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Young Joo Park, Se Joon Woo, Yu Mi Kim, Subeen Hong, Young Eun Lee, Kyo Hoon Park; Immune and Inflammatory Proteins in Cord Blood as Predictive Biomarkers of Retinopathy of Prematurity in Preterm Infants. Invest. Ophthalmol. Vis. Sci. 2019;60(12):3813-3820. doi: https://doi.org/10.1167/iovs.19-27258.
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To determine whether elevated levels of immune/inflammatory proteins in cord blood, alone or in combination with conventional clinical parameters, can predict the occurrence and progression of retinopathy of prematurity (ROP) in preterm infants.
This was a retrospective cohort study of 110 premature singleton infants who were born at ≤32.0 weeks. Cord plasma at birth was assayed for interleukin-6, C3a, C5a, matrix metalloproteinase-2 (MMP-2), MMP-9, tissue inhibitor of metalloproteinase-1, macrophage colony-stimulating factor, endostatin, a proliferation-inducing ligand, insulin-like growth factor-binding protein-1 (IGFBP-1), IGFBP-2, and calcium-binding protein A8/A9 complex levels. The primary outcome measures were the occurrence of any stage ROP, severe ROP (>stage 3), and vision-threatening type 1 ROP requiring laser treatment.
ROP was diagnosed in 30 of 110 infants (27.3%), including 14 (12.7%) with severe ROP. Laser treatment was performed on 7 infants (6.4%). Multiple logistic regression analyses indicated that elevated levels of cord plasma IL-6 were significantly associated with severe ROP, whereas elevated levels of cord plasma C5a were significantly associated with ROP laser treatments. However, none of the proteins measured in the cord plasma were associated with ROP occurrence. Using a stepwise regression procedure, we developed a combined prediction model, which included high cord plasma IL-6 levels and low birth weight for severe ROP (area under the curve [AUC], 0.840), and high cord plasma C5a levels and low birth weight for laser treatment (AUC, 0.884).
Elevated levels of cord plasma IL-6 and C5a could be used as independent markers to predict severe ROP and laser treatment, respectively, with combined models predicting ROP progression with good accuracy.
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