OpenLink Software

About: BACKGROUND: Current tools to predict the severity of respiratory syncytial virus (RSV) infection might be improved by including immunological parameters. We hypothesized that a combination of inflammatory markers would differentiate between severe and mild disease in RSV-infected children. METHODS: Blood and nasopharyngeal samples from 52 RSV-infected children were collected during acute infection and after recovery. Retrospectively, patients were categorized into three groups based on disease severity: mild (no supportive treatment), moderate (supplemental oxygen and/or nasogastric feeding), and severe (mechanical ventilation). Clinical data, number of flow-defined leukocyte subsets, and cytokine concentrations were compared. RESULTS: Children with severe RSV infection were characterized by young age; lymphocytopenia; increased interleukin (IL)-8, granulocyte colony-stimulating factor (G-CSF), and IL-6 concentrations; and decreased chemokine (C-C motif) ligand (CCL-5) concentrations in plasma. The combination of plasma levels of IL-8 and CCL-5, and CD4(+) T-cell counts, with cutoff values of 67 pg/ml, 13 ng/ml, and 2.3 × 10(6)/ml, respectively, discriminated severe from mild RSV infection with 82% sensitivity and 96% specificity. CONCLUSION: This study demonstrates that the combination of CD4(+) T-cell counts and IL-8 and CCL-5 plasma concentrations correlates with disease severity in RSV-infected children. In addition to clinical features, these immunological markers may be used to assess severity of RSV infection and guide clinical management. SUPPLEMENTARY INFORMATION: The online version of this article (doi:10.1038/pr.2012.163) contains supplementary material, which is available to authorized users.

 Permalink

an Entity references as follows:

Faceted Search & Find service v1.13.91

Alternative Linked Data Documents: Sponger | ODE     Raw Data in: CXML | CSV | RDF ( N-Triples N3/Turtle JSON XML ) | OData ( Atom JSON ) | Microdata ( JSON HTML) | JSON-LD    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] This material is Open Knowledge Creative Commons License Valid XHTML + RDFa
This work is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License.
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Copyright © 2009-2024 OpenLink Software