderson, Matthew
Saha, Samir K.
Akther, Salma
Otieno, Nancy A.
Munga, Stephen
Atito, Raphael O.
Stringer, Jeffrey S. A.
Mwape, Humphrey
Price, Joan T.
Mujuru, Hilda Angela
Chimhini, Gwendoline
Magwali, Thulani
Mudawarima, Louisa
Chakraborty, Pranesh
Darmstadt, Gary L.
Wilson, Kumanan
author_sort Bota, A. Brianne
collection PubMed
description Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings can be challenging, particularly in places where access to ultrasound is limited. Our group has developed an algorithm using newborn screening analyte values derived from dried blood spots from newborns born in Ontario, Canada for estimating gestational age within one to two weeks. The primary objective of this study is to validate a program that derives gestational age estimates from dried blood spot samples (heel-prick or cord blood) collected from health and demographic surveillance sites and population representative health facilities in low-resource settings in Zambia, Kenya, Bangladesh and Zimbabwe. We will also pilot the use of an algorithm to identify birth percentiles based on gestational age estimates and weight to identify small for gestational age infants. Once collected from local sites, samples will be tested by the Newborn Screening Ontario laboratory at the Children’s Hospital of Eastern Ontario (CHEO) in Ottawa, Canada. Analyte values will be obtained through laboratory analysis for estimation of gestational age as well as screening for other diseases routinely conducted at Ontario’s newborn screening program. For select conditions, abnormal screening results will be reported back to the sites in real time to facilitate counseling and future clinical management. We will determine the accuracy of our existing algorithm for estimation of gestational age in these newborn samples. Results from this research hold the potential to create a feasible method to assess gestational age at birth in low- and middle-income countries where reliable estimation may be otherwise unavailable.
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spelling pubmed-78018592021-01-25 Metabolic gestational age assessment in low resource settings: a validation protocol Bota, A. Brianne Ward, Victoria Hawken, Stephen Wilson, Lindsay A. Lamoureux, Monica Ducharme, Robin Murphy, Malia S. Q. Denize, Kathryn M. Henderson, Matthew Saha, Samir K. Akther, Salma Otieno, Nancy A. Munga, Stephen Atito, Raphael O. Stringer, Jeffrey S. A. Mwape, Humphrey Price, Joan T. Mujuru, Hilda Angela Chimhini, Gwendoline Magwali, Thulani Mudawarima, Louisa Chakraborty, Pranesh Darmstadt, Gary L. Wilson, Kumanan Gates Open Res Study Protocol Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings can be challenging, particularly in places where access to ultrasound is limited. Our group has developed an algorithm using newborn screening analyte values derived from dried blood spots from newborns born in Ontario, Canada for estimating gestational age within one to two weeks. The primary objective of this study is to validate a program that derives gestational age estimates from dried blood spot samples (heel-prick or cord blood) collected from health and demographic surveillance sites and population representative health facilities in low-resource settings in Zambia, Kenya, Bangladesh and Zimbabwe. We will also pilot the use of an algorithm to identify birth percentiles based on gestational age estimates and weight to identify small for gestational age infants. Once collected from local sites, samples will be tested by the Newborn Screening Ontario laboratory at the Children’s Hospital of Eastern Ontario (CHEO) in Ottawa, Canada. Analyte values will be obtained through laboratory analysis for estimation of gestational age as well as screening for other diseases routinely conducted at Ontario’s newborn screening program. For select conditions, abnormal screening results will be reported back to the sites in real time to facilitate counseling and future clinical management. We will determine the accuracy of our existing algorithm for estimation of gestational age in these newborn samples. Results from this research hold the potential to create a feasible method to assess gestational age at birth in low- and middle-income countries where reliable estimation may be otherwise unavailable. F1000 Research Limited 2021-01-28 /pmc/articles/PMC7801859/ /pubmed/33501414 http://dx.doi.org/10.12688/gatesopenres.13155.2 Text en Copyright: © 2021 Bota AB et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Study Protocol
Bota, A. Brianne
Ward, Victoria
Hawken, Stephen
Wilson, Lindsay A.
Lamoureux, Monica
Ducharme, Robin
Murphy, Malia S. Q.
Denize, Kathryn M.
Henderson, Matthew
Saha, Samir K.
Akther, Salma
Otieno, Nancy A.
Munga, Stephen
Atito, Raphael O.
Stringer, Jeffrey S. A.
Mwape, Humphrey
Price, Joan T.
Mujuru, Hilda Angela
Chimhini, Gwendoline
Magwali, Thulani
Mudawarima, Louisa
Chakraborty, Pranesh
Darmstadt, Gary L.
Wilson, Kumanan
Metabolic gestational age assessment in low resource settings: a validation protocol
title Metabolic gestational age assessment in low resource settings: a validation protocol
title_full Metabolic gestational age assessment in low resource settings: a validation protocol
title_fullStr Metabolic gestational age assessment in low resource settings: a validation protocol
title_full_unstemmed Metabolic gestational age assessment in low resource settings: a validation protocol
title_short Metabolic gestational age assessment in low resource settings: a validation protocol
title_sort metabolic gestational age assessment in low resource settings: a validation protocol
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801859/
https://www.ncbi.nlm.nih.gov/pubmed/33501414
http://dx.doi.org/10.12688/gatesopenres.13155.2
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