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Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients

PURPOSE: The purpose of this study was to develop a new prediction model to reflect the risk of mortality and severity of disease and to evaluate the ability of the developed model to predict mortality among adult burn patients. METHODS: This study included 2009 patients aged more than 18 years who...

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Autores principales: Kim, Youngmin, Kym, Dohern, Hur, Jun, Jeon, Jinwoo, Yoon, Jaechul, Yim, Haejun, Cho, Yong Suk, Chun, Wook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6364897/
https://www.ncbi.nlm.nih.gov/pubmed/30726241
http://dx.doi.org/10.1371/journal.pone.0211075
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author Kim, Youngmin
Kym, Dohern
Hur, Jun
Jeon, Jinwoo
Yoon, Jaechul
Yim, Haejun
Cho, Yong Suk
Chun, Wook
author_facet Kim, Youngmin
Kym, Dohern
Hur, Jun
Jeon, Jinwoo
Yoon, Jaechul
Yim, Haejun
Cho, Yong Suk
Chun, Wook
author_sort Kim, Youngmin
collection PubMed
description PURPOSE: The purpose of this study was to develop a new prediction model to reflect the risk of mortality and severity of disease and to evaluate the ability of the developed model to predict mortality among adult burn patients. METHODS: This study included 2009 patients aged more than 18 years who were admitted to the intensive care unit (ICU) within 24 hours after a burn. We divided the patients into two groups; those admitted from January 2007 to December 2013 were included in the derivation group and those admitted from January 2014 to September 2017 were included in the validation group. Shrinkage methods with 10-folds cross-validation were performed to identify variables and limit overfitting of the model. The discrimination was analyzed using the area under the curve (AUC) of the receiver operating characteristic curve. The Brier score, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were also calculated. The calibration was analyzed using the Hosmer-Lemeshow goodness-of-fit test (HL test). The clinical usefulness was evaluated using a decision-curve analysis. RESULTS: The Hangang model showed good calibration with the HL test (χ(2) = 8.785, p = 0.361); the highest AUC and the lowest Brier score were 0.943 and 0.068, respectively. The NRI and IDI were 0.124 (p-value = 0.003) and 0.079 (p-value <0.001) when compared with FLAMES, respectively. CONCLUSIONS: This model reflects the current risk factors of mortality among adult burn patients. Furthermore, it was a highly discriminatory and well-calibrated model for the prediction of mortality in this cohort.
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spelling pubmed-63648972019-02-22 Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients Kim, Youngmin Kym, Dohern Hur, Jun Jeon, Jinwoo Yoon, Jaechul Yim, Haejun Cho, Yong Suk Chun, Wook PLoS One Research Article PURPOSE: The purpose of this study was to develop a new prediction model to reflect the risk of mortality and severity of disease and to evaluate the ability of the developed model to predict mortality among adult burn patients. METHODS: This study included 2009 patients aged more than 18 years who were admitted to the intensive care unit (ICU) within 24 hours after a burn. We divided the patients into two groups; those admitted from January 2007 to December 2013 were included in the derivation group and those admitted from January 2014 to September 2017 were included in the validation group. Shrinkage methods with 10-folds cross-validation were performed to identify variables and limit overfitting of the model. The discrimination was analyzed using the area under the curve (AUC) of the receiver operating characteristic curve. The Brier score, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were also calculated. The calibration was analyzed using the Hosmer-Lemeshow goodness-of-fit test (HL test). The clinical usefulness was evaluated using a decision-curve analysis. RESULTS: The Hangang model showed good calibration with the HL test (χ(2) = 8.785, p = 0.361); the highest AUC and the lowest Brier score were 0.943 and 0.068, respectively. The NRI and IDI were 0.124 (p-value = 0.003) and 0.079 (p-value <0.001) when compared with FLAMES, respectively. CONCLUSIONS: This model reflects the current risk factors of mortality among adult burn patients. Furthermore, it was a highly discriminatory and well-calibrated model for the prediction of mortality in this cohort. Public Library of Science 2019-02-06 /pmc/articles/PMC6364897/ /pubmed/30726241 http://dx.doi.org/10.1371/journal.pone.0211075 Text en © 2019 Kim 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
Kim, Youngmin
Kym, Dohern
Hur, Jun
Jeon, Jinwoo
Yoon, Jaechul
Yim, Haejun
Cho, Yong Suk
Chun, Wook
Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients
title Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients
title_full Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients
title_fullStr Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients
title_full_unstemmed Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients
title_short Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients
title_sort development of a risk prediction model (hangang) and comparison with clinical severity scores in burn patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6364897/
https://www.ncbi.nlm.nih.gov/pubmed/30726241
http://dx.doi.org/10.1371/journal.pone.0211075
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