American journal of reproductive immunology (New York, N.Y. : 1989) · 2016
Mathematical Modeling of the Biomarker Milieu to Characterize Preterm Birth and Predict Adverse Neonatal Outcomes.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Cordeiro Christina N, Savva Yulia, Vaidya Dhananjay, Argani Cynthia H, Hong Xiumei, Wang Xiaobin, Burd Irina
Аннотация
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-α, 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-α, 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.
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-α, 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-α, 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.