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Systemic inflammation in the extremely low gestational age newborn following maternal genitourinary infections.


ABSTRACT: Gestational genitourinary infections are associated with lifelong disabilities, but it is unknown if neonatal inflammation is involved.Mothers of 914 infants born before 28th gestation week reported cervical/vaginal infection (CVI), and/or urine/bladder/kidney infection (UTI), or neither. Inflammation proteins measured in baby's blood on postnatal days 1, 7, and 14 were considered elevated if in the top quartile for gestational age. Logistic regression models adjusting for potential confounders assessed odds ratios.Compared to mothers with neither UTI/CVI, those with CVI were more likely to have infants with elevated CRP, SAA, MPO, IL-1?, IL-6, IL-6R, TNF-?, RANTES, ICAM-3, E-selectin, and VEGF-R2 on day 1; those with UTI were more likely to have infants with elevated MPO, IL-6R, TNF-R1, TNF-R2, and RANTES on day 7. Placental anaerobes and genital mycoplasma were more common in pregnancies with CVI.Gestational UTI/CVI should be targeted for preventing systemic inflammation in the very preterm newborn.

SUBMITTER: Fichorova RN 

PROVIDER: S-EPMC4293273 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Systemic inflammation in the extremely low gestational age newborn following maternal genitourinary infections.

Fichorova Raina N RN   Beatty Noah N   Sassi Rita R S RR   Yamamoto Hidemi S HS   Allred Elizabeth N EN   Leviton Alan A  

American journal of reproductive immunology (New York, N.Y. : 1989) 20140828 2


<h4>Problem</h4>Gestational genitourinary infections are associated with lifelong disabilities, but it is unknown if neonatal inflammation is involved.<h4>Method</h4>Mothers of 914 infants born before 28th gestation week reported cervical/vaginal infection (CVI), and/or urine/bladder/kidney infection (UTI), or neither. Inflammation proteins measured in baby's blood on postnatal days 1, 7, and 14 were considered elevated if in the top quartile for gestational age. Logistic regression models adjus  ...[more]

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