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Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS
BACKGROUND: To allow early identification of patients at risk of sepsis in the emergency department (ED), a variety of risk stratification scores and/or triage systems are used. The first aim of this study was to develop a risk stratification score for sepsis based upon vital signs and biomarkers us...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7032705/ https://www.ncbi.nlm.nih.gov/pubmed/32078640 http://dx.doi.org/10.1371/journal.pone.0229210 |
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author | Mellhammar, Lisa Linder, Adam Tverring, Jonas Christensson, Bertil Boyd, John H. Åkesson, Per Kahn, Fredrik |
author_facet | Mellhammar, Lisa Linder, Adam Tverring, Jonas Christensson, Bertil Boyd, John H. Åkesson, Per Kahn, Fredrik |
author_sort | Mellhammar, Lisa |
collection | PubMed |
description | BACKGROUND: To allow early identification of patients at risk of sepsis in the emergency department (ED), a variety of risk stratification scores and/or triage systems are used. The first aim of this study was to develop a risk stratification score for sepsis based upon vital signs and biomarkers using a statistical approach. Second, we aimed to validate the Rapid Emergency Triage and Treatment System (RETTS) for sepsis. RETTS combines vital signs with symptoms for risk stratification. METHODS: We retrospectively analysed data from two prospective, observational, multicentre cohorts of patients from studies of biomarkers in ED. A candidate risk stratification score called Sepsis Heparin-binding protein-based Early Warning Score (SHEWS) was constructed using the Least Absolute Shrinkage and Selector Operator (LASSO) method. SHEWS and RETTS were compared to National Early Warning Score 2 (NEWS2) for infection-related organ dysfunction, intensive care or death within the first 72h after admission (i.e. sepsis). RESULTS: 506 patients with a diagnosed infection constituted cohort A, in which SHEWS was derived and RETTS was validated. 435 patients constituted cohort B of whom 184 had a diagnosed infection where both scores were validated. In both cohorts (A and B), AUC for infection-related organ dysfunction, intensive care or death was higher for NEWS2, 0.80 (95% CI 0.76–0.84) and 0.69 (95% CI 0.63–0.74), than RETTS, 0.74 (95% CI 0.70–0.79) and 0.55 (95% CI 0.49–0.60), p = 0.05 and p <0.01, respectively. SHEWS had the highest AUC, 0.73 (95% CI 0.68–0.79) p = 0.32 in cohort B. CONCLUSIONS: Even with a statistical approach, we could not construct better risk stratification scores for sepsis than NEWS2. RETTS was inferior to NEWS2 for screening for sepsis. |
format | Online Article Text |
id | pubmed-7032705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-70327052020-02-27 Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS Mellhammar, Lisa Linder, Adam Tverring, Jonas Christensson, Bertil Boyd, John H. Åkesson, Per Kahn, Fredrik PLoS One Research Article BACKGROUND: To allow early identification of patients at risk of sepsis in the emergency department (ED), a variety of risk stratification scores and/or triage systems are used. The first aim of this study was to develop a risk stratification score for sepsis based upon vital signs and biomarkers using a statistical approach. Second, we aimed to validate the Rapid Emergency Triage and Treatment System (RETTS) for sepsis. RETTS combines vital signs with symptoms for risk stratification. METHODS: We retrospectively analysed data from two prospective, observational, multicentre cohorts of patients from studies of biomarkers in ED. A candidate risk stratification score called Sepsis Heparin-binding protein-based Early Warning Score (SHEWS) was constructed using the Least Absolute Shrinkage and Selector Operator (LASSO) method. SHEWS and RETTS were compared to National Early Warning Score 2 (NEWS2) for infection-related organ dysfunction, intensive care or death within the first 72h after admission (i.e. sepsis). RESULTS: 506 patients with a diagnosed infection constituted cohort A, in which SHEWS was derived and RETTS was validated. 435 patients constituted cohort B of whom 184 had a diagnosed infection where both scores were validated. In both cohorts (A and B), AUC for infection-related organ dysfunction, intensive care or death was higher for NEWS2, 0.80 (95% CI 0.76–0.84) and 0.69 (95% CI 0.63–0.74), than RETTS, 0.74 (95% CI 0.70–0.79) and 0.55 (95% CI 0.49–0.60), p = 0.05 and p <0.01, respectively. SHEWS had the highest AUC, 0.73 (95% CI 0.68–0.79) p = 0.32 in cohort B. CONCLUSIONS: Even with a statistical approach, we could not construct better risk stratification scores for sepsis than NEWS2. RETTS was inferior to NEWS2 for screening for sepsis. Public Library of Science 2020-02-20 /pmc/articles/PMC7032705/ /pubmed/32078640 http://dx.doi.org/10.1371/journal.pone.0229210 Text en © 2020 Mellhammar 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mellhammar, Lisa Linder, Adam Tverring, Jonas Christensson, Bertil Boyd, John H. Åkesson, Per Kahn, Fredrik Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS |
title | Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS |
title_full | Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS |
title_fullStr | Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS |
title_full_unstemmed | Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS |
title_short | Scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of RETTS |
title_sort | scores for sepsis detection and risk stratification – construction of a novel score using a statistical approach and validation of retts |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7032705/ https://www.ncbi.nlm.nih.gov/pubmed/32078640 http://dx.doi.org/10.1371/journal.pone.0229210 |
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