{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T03:42:36Z","timestamp":1770349356766,"version":"3.49.0"},"reference-count":30,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2016,2,19]],"date-time":"2016-02-19T00:00:00Z","timestamp":1455840000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["American J Rep Immunol"],"published-print":{"date-parts":[[2016,5]]},"abstract":"<jats:sec><jats:title>Problem<\/jats:title><jats:p>To identify preterm neonates at risk for adverse neonatal outcomes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method of Study<\/jats:title><jats:p>A nested case\u2013control study from the prospectively followed Boston Birth Cohort of mother\u2013neonate pairs was performed. A classification model for preterm\u2010born 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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 <jats:styled-content style=\"fixed-case\">TNF<\/jats:styled-content>\u2010R1, <jats:styled-content style=\"fixed-case\">NT<\/jats:styled-content>\u20103, <jats:styled-content style=\"fixed-case\">MCP<\/jats:styled-content>\u20101, <jats:styled-content style=\"fixed-case\">BDNF<\/jats:styled-content>,<jats:styled-content style=\"fixed-case\"> IL<\/jats:styled-content>\u20104, <jats:styled-content style=\"fixed-case\">MMP<\/jats:styled-content>\u20109, <jats:styled-content style=\"fixed-case\">TREM<\/jats:styled-content>\u20101, <jats:styled-content style=\"fixed-case\">TNF<\/jats:styled-content>\u2010\u03b1, <jats:styled-content style=\"fixed-case\">IL<\/jats:styled-content>\u20105 and <jats:styled-content style=\"fixed-case\">IL<\/jats:styled-content>\u201010 were most influential. Our model was more sensitive for birth &lt;34 weeks (sensitivity 89.5%, specificity 76.9%). <jats:styled-content style=\"fixed-case\">IL<\/jats:styled-content>\u201010, <jats:styled-content style=\"fixed-case\">TNF<\/jats:styled-content>\u2010\u03b1, <jats:styled-content style=\"fixed-case\">BDNF<\/jats:styled-content>,<jats:styled-content style=\"fixed-case\"> NT<\/jats:styled-content>\u20103, <jats:styled-content style=\"fixed-case\">MMP<\/jats:styled-content>\u20109, <jats:styled-content style=\"fixed-case\">sTNF<\/jats:styled-content>\u2010R1 and <jats:styled-content style=\"fixed-case\">MCP<\/jats:styled-content>\u20101 were significantly predictive of <jats:styled-content style=\"fixed-case\">NEC<\/jats:styled-content>,<jats:styled-content style=\"fixed-case\"> IVH<\/jats:styled-content>, sepsis and infections.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>We developed a novel mathematical model of 27 biomarkers associated with adverse neonatal outcomes in neonates born preterm.<\/jats:p><\/jats:sec>","DOI":"10.1111\/aji.12502","type":"journal-article","created":{"date-parts":[[2016,2,20]],"date-time":"2016-02-20T14:27:11Z","timestamp":1455978431000},"page":"594-601","source":"Crossref","is-referenced-by-count":20,"title":["Mathematical Modeling of the Biomarker Milieu to Characterize Preterm Birth and Predict Adverse Neonatal Outcomes"],"prefix":"10.1111","volume":"75","author":[{"given":"Christina N.","family":"Cordeiro","sequence":"first","affiliation":[{"name":"Integrated Research Center for Fetal Medicine Department of Gynecology and Obstetrics Johns Hopkins University School of Medicine Baltimore MD USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yulia","family":"Savva","sequence":"additional","affiliation":[{"name":"Center for Child and Community Health Research Johns Hopkins University School of Medicine Baltimore MD 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