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Development and performance of a novel vasopressor-driven mortality prediction model in septic shock

BACKGROUND: Vasoactive medications are essential in septic shock, but are not fully incorporated into current mortality prediction risk scores. We sought to develop a novel mortality prediction model for septic shock incorporating quantitative vasoactive medication usage. METHODS: Quantitative vasop...

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Autores principales: Vallabhajosyula, Saraschandra, Jentzer, Jacob C., Kotecha, Aditya A., Murphree, Dennis H., Barreto, Erin F., Khanna, Ashish K., Iyer, Vivek N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250607/
https://www.ncbi.nlm.nih.gov/pubmed/30467807
http://dx.doi.org/10.1186/s13613-018-0459-6
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author Vallabhajosyula, Saraschandra
Jentzer, Jacob C.
Kotecha, Aditya A.
Murphree, Dennis H.
Barreto, Erin F.
Khanna, Ashish K.
Iyer, Vivek N.
author_facet Vallabhajosyula, Saraschandra
Jentzer, Jacob C.
Kotecha, Aditya A.
Murphree, Dennis H.
Barreto, Erin F.
Khanna, Ashish K.
Iyer, Vivek N.
author_sort Vallabhajosyula, Saraschandra
collection PubMed
description BACKGROUND: Vasoactive medications are essential in septic shock, but are not fully incorporated into current mortality prediction risk scores. We sought to develop a novel mortality prediction model for septic shock incorporating quantitative vasoactive medication usage. METHODS: Quantitative vasopressor use was calculated in a cohort of 5352 septic shock patients and compared using norepinephrine equivalents (NEE), cumulative vasopressor index and the vasoactive inotrope score models. Having best discrimination prediction, log(10)NEE was selected for further development of a novel prediction model for 28-day and 1-year mortality via backward stepwise logistic regression. This model termed ‘MAVIC’ (Mechanical ventilation, Acute Physiology And Chronic Health Evaluation-III, Vasopressors, Inotropes, Charlson comorbidity index) was then compared to Acute Physiology And Chronic Health Evaluation-III (APACHE-III) and Sequential Organ Failure Assessment (SOFA) scores in an independent validation cohort for its accuracy in predicting 28-day and 1-year mortality. MEASUREMENTS AND MAIN RESULTS: The MAVIC model was superior to the APACHE-III and SOFA scores in its ability to predict 28-day mortality (area under receiver operating characteristic curve [AUROC] 0.73 vs. 0.66 and 0.60) and 1-year mortality (AUROC 0.74 vs. 0.66 and 0.60), respectively. CONCLUSIONS: The incorporation of quantitative vasopressor usage into a novel ‘MAVIC’ model results in superior 28-day and 1-year mortality risk prediction in a large cohort of patients with septic shock.
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spelling pubmed-62506072018-12-06 Development and performance of a novel vasopressor-driven mortality prediction model in septic shock Vallabhajosyula, Saraschandra Jentzer, Jacob C. Kotecha, Aditya A. Murphree, Dennis H. Barreto, Erin F. Khanna, Ashish K. Iyer, Vivek N. Ann Intensive Care Research BACKGROUND: Vasoactive medications are essential in septic shock, but are not fully incorporated into current mortality prediction risk scores. We sought to develop a novel mortality prediction model for septic shock incorporating quantitative vasoactive medication usage. METHODS: Quantitative vasopressor use was calculated in a cohort of 5352 septic shock patients and compared using norepinephrine equivalents (NEE), cumulative vasopressor index and the vasoactive inotrope score models. Having best discrimination prediction, log(10)NEE was selected for further development of a novel prediction model for 28-day and 1-year mortality via backward stepwise logistic regression. This model termed ‘MAVIC’ (Mechanical ventilation, Acute Physiology And Chronic Health Evaluation-III, Vasopressors, Inotropes, Charlson comorbidity index) was then compared to Acute Physiology And Chronic Health Evaluation-III (APACHE-III) and Sequential Organ Failure Assessment (SOFA) scores in an independent validation cohort for its accuracy in predicting 28-day and 1-year mortality. MEASUREMENTS AND MAIN RESULTS: The MAVIC model was superior to the APACHE-III and SOFA scores in its ability to predict 28-day mortality (area under receiver operating characteristic curve [AUROC] 0.73 vs. 0.66 and 0.60) and 1-year mortality (AUROC 0.74 vs. 0.66 and 0.60), respectively. CONCLUSIONS: The incorporation of quantitative vasopressor usage into a novel ‘MAVIC’ model results in superior 28-day and 1-year mortality risk prediction in a large cohort of patients with septic shock. Springer International Publishing 2018-11-22 /pmc/articles/PMC6250607/ /pubmed/30467807 http://dx.doi.org/10.1186/s13613-018-0459-6 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.
spellingShingle Research
Vallabhajosyula, Saraschandra
Jentzer, Jacob C.
Kotecha, Aditya A.
Murphree, Dennis H.
Barreto, Erin F.
Khanna, Ashish K.
Iyer, Vivek N.
Development and performance of a novel vasopressor-driven mortality prediction model in septic shock
title Development and performance of a novel vasopressor-driven mortality prediction model in septic shock
title_full Development and performance of a novel vasopressor-driven mortality prediction model in septic shock
title_fullStr Development and performance of a novel vasopressor-driven mortality prediction model in septic shock
title_full_unstemmed Development and performance of a novel vasopressor-driven mortality prediction model in septic shock
title_short Development and performance of a novel vasopressor-driven mortality prediction model in septic shock
title_sort development and performance of a novel vasopressor-driven mortality prediction model in septic shock
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250607/
https://www.ncbi.nlm.nih.gov/pubmed/30467807
http://dx.doi.org/10.1186/s13613-018-0459-6
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