A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes

Abstract Abbreviated Injury Scale (AIS)-based systems such as injury severity score (ISS), exponential injury severity score (EISS), trauma mortality prediction model (TMPM), and injury mortality prediction (IMP), classify anatomical injuries with limited accuracy. The widely accepted alternative, t...

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Autores principales:	Muding Wang, Guohu Zhang, Degang Cong, Yunji Zeng, Wenhui Fan, Yi Shen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/087c5d5da7fc4c9a9c169f71121d5c57
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spelling	oai:doaj.org-article:087c5d5da7fc4c9a9c169f71121d5c572021-11-08T10:54:07ZA traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes10.1038/s41598-021-98558-92045-2322https://doaj.org/article/087c5d5da7fc4c9a9c169f71121d5c572021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98558-9https://doaj.org/toc/2045-2322Abstract Abbreviated Injury Scale (AIS)-based systems such as injury severity score (ISS), exponential injury severity score (EISS), trauma mortality prediction model (TMPM), and injury mortality prediction (IMP), classify anatomical injuries with limited accuracy. The widely accepted alternative, trauma and injury severity score (TRISS), improves the prediction rate by combining an anatomical index of ISS, physiological index (the Revised Trauma Score, RTS), and the age of patients. The study introduced the traumatic injury mortality prediction (TRIMP) with the inclusion of extra clinical information and aimed to compare the ability against the TRISS as predictors of survival. The hypothesis was that TRIMP would outperform TRISS in prediction power by incorporating clinically available data. This was a retrospective cohort study where a total of 1,198,885 injured patients hospitalized between 2012 and 2014 were subset from the National Trauma Data Bank (NTDB) in the United States. A TRIMP model was computed that uses AIS 2005 (AIS_05), physiological reserve and physiological response indicators. The results were analysed by examining the area under the receiver operating characteristic curve (AUC), the Hosmer–Lemeshow (HL) statistic, and the Akaike information criterion. TRIMP gave both significantly better discrimination (AUCTRIMP, 0.964; 95% confidence interval (CI), 0.962 to 0.966 and AUCTRISS, 0.923; 95% CI, 0.919 to 0.926) and calibration (HLTRIMP, 14.0; 95% CI, 7.7 to 18.8 and HLTRISS, 411; 95% CI, 332 to 492) than TRISS. Similar results were found in statistical comparisons among different body regions. TRIMP was superior to TRISS in terms of accurate of mortality prediction, TRIMP is a new and feasible scoring method in trauma research and should replace the TRISS.Muding WangGuohu ZhangDegang CongYunji ZengWenhui FanYi ShenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Muding Wang Guohu Zhang Degang Cong Yunji Zeng Wenhui Fan Yi Shen A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes
description	Abstract Abbreviated Injury Scale (AIS)-based systems such as injury severity score (ISS), exponential injury severity score (EISS), trauma mortality prediction model (TMPM), and injury mortality prediction (IMP), classify anatomical injuries with limited accuracy. The widely accepted alternative, trauma and injury severity score (TRISS), improves the prediction rate by combining an anatomical index of ISS, physiological index (the Revised Trauma Score, RTS), and the age of patients. The study introduced the traumatic injury mortality prediction (TRIMP) with the inclusion of extra clinical information and aimed to compare the ability against the TRISS as predictors of survival. The hypothesis was that TRIMP would outperform TRISS in prediction power by incorporating clinically available data. This was a retrospective cohort study where a total of 1,198,885 injured patients hospitalized between 2012 and 2014 were subset from the National Trauma Data Bank (NTDB) in the United States. A TRIMP model was computed that uses AIS 2005 (AIS_05), physiological reserve and physiological response indicators. The results were analysed by examining the area under the receiver operating characteristic curve (AUC), the Hosmer–Lemeshow (HL) statistic, and the Akaike information criterion. TRIMP gave both significantly better discrimination (AUCTRIMP, 0.964; 95% confidence interval (CI), 0.962 to 0.966 and AUCTRISS, 0.923; 95% CI, 0.919 to 0.926) and calibration (HLTRIMP, 14.0; 95% CI, 7.7 to 18.8 and HLTRISS, 411; 95% CI, 332 to 492) than TRISS. Similar results were found in statistical comparisons among different body regions. TRIMP was superior to TRISS in terms of accurate of mortality prediction, TRIMP is a new and feasible scoring method in trauma research and should replace the TRISS.
format	article
author	Muding Wang Guohu Zhang Degang Cong Yunji Zeng Wenhui Fan Yi Shen
author_facet	Muding Wang Guohu Zhang Degang Cong Yunji Zeng Wenhui Fan Yi Shen
author_sort	Muding Wang
title	A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes
title_short	A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes
title_full	A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes
title_fullStr	A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes
title_full_unstemmed	A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes
title_sort	traumatic injury mortality prediction (trimp) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/087c5d5da7fc4c9a9c169f71121d5c57
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A traumatic injury mortality prediction (TRIMP) based on a comprehensive assessment of abbreviated injury scale 2005 predot codes

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