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Biomarker combinations in predicting sepsis in hospitalized children with fever
Sepsis is among the leading causes of critical illness worldwide. It includes physiologic, pathologic, and biochemical abnormalities, induced by infection. Novel methods for recognizing a dysregulated inflammatory response and predicting associated mortality must be developed. Our aim was to investi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9097178/ https://www.ncbi.nlm.nih.gov/pubmed/35550043 http://dx.doi.org/10.1186/s12887-022-03285-3 |
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author | Rautiainen, Linda Cirko, Anna Pavare, Jana Grope, Ilze Gersone, Gita Tretjakovs, Peteris Gardovska, Dace |
author_facet | Rautiainen, Linda Cirko, Anna Pavare, Jana Grope, Ilze Gersone, Gita Tretjakovs, Peteris Gardovska, Dace |
author_sort | Rautiainen, Linda |
collection | PubMed |
description | Sepsis is among the leading causes of critical illness worldwide. It includes physiologic, pathologic, and biochemical abnormalities, induced by infection. Novel methods for recognizing a dysregulated inflammatory response and predicting associated mortality must be developed. Our aim was to investigate biomarkers that characterize a pro-inflammatory and anti-inflammatory response in patients with fever by comparing predictive validity for sepsis. 165 patients with fever were enrolled in this study, 55 of them had sepsis according to pSOFA criteria. All patients had blood samples drawn at the time of inclusion and after 24 h. CRP, PCT and also IL-6, IL-8 and sFAS levels were significantly higher in patients with sepsis. The AUC of CRP to predict sepsis was 0.799, all the other biomarkers had AUC’s lower than that. Cytokines, when used as a single marker, did not show a significant diagnostic performance We analyzed various models of biomarker combinations. CRP combined with sFAS showed increase in sensitivity in predicting sepsis (88% vs. 83%). The highest AUC was achieved, when CRP, IL-6, sFAS and sVCAM-1 markers were combined 0.830 (95% CI 0.762–0.884) with a sensitivity of 70% and specificity of 84%. vs. 0.799 for CRP alone. |
format | Online Article Text |
id | pubmed-9097178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90971782022-05-13 Biomarker combinations in predicting sepsis in hospitalized children with fever Rautiainen, Linda Cirko, Anna Pavare, Jana Grope, Ilze Gersone, Gita Tretjakovs, Peteris Gardovska, Dace BMC Pediatr Research Sepsis is among the leading causes of critical illness worldwide. It includes physiologic, pathologic, and biochemical abnormalities, induced by infection. Novel methods for recognizing a dysregulated inflammatory response and predicting associated mortality must be developed. Our aim was to investigate biomarkers that characterize a pro-inflammatory and anti-inflammatory response in patients with fever by comparing predictive validity for sepsis. 165 patients with fever were enrolled in this study, 55 of them had sepsis according to pSOFA criteria. All patients had blood samples drawn at the time of inclusion and after 24 h. CRP, PCT and also IL-6, IL-8 and sFAS levels were significantly higher in patients with sepsis. The AUC of CRP to predict sepsis was 0.799, all the other biomarkers had AUC’s lower than that. Cytokines, when used as a single marker, did not show a significant diagnostic performance We analyzed various models of biomarker combinations. CRP combined with sFAS showed increase in sensitivity in predicting sepsis (88% vs. 83%). The highest AUC was achieved, when CRP, IL-6, sFAS and sVCAM-1 markers were combined 0.830 (95% CI 0.762–0.884) with a sensitivity of 70% and specificity of 84%. vs. 0.799 for CRP alone. BioMed Central 2022-05-12 /pmc/articles/PMC9097178/ /pubmed/35550043 http://dx.doi.org/10.1186/s12887-022-03285-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Rautiainen, Linda Cirko, Anna Pavare, Jana Grope, Ilze Gersone, Gita Tretjakovs, Peteris Gardovska, Dace Biomarker combinations in predicting sepsis in hospitalized children with fever |
title | Biomarker combinations in predicting sepsis in hospitalized children with fever |
title_full | Biomarker combinations in predicting sepsis in hospitalized children with fever |
title_fullStr | Biomarker combinations in predicting sepsis in hospitalized children with fever |
title_full_unstemmed | Biomarker combinations in predicting sepsis in hospitalized children with fever |
title_short | Biomarker combinations in predicting sepsis in hospitalized children with fever |
title_sort | biomarker combinations in predicting sepsis in hospitalized children with fever |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9097178/ https://www.ncbi.nlm.nih.gov/pubmed/35550043 http://dx.doi.org/10.1186/s12887-022-03285-3 |
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