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Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection

Clostridioides difficile infection (CDI) can result in severe disease and death, with no accurate models that allow for early prediction of adverse outcomes. To address this need, we sought to develop serum-based biomarker models to predict CDI outcomes. We prospectively collected sera ≤48 h after d...

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Autores principales: Dieterle, Michael G., Putler, Rosemary, Perry, D. Alexander, Menon, Anitha, Abernathy-Close, Lisa, Perlman, Naomi S., Penkevich, Aline, Standke, Alex, Keidan, Micah, Vendrov, Kimberly C., Bergin, Ingrid L., Young, Vincent B., Rao, Krishna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7403776/
https://www.ncbi.nlm.nih.gov/pubmed/32371595
http://dx.doi.org/10.1128/mBio.00180-20
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author Dieterle, Michael G.
Putler, Rosemary
Perry, D. Alexander
Menon, Anitha
Abernathy-Close, Lisa
Perlman, Naomi S.
Penkevich, Aline
Standke, Alex
Keidan, Micah
Vendrov, Kimberly C.
Bergin, Ingrid L.
Young, Vincent B.
Rao, Krishna
author_facet Dieterle, Michael G.
Putler, Rosemary
Perry, D. Alexander
Menon, Anitha
Abernathy-Close, Lisa
Perlman, Naomi S.
Penkevich, Aline
Standke, Alex
Keidan, Micah
Vendrov, Kimberly C.
Bergin, Ingrid L.
Young, Vincent B.
Rao, Krishna
author_sort Dieterle, Michael G.
collection PubMed
description Clostridioides difficile infection (CDI) can result in severe disease and death, with no accurate models that allow for early prediction of adverse outcomes. To address this need, we sought to develop serum-based biomarker models to predict CDI outcomes. We prospectively collected sera ≤48 h after diagnosis of CDI in two cohorts. Biomarkers were measured with a custom multiplex bead array assay. Patients were classified using IDSA severity criteria and the development of disease-related complications (DRCs), which were defined as ICU admission, colectomy, and/or death attributed to CDI. Unadjusted and adjusted models were built using logistic and elastic net modeling. The best model for severity included procalcitonin (PCT) and hepatocyte growth factor (HGF) with an area (AUC) under the receiver operating characteristic (ROC) curve of 0.74 (95% confidence interval, 0.67 to 0.81). The best model for 30-day mortality included interleukin-8 (IL-8), PCT, CXCL-5, IP-10, and IL-2Rα with an AUC of 0.89 (0.84 to 0.95). The best model for DRCs included IL-8, procalcitonin, HGF, and IL-2Rα with an AUC of 0.84 (0.73 to 0.94). To validate our models, we employed experimental infection of mice with C. difficile. Antibiotic-treated mice were challenged with C. difficile and a similar panel of serum biomarkers was measured. Applying each model to the mouse cohort of severe and nonsevere CDI revealed AUCs of 0.59 (0.44 to 0.74), 0.96 (0.90 to 1.0), and 0.89 (0.81 to 0.97). In both human and murine CDI, models based on serum biomarkers predicted adverse CDI outcomes. Our results support the use of serum-based biomarker panels to inform Clostridioides difficile infection treatment.
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spelling pubmed-74037762020-08-11 Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection Dieterle, Michael G. Putler, Rosemary Perry, D. Alexander Menon, Anitha Abernathy-Close, Lisa Perlman, Naomi S. Penkevich, Aline Standke, Alex Keidan, Micah Vendrov, Kimberly C. Bergin, Ingrid L. Young, Vincent B. Rao, Krishna mBio Research Article Clostridioides difficile infection (CDI) can result in severe disease and death, with no accurate models that allow for early prediction of adverse outcomes. To address this need, we sought to develop serum-based biomarker models to predict CDI outcomes. We prospectively collected sera ≤48 h after diagnosis of CDI in two cohorts. Biomarkers were measured with a custom multiplex bead array assay. Patients were classified using IDSA severity criteria and the development of disease-related complications (DRCs), which were defined as ICU admission, colectomy, and/or death attributed to CDI. Unadjusted and adjusted models were built using logistic and elastic net modeling. The best model for severity included procalcitonin (PCT) and hepatocyte growth factor (HGF) with an area (AUC) under the receiver operating characteristic (ROC) curve of 0.74 (95% confidence interval, 0.67 to 0.81). The best model for 30-day mortality included interleukin-8 (IL-8), PCT, CXCL-5, IP-10, and IL-2Rα with an AUC of 0.89 (0.84 to 0.95). The best model for DRCs included IL-8, procalcitonin, HGF, and IL-2Rα with an AUC of 0.84 (0.73 to 0.94). To validate our models, we employed experimental infection of mice with C. difficile. Antibiotic-treated mice were challenged with C. difficile and a similar panel of serum biomarkers was measured. Applying each model to the mouse cohort of severe and nonsevere CDI revealed AUCs of 0.59 (0.44 to 0.74), 0.96 (0.90 to 1.0), and 0.89 (0.81 to 0.97). In both human and murine CDI, models based on serum biomarkers predicted adverse CDI outcomes. Our results support the use of serum-based biomarker panels to inform Clostridioides difficile infection treatment. American Society for Microbiology 2020-05-05 /pmc/articles/PMC7403776/ /pubmed/32371595 http://dx.doi.org/10.1128/mBio.00180-20 Text en Copyright © 2020 Dieterle et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Dieterle, Michael G.
Putler, Rosemary
Perry, D. Alexander
Menon, Anitha
Abernathy-Close, Lisa
Perlman, Naomi S.
Penkevich, Aline
Standke, Alex
Keidan, Micah
Vendrov, Kimberly C.
Bergin, Ingrid L.
Young, Vincent B.
Rao, Krishna
Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection
title Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection
title_full Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection
title_fullStr Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection
title_full_unstemmed Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection
title_short Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection
title_sort systemic inflammatory mediators are effective biomarkers for predicting adverse outcomes in clostridioides difficile infection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7403776/
https://www.ncbi.nlm.nih.gov/pubmed/32371595
http://dx.doi.org/10.1128/mBio.00180-20
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