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https://ahro.austin.org.au/austinjspui/handle/1/19395
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DC Field | Value | Language |
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dc.contributor.author | Nahavandi, Sofia | - |
dc.contributor.author | Seah, Jas-Mine | - |
dc.contributor.author | Shub, Alexis | - |
dc.contributor.author | Houlihan, Christine A | - |
dc.contributor.author | Ekinci, Elif I | - |
dc.date | 2018-07-31 | - |
dc.date.accessioned | 2018-09-17T01:47:04Z | - |
dc.date.available | 2018-09-17T01:47:04Z | - |
dc.date.issued | 2018-07-31 | - |
dc.identifier.citation | Frontiers in Endocrinology 2018; 9: 407 | en_US |
dc.identifier.issn | 1664-2392 | - |
dc.identifier.uri | https://ahro.austin.org.au/austinjspui/handle/1/19395 | - |
dc.description.abstract | 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. | en_US |
dc.language.iso | eng | - |
dc.subject | biomarkers | en_US |
dc.subject | birthweight | en_US |
dc.subject | diabetes | en_US |
dc.subject | macrosomia | en_US |
dc.subject | pregnancy | en_US |
dc.title | Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes. | en_US |
dc.type | Journal Article | en_US |
dc.identifier.journaltitle | Frontiers in Endocrinology | en_US |
dc.identifier.affiliation | Mercy Hospital for Women, Mercy Health, Heidelberg, Victoria, Australia | en_US |
dc.identifier.affiliation | Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia | en_US |
dc.identifier.affiliation | Endocrinology | en_US |
dc.identifier.doi | 10.3389/fendo.2018.00407 | en_US |
dc.type.content | Text | en_US |
dc.identifier.orcid | 0000-0003-2372-395X | en_US |
dc.identifier.pubmedid | 30108547 | - |
dc.type.austin | Journal Article | - |
dc.type.austin | Review | - |
local.name.researcher | Ekinci, Elif I | |
item.languageiso639-1 | en | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.openairetype | Journal Article | - |
crisitem.author.dept | Endocrinology | - |
crisitem.author.dept | Endocrinology | - |
crisitem.author.dept | Endocrinology | - |
Appears in Collections: | Journal articles |
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