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Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU
Background: This study aimed to assess the value of blood and urine biomarkers in addition to routine clinical variables in risk stratification of patients admitted to ICU. Methods: Multivariable prognostic models were developed in this post hoc analysis of the French and EuRopean Outcome ReGistry i...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179283/ https://www.ncbi.nlm.nih.gov/pubmed/37176751 http://dx.doi.org/10.3390/jcm12093311 |
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author | Davison, Beth A. Edwards, Christopher Cotter, Gad Kimmoun, Antoine Gayat, Étienne Latosinska, Agnieszka Mischak, Harald Takagi, Koji Deniau, Benjamin Picod, Adrien Mebazaa, Alexandre |
author_facet | Davison, Beth A. Edwards, Christopher Cotter, Gad Kimmoun, Antoine Gayat, Étienne Latosinska, Agnieszka Mischak, Harald Takagi, Koji Deniau, Benjamin Picod, Adrien Mebazaa, Alexandre |
author_sort | Davison, Beth A. |
collection | PubMed |
description | Background: This study aimed to assess the value of blood and urine biomarkers in addition to routine clinical variables in risk stratification of patients admitted to ICU. Methods: Multivariable prognostic models were developed in this post hoc analysis of the French and EuRopean Outcome ReGistry in Intensive Care Units study, a prospective observational study of patients admitted to ICUs. The study included 2087 patients consecutively admitted to the ICU who required invasive mechanical ventilation or a vasoactive agent for more than 24 h. The main outcome measures were in-ICU, in-hospital, and 1 year mortality. Results: Models including only SAPS II or APACHE II scores had c-indexes for in-hospital and 1 year mortality of 0.64 and 0.65, and 0.63 and 0.61, respectively. The c-indexes for a model including age and estimated glomerular filtration rate were higher at 0.69 and 0.67, respectively. Models utilizing available clinical variables increased the c-index for in-hospital and 1 year mortality to 0.80 and 0.76, respectively. The addition of biomarkers and urine proteomic markers increased c-indexes to 0.83 and 0.78. Conclusions: The commonly used scores for risk stratification in ICU patients did not perform well in this study. Models including clinical variables and biomarkers had significantly higher predictive values. |
format | Online Article Text |
id | pubmed-10179283 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101792832023-05-13 Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU Davison, Beth A. Edwards, Christopher Cotter, Gad Kimmoun, Antoine Gayat, Étienne Latosinska, Agnieszka Mischak, Harald Takagi, Koji Deniau, Benjamin Picod, Adrien Mebazaa, Alexandre J Clin Med Article Background: This study aimed to assess the value of blood and urine biomarkers in addition to routine clinical variables in risk stratification of patients admitted to ICU. Methods: Multivariable prognostic models were developed in this post hoc analysis of the French and EuRopean Outcome ReGistry in Intensive Care Units study, a prospective observational study of patients admitted to ICUs. The study included 2087 patients consecutively admitted to the ICU who required invasive mechanical ventilation or a vasoactive agent for more than 24 h. The main outcome measures were in-ICU, in-hospital, and 1 year mortality. Results: Models including only SAPS II or APACHE II scores had c-indexes for in-hospital and 1 year mortality of 0.64 and 0.65, and 0.63 and 0.61, respectively. The c-indexes for a model including age and estimated glomerular filtration rate were higher at 0.69 and 0.67, respectively. Models utilizing available clinical variables increased the c-index for in-hospital and 1 year mortality to 0.80 and 0.76, respectively. The addition of biomarkers and urine proteomic markers increased c-indexes to 0.83 and 0.78. Conclusions: The commonly used scores for risk stratification in ICU patients did not perform well in this study. Models including clinical variables and biomarkers had significantly higher predictive values. MDPI 2023-05-06 /pmc/articles/PMC10179283/ /pubmed/37176751 http://dx.doi.org/10.3390/jcm12093311 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Davison, Beth A. Edwards, Christopher Cotter, Gad Kimmoun, Antoine Gayat, Étienne Latosinska, Agnieszka Mischak, Harald Takagi, Koji Deniau, Benjamin Picod, Adrien Mebazaa, Alexandre Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU |
title | Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU |
title_full | Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU |
title_fullStr | Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU |
title_full_unstemmed | Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU |
title_short | Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU |
title_sort | plasma and urinary biomarkers improve prediction of mortality through 1 year in intensive care patients: an analysis from frog-icu |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179283/ https://www.ncbi.nlm.nih.gov/pubmed/37176751 http://dx.doi.org/10.3390/jcm12093311 |
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