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Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes

Large birthweight, or macrosomia, is one of the commonest complications for pregnancies affected by diabetes. As macrosomia is associated with an increased risk of a number of adverse outcomes for both the mother and offspring, accurate antenatal prediction of fetal macrosomia could be beneficial in...

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Autores principales: Nahavandi, Sofia, Seah, Jas-mine, Shub, Alexis, Houlihan, Christine, Ekinci, Elif I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6079223/
https://www.ncbi.nlm.nih.gov/pubmed/30108547
http://dx.doi.org/10.3389/fendo.2018.00407
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author Nahavandi, Sofia
Seah, Jas-mine
Shub, Alexis
Houlihan, Christine
Ekinci, Elif I.
author_facet Nahavandi, Sofia
Seah, Jas-mine
Shub, Alexis
Houlihan, Christine
Ekinci, Elif I.
author_sort Nahavandi, Sofia
collection PubMed
description Large birthweight, or macrosomia, is one of the commonest complications for pregnancies affected by diabetes. As macrosomia is associated with an increased risk of a number of adverse outcomes for both the mother and offspring, accurate antenatal prediction of fetal macrosomia could be beneficial in guiding appropriate models of care and interventions that may avoid or reduce these associated risks. However, current prediction strategies which include physical examination and ultrasound assessment, are imprecise. Biomarkers are proving useful in various specialties and may offer a new avenue for improved prediction of macrosomia. Prime biomarker candidates in pregnancies with diabetes include maternal glycaemic markers (glucose, 1,5-anhydroglucitol, glycosylated hemoglobin) and hormones proposed implicated in placental nutrient transfer (adiponectin and insulin-like growth factor-1). There is some support for an association of these biomarkers with birthweight and/or macrosomia, although current evidence in this emerging field is still limited. Thus, although biomarkers hold promise, further investigation is needed to elucidate the potential clinical utility of biomarkers for macrosomia prediction for pregnancies affected by diabetes.
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spelling pubmed-60792232018-08-14 Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes Nahavandi, Sofia Seah, Jas-mine Shub, Alexis Houlihan, Christine Ekinci, Elif I. Front Endocrinol (Lausanne) Endocrinology Large birthweight, or macrosomia, is one of the commonest complications for pregnancies affected by diabetes. As macrosomia is associated with an increased risk of a number of adverse outcomes for both the mother and offspring, accurate antenatal prediction of fetal macrosomia could be beneficial in guiding appropriate models of care and interventions that may avoid or reduce these associated risks. However, current prediction strategies which include physical examination and ultrasound assessment, are imprecise. Biomarkers are proving useful in various specialties and may offer a new avenue for improved prediction of macrosomia. Prime biomarker candidates in pregnancies with diabetes include maternal glycaemic markers (glucose, 1,5-anhydroglucitol, glycosylated hemoglobin) and hormones proposed implicated in placental nutrient transfer (adiponectin and insulin-like growth factor-1). There is some support for an association of these biomarkers with birthweight and/or macrosomia, although current evidence in this emerging field is still limited. Thus, although biomarkers hold promise, further investigation is needed to elucidate the potential clinical utility of biomarkers for macrosomia prediction for pregnancies affected by diabetes. Frontiers Media S.A. 2018-07-31 /pmc/articles/PMC6079223/ /pubmed/30108547 http://dx.doi.org/10.3389/fendo.2018.00407 Text en Copyright © 2018 Nahavandi, Seah, Shub, Houlihan and Ekinci. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Nahavandi, Sofia
Seah, Jas-mine
Shub, Alexis
Houlihan, Christine
Ekinci, Elif I.
Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes
title Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes
title_full Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes
title_fullStr Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes
title_full_unstemmed Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes
title_short Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes
title_sort biomarkers for macrosomia prediction in pregnancies affected by diabetes
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6079223/
https://www.ncbi.nlm.nih.gov/pubmed/30108547
http://dx.doi.org/10.3389/fendo.2018.00407
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