Cargando…
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...
Autores principales: | , , , , |
---|---|
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 |
_version_ | 1783345226648125440 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6079223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT nahavandisofia biomarkersformacrosomiapredictioninpregnanciesaffectedbydiabetes AT seahjasmine biomarkersformacrosomiapredictioninpregnanciesaffectedbydiabetes AT shubalexis biomarkersformacrosomiapredictioninpregnanciesaffectedbydiabetes AT houlihanchristine biomarkersformacrosomiapredictioninpregnanciesaffectedbydiabetes AT ekincielifi biomarkersformacrosomiapredictioninpregnanciesaffectedbydiabetes |