%0 Journal Article
%J Am J Reprod Immunol
%D 2016
%T Mathematical Modeling of the Biomarker Milieu to Characterize Preterm Birth and Predict Adverse Neonatal Outcomes
%A Cordeiro, C. N.
%A Savva, Y.
%A Vaidya, D.
%A Argani, C. H.
%A Hong, X.
%A Wang, X.
%A Burd, I.
%K cytokines
%K mathematical model
%K neonatal brain injury
%K neonatal sepsis
%K preterm birth
%X PROBLEM: To identify preterm neonates at risk for adverse neonatal outcomes. METHOD OF STUDY: A nested case-control study from the prospectively followed Boston Birth Cohort of mother-neonate pairs was performed. A classification model for preterm-born neonates was derived from 27 cord blood biomarkers using orthogonal projections to latent structures discriminant analysis. Predictive relationships were made between biomarkers and adverse outcomes using logistic regression. RESULTS: From 926 births (53% of which were preterm), using weighted values for 27 biomarkers, a score was created that classified 73% of preterm deliveries. Soluble TNF-R1, NT-3, MCP-1, BDNF, IL-4, MMP-9, TREM-1, TNF-alpha, IL-5 and IL-10 were most influential. Our model was more sensitive for birth <34 weeks (sensitivity 89.5%, specificity 76.9%). IL-10, TNF-alpha, BDNF, NT-3, MMP-9, sTNF-R1 and MCP-1 were significantly predictive of NEC, IVH, sepsis and infections. CONCLUSION: We developed a novel mathematical model of 27 biomarkers associated with adverse neonatal outcomes in neonates born preterm.
%B Am J Reprod Immunol
%V 75
%P 594-601
%8 May
%@ 1600-0897 (Electronic)1046-7408 (Linking)
%M 26892347