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Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients
Physicians are regularly faced with severely ill patients at risk of developing infections. In literature, standard care wards are often neglected, although their patients frequently suffer from a systemic inflammatory response syndrome (SIRS) of unknown origin. Fast identification of patients with...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859603/ https://www.ncbi.nlm.nih.gov/pubmed/24349403 http://dx.doi.org/10.1371/journal.pone.0082946 |
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author | Ratzinger, Franz Schuardt, Michael Eichbichler, Katherina Tsirkinidou, Irene Bauer, Marlene Haslacher, Helmuth Mitteregger, Dieter Binder, Michael Burgmann, Heinz |
author_facet | Ratzinger, Franz Schuardt, Michael Eichbichler, Katherina Tsirkinidou, Irene Bauer, Marlene Haslacher, Helmuth Mitteregger, Dieter Binder, Michael Burgmann, Heinz |
author_sort | Ratzinger, Franz |
collection | PubMed |
description | Physicians are regularly faced with severely ill patients at risk of developing infections. In literature, standard care wards are often neglected, although their patients frequently suffer from a systemic inflammatory response syndrome (SIRS) of unknown origin. Fast identification of patients with infections is vital, as they immediately require appropriate therapy. Further, tools with a high negative predictive value (NPV) to exclude infection or bacteremia are important to increase the cost effectiveness of microbiological examinations and to avoid inappropriate antibiotic treatment. In this prospective cohort study, 2,384 patients with suspected infections were screened for suffering from two or more SIRS criteria on standard care wards. The infection probability score (IPS) and sepsis biomarkers with discriminatory power were assessed regarding their capacity to identify infection or bacteremia. In this cohort finally consisting of 298 SIRS-patients, the infection prevalence was 72%. Bacteremia was found in 25% of cases. For the prediction of infection, the IPS yielded 0.51 ROC-AUC (30.1% sensitivity, 64.6% specificity). Among sepsis biomarkers, lipopolysaccharide binding protein (LBP) was the best parameter with 0.63 ROC-AUC (57.5% sensitivity, 67.1% specificity). For the prediction of bacteremia, the IPS performed slightly better with a ROC-AUC of 0.58 (21.3% sensitivity, 65% specificity). Procalcitonin was the best discriminator with 0.78 ROC-AUC, 86.3% sensitivity, 59.6% specificity and 92.9% NPV. Furthermore, bilirubin and LBP (ROC-AUC: 0.65, 0.62) might also be considered as useful parameters. In summary, the IPS and widely used infection parameters, including CRP or WBC, yielded a poor diagnostic performance for the detection of infection or bacteremia. Additional sepsis biomarkers do not aid in discriminating inflammation from infection. For the prediction of bacteremia procalcitonin, and bilirubin were the most promising parameters, which might be used as a rule for when to take blood cultures or using nucleic acid amplification tests for microbiological diagnostics. |
format | Online Article Text |
id | pubmed-3859603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38596032013-12-13 Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients Ratzinger, Franz Schuardt, Michael Eichbichler, Katherina Tsirkinidou, Irene Bauer, Marlene Haslacher, Helmuth Mitteregger, Dieter Binder, Michael Burgmann, Heinz PLoS One Research Article Physicians are regularly faced with severely ill patients at risk of developing infections. In literature, standard care wards are often neglected, although their patients frequently suffer from a systemic inflammatory response syndrome (SIRS) of unknown origin. Fast identification of patients with infections is vital, as they immediately require appropriate therapy. Further, tools with a high negative predictive value (NPV) to exclude infection or bacteremia are important to increase the cost effectiveness of microbiological examinations and to avoid inappropriate antibiotic treatment. In this prospective cohort study, 2,384 patients with suspected infections were screened for suffering from two or more SIRS criteria on standard care wards. The infection probability score (IPS) and sepsis biomarkers with discriminatory power were assessed regarding their capacity to identify infection or bacteremia. In this cohort finally consisting of 298 SIRS-patients, the infection prevalence was 72%. Bacteremia was found in 25% of cases. For the prediction of infection, the IPS yielded 0.51 ROC-AUC (30.1% sensitivity, 64.6% specificity). Among sepsis biomarkers, lipopolysaccharide binding protein (LBP) was the best parameter with 0.63 ROC-AUC (57.5% sensitivity, 67.1% specificity). For the prediction of bacteremia, the IPS performed slightly better with a ROC-AUC of 0.58 (21.3% sensitivity, 65% specificity). Procalcitonin was the best discriminator with 0.78 ROC-AUC, 86.3% sensitivity, 59.6% specificity and 92.9% NPV. Furthermore, bilirubin and LBP (ROC-AUC: 0.65, 0.62) might also be considered as useful parameters. In summary, the IPS and widely used infection parameters, including CRP or WBC, yielded a poor diagnostic performance for the detection of infection or bacteremia. Additional sepsis biomarkers do not aid in discriminating inflammation from infection. For the prediction of bacteremia procalcitonin, and bilirubin were the most promising parameters, which might be used as a rule for when to take blood cultures or using nucleic acid amplification tests for microbiological diagnostics. Public Library of Science 2013-12-11 /pmc/articles/PMC3859603/ /pubmed/24349403 http://dx.doi.org/10.1371/journal.pone.0082946 Text en © 2013 Ratzinger et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ratzinger, Franz Schuardt, Michael Eichbichler, Katherina Tsirkinidou, Irene Bauer, Marlene Haslacher, Helmuth Mitteregger, Dieter Binder, Michael Burgmann, Heinz Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients |
title | Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients |
title_full | Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients |
title_fullStr | Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients |
title_full_unstemmed | Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients |
title_short | Utility of Sepsis Biomarkers and the Infection Probability Score to Discriminate Sepsis and Systemic Inflammatory Response Syndrome in Standard Care Patients |
title_sort | utility of sepsis biomarkers and the infection probability score to discriminate sepsis and systemic inflammatory response syndrome in standard care patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859603/ https://www.ncbi.nlm.nih.gov/pubmed/24349403 http://dx.doi.org/10.1371/journal.pone.0082946 |
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