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Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis
BACKGROUND: Sepsis biomarker panels that provide diagnostic and prognostic discrimination in sepsis patients would be transformative to patient care. We assessed the mortality prediction and diagnostic discriminatory accuracy of two biomarkers reflective of cell death (apoptosis), circulating cell-f...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234551/ https://www.ncbi.nlm.nih.gov/pubmed/30459950 http://dx.doi.org/10.1186/s40560-018-0341-5 |
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author | Duplessis, Christopher Gregory, Michael Frey, Kenneth Bell, Matthew Truong, Luu Schully, Kevin Lawler, James Langley, Raymond J. Kingsmore, Stephen F. Woods, Christopher W. Rivers, Emanuel P. Jaehne, Anja K. Quackenbush, Eugenia B. Fowler, Vance G. Tsalik, Ephraim L. Clark, Danielle |
author_facet | Duplessis, Christopher Gregory, Michael Frey, Kenneth Bell, Matthew Truong, Luu Schully, Kevin Lawler, James Langley, Raymond J. Kingsmore, Stephen F. Woods, Christopher W. Rivers, Emanuel P. Jaehne, Anja K. Quackenbush, Eugenia B. Fowler, Vance G. Tsalik, Ephraim L. Clark, Danielle |
author_sort | Duplessis, Christopher |
collection | PubMed |
description | BACKGROUND: Sepsis biomarker panels that provide diagnostic and prognostic discrimination in sepsis patients would be transformative to patient care. We assessed the mortality prediction and diagnostic discriminatory accuracy of two biomarkers reflective of cell death (apoptosis), circulating cell-free DNA (cfDNA), and nucleosomes. METHODS: The cfDNA and nucleosome levels were assayed in plasma samples acquired in patients admitted from four emergency departments with suspected sepsis. Subjects with non-infectious systemic inflammatory response syndrome (SIRS) served as controls. Samples were acquired at enrollment (T0) and 24 h later (T24). We assessed diagnostic (differentiating SIRS from sepsis) and prognostic (28-day mortality) predictive power. Models incorporating procalcitonin (diagnostic prediction) and APACHE II scores (mortality prediction) were generated. RESULTS: Two hundred three subjects were included (107 provided procalcitonin measurements). Four subjects exhibited uncomplicated sepsis, 127 severe sepsis, 35 septic shock, and 24 had non-infectious SIRS. There were 190-survivors and 13 non-survivors. Mortality prediction models using cfDNA, nucleosomes, or APACHEII yielded AUC values of 0.61, 0.75, and 0.81, respectively. A model combining nucleosomes with the APACHE II score improved the AUC to 0.84. Diagnostic models distinguishing sepsis from SIRS using procalcitonin, cfDNA(T0), or nucleosomes(T0) yielded AUC values of 0.64, 0.65, and 0.63, respectively. The three parameter model yielded an AUC of 0.74. CONCLUSIONS: To our knowledge, this is the first head-to-head comparison of cfDNA and nucleosomes in diagnosing sepsis and predicting sepsis-related mortality. Both cfDNA and nucleosome concentrations demonstrated a modest ability to distinguish sepsis survivors and non-survivors and provided additive diagnostic predictive accuracy in differentiating sepsis from non-infectious SIRS when integrated into a diagnostic prediction model including PCT and APACHE II. A sepsis biomarker strategy incorporating measures of the apoptotic pathway may serve as an important component of a sepsis diagnostic and mortality prediction tool. |
format | Online Article Text |
id | pubmed-6234551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62345512018-11-20 Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis Duplessis, Christopher Gregory, Michael Frey, Kenneth Bell, Matthew Truong, Luu Schully, Kevin Lawler, James Langley, Raymond J. Kingsmore, Stephen F. Woods, Christopher W. Rivers, Emanuel P. Jaehne, Anja K. Quackenbush, Eugenia B. Fowler, Vance G. Tsalik, Ephraim L. Clark, Danielle J Intensive Care Research BACKGROUND: Sepsis biomarker panels that provide diagnostic and prognostic discrimination in sepsis patients would be transformative to patient care. We assessed the mortality prediction and diagnostic discriminatory accuracy of two biomarkers reflective of cell death (apoptosis), circulating cell-free DNA (cfDNA), and nucleosomes. METHODS: The cfDNA and nucleosome levels were assayed in plasma samples acquired in patients admitted from four emergency departments with suspected sepsis. Subjects with non-infectious systemic inflammatory response syndrome (SIRS) served as controls. Samples were acquired at enrollment (T0) and 24 h later (T24). We assessed diagnostic (differentiating SIRS from sepsis) and prognostic (28-day mortality) predictive power. Models incorporating procalcitonin (diagnostic prediction) and APACHE II scores (mortality prediction) were generated. RESULTS: Two hundred three subjects were included (107 provided procalcitonin measurements). Four subjects exhibited uncomplicated sepsis, 127 severe sepsis, 35 septic shock, and 24 had non-infectious SIRS. There were 190-survivors and 13 non-survivors. Mortality prediction models using cfDNA, nucleosomes, or APACHEII yielded AUC values of 0.61, 0.75, and 0.81, respectively. A model combining nucleosomes with the APACHE II score improved the AUC to 0.84. Diagnostic models distinguishing sepsis from SIRS using procalcitonin, cfDNA(T0), or nucleosomes(T0) yielded AUC values of 0.64, 0.65, and 0.63, respectively. The three parameter model yielded an AUC of 0.74. CONCLUSIONS: To our knowledge, this is the first head-to-head comparison of cfDNA and nucleosomes in diagnosing sepsis and predicting sepsis-related mortality. Both cfDNA and nucleosome concentrations demonstrated a modest ability to distinguish sepsis survivors and non-survivors and provided additive diagnostic predictive accuracy in differentiating sepsis from non-infectious SIRS when integrated into a diagnostic prediction model including PCT and APACHE II. A sepsis biomarker strategy incorporating measures of the apoptotic pathway may serve as an important component of a sepsis diagnostic and mortality prediction tool. BioMed Central 2018-11-13 /pmc/articles/PMC6234551/ /pubmed/30459950 http://dx.doi.org/10.1186/s40560-018-0341-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Duplessis, Christopher Gregory, Michael Frey, Kenneth Bell, Matthew Truong, Luu Schully, Kevin Lawler, James Langley, Raymond J. Kingsmore, Stephen F. Woods, Christopher W. Rivers, Emanuel P. Jaehne, Anja K. Quackenbush, Eugenia B. Fowler, Vance G. Tsalik, Ephraim L. Clark, Danielle Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis |
title | Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis |
title_full | Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis |
title_fullStr | Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis |
title_full_unstemmed | Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis |
title_short | Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis |
title_sort | evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234551/ https://www.ncbi.nlm.nih.gov/pubmed/30459950 http://dx.doi.org/10.1186/s40560-018-0341-5 |
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