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Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach
To determine if a set of time-varying biological indicators can be used to: 1) predict the sepsis mortality risk over time and 2) generate mortality risk profiles. DESIGN: Prospective observational study. SETTING: Nine Canadian ICUs. SUBJECTS: Three-hundred fifty-six septic patients. INTERVENTIONS:...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063956/ https://www.ncbi.nlm.nih.gov/pubmed/32166273 http://dx.doi.org/10.1097/CCE.0000000000000032 |
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author | Liaw, Patricia C. Fox-Robichaud, Alison E. Liaw, Kao-Lee McDonald, Ellen Dwivedi, Dhruva J. Zamir, Nasim M. Pepler, Laura Gould, Travis J. Xu, Michael Zytaruk, Nicole Medeiros, Sarah K. McIntyre, Lauralyn Tsang, Jennifer Dodek, Peter M. Winston, Brent W. Martin, Claudio Fraser, Douglas D. Weitz, Jeffrey I. Lellouche, Francois Cook, Deborah J. Marshall, John |
author_facet | Liaw, Patricia C. Fox-Robichaud, Alison E. Liaw, Kao-Lee McDonald, Ellen Dwivedi, Dhruva J. Zamir, Nasim M. Pepler, Laura Gould, Travis J. Xu, Michael Zytaruk, Nicole Medeiros, Sarah K. McIntyre, Lauralyn Tsang, Jennifer Dodek, Peter M. Winston, Brent W. Martin, Claudio Fraser, Douglas D. Weitz, Jeffrey I. Lellouche, Francois Cook, Deborah J. Marshall, John |
author_sort | Liaw, Patricia C. |
collection | PubMed |
description | To determine if a set of time-varying biological indicators can be used to: 1) predict the sepsis mortality risk over time and 2) generate mortality risk profiles. DESIGN: Prospective observational study. SETTING: Nine Canadian ICUs. SUBJECTS: Three-hundred fifty-six septic patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Clinical data and plasma levels of biomarkers were collected longitudinally. We used a complementary log-log model to account for the daily mortality risk of each patient until death in ICU/hospital, discharge, or 28 days after admission. The model, which is a versatile version of the Cox model for gaining longitudinal insights, created a composite indicator (the daily hazard of dying) from the “day 1” and “change” variables of six time-varying biological indicators (cell-free DNA, protein C, platelet count, creatinine, Glasgow Coma Scale score, and lactate) and a set of contextual variables (age, presence of chronic lung disease or previous brain injury, and duration of stay), achieving a high predictive power (conventional area under the curve, 0.90; 95% CI, 0.86–0.94). Including change variables avoided misleading inferences about the effects of day 1 variables, signifying the importance of the longitudinal approach. We then generated mortality risk profiles that highlight the relative contributions among the time-varying biological indicators to overall mortality risk. The tool was validated in 28 nonseptic patients from the same ICUs who became septic later and was subject to 10-fold cross-validation, achieving similarly high area under the curve. CONCLUSIONS: Using a novel version of the Cox model, we created a prognostic tool for septic patients that yields not only a predicted probability of dying but also a mortality risk profile that reveals how six time-varying biological indicators differentially and longitudinally account for the patient’s overall daily mortality risk. |
format | Online Article Text |
id | pubmed-7063956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-70639562020-03-12 Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach Liaw, Patricia C. Fox-Robichaud, Alison E. Liaw, Kao-Lee McDonald, Ellen Dwivedi, Dhruva J. Zamir, Nasim M. Pepler, Laura Gould, Travis J. Xu, Michael Zytaruk, Nicole Medeiros, Sarah K. McIntyre, Lauralyn Tsang, Jennifer Dodek, Peter M. Winston, Brent W. Martin, Claudio Fraser, Douglas D. Weitz, Jeffrey I. Lellouche, Francois Cook, Deborah J. Marshall, John Crit Care Explor Observational Study To determine if a set of time-varying biological indicators can be used to: 1) predict the sepsis mortality risk over time and 2) generate mortality risk profiles. DESIGN: Prospective observational study. SETTING: Nine Canadian ICUs. SUBJECTS: Three-hundred fifty-six septic patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Clinical data and plasma levels of biomarkers were collected longitudinally. We used a complementary log-log model to account for the daily mortality risk of each patient until death in ICU/hospital, discharge, or 28 days after admission. The model, which is a versatile version of the Cox model for gaining longitudinal insights, created a composite indicator (the daily hazard of dying) from the “day 1” and “change” variables of six time-varying biological indicators (cell-free DNA, protein C, platelet count, creatinine, Glasgow Coma Scale score, and lactate) and a set of contextual variables (age, presence of chronic lung disease or previous brain injury, and duration of stay), achieving a high predictive power (conventional area under the curve, 0.90; 95% CI, 0.86–0.94). Including change variables avoided misleading inferences about the effects of day 1 variables, signifying the importance of the longitudinal approach. We then generated mortality risk profiles that highlight the relative contributions among the time-varying biological indicators to overall mortality risk. The tool was validated in 28 nonseptic patients from the same ICUs who became septic later and was subject to 10-fold cross-validation, achieving similarly high area under the curve. CONCLUSIONS: Using a novel version of the Cox model, we created a prognostic tool for septic patients that yields not only a predicted probability of dying but also a mortality risk profile that reveals how six time-varying biological indicators differentially and longitudinally account for the patient’s overall daily mortality risk. Wolters Kluwer Health 2019-08-01 /pmc/articles/PMC7063956/ /pubmed/32166273 http://dx.doi.org/10.1097/CCE.0000000000000032 Text en Copyright © 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Observational Study Liaw, Patricia C. Fox-Robichaud, Alison E. Liaw, Kao-Lee McDonald, Ellen Dwivedi, Dhruva J. Zamir, Nasim M. Pepler, Laura Gould, Travis J. Xu, Michael Zytaruk, Nicole Medeiros, Sarah K. McIntyre, Lauralyn Tsang, Jennifer Dodek, Peter M. Winston, Brent W. Martin, Claudio Fraser, Douglas D. Weitz, Jeffrey I. Lellouche, Francois Cook, Deborah J. Marshall, John Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach |
title | Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach |
title_full | Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach |
title_fullStr | Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach |
title_full_unstemmed | Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach |
title_short | Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach |
title_sort | mortality risk profiles for sepsis: a novel longitudinal and multivariable approach |
topic | Observational Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063956/ https://www.ncbi.nlm.nih.gov/pubmed/32166273 http://dx.doi.org/10.1097/CCE.0000000000000032 |
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