| Which growth criteria better predict fetal programming? | |
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MedLine Citation:
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PMID: 21444299 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Objective To test whether customised (ct) growth criteria are more reliable than standard (st) ones to predict intrauterine insult. Patients 32 mothers and their singleton term neonates selected as small for gestational age (st-SGA=8) or appropriate for gestational age (st-AGA=24). Main outcome measures Nitric oxide, high-sensitive C reactive protein (hs-CRP), uric acid, blood lipids and protein levels were analysed in maternal and cord blood. Results Applying customised criteria yielded 16 ct-AGA, 13 ct-SGA and 3 ct-LGA (large for gestational age) babies. Both st-SGA and ct-SGA babies had higher nitric oxide and hs-CRP levels. Their mothers had lower albumin fractions. st-SGA babies also had higher triglyceride and cholesterol levels. ct-LGA babies and mothers had higher uric acid levels, and the mothers had higher triglyceride levels. Conclusions Customised growth criteria better identify babies submitted to unfavourable intrauterine environments. The authors suggest that combined with maternal biochemistry, these growth criteria can be used to screen for adverse fetal programming. |
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Authors:
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Sandra S Mattos; Maria Elizabeth C Chaves; Suzana Maria Ramos Costa; Ana Catarina Matos Ishigami; Sarah Bezerra Rêgo; Vinicius Souto Maior; Rossana Severi; José Luiz de Lima Filho |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-3-27 |
Journal Detail:
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Title: Archives of disease in childhood. Fetal and neonatal edition Volume: - ISSN: 1468-2052 ISO Abbreviation: - Publication Date: 2011 Mar |
Date Detail:
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Created Date: 2011-3-29 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9501297 Medline TA: Arch Dis Child Fetal Neonatal Ed Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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1Laboratório de Imunopatologia Keizo-Asami-LIKA, Universidade Federal de Pernambuco-UFPE, Recife, Brazil. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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