Trauma and Injury Severity Score (TRISS): Is it time for variable re-categorisations and re-characterisations?

Schluter, Philip J. (2011) Trauma and Injury Severity Score (TRISS): Is it time for variable re-categorisations and re-characterisations?. Injury, 42 1: 83-89. doi:10.1016/j.injury.2010.08.036

Author Schluter, Philip J.
Title Trauma and Injury Severity Score (TRISS): Is it time for variable re-categorisations and re-characterisations?
Journal name Injury   Check publisher's open access policy
ISSN 0020-1383
Publication date 2011-01
Year available 2010
Sub-type Article (original research)
DOI 10.1016/j.injury.2010.08.036
Volume 42
Issue 1
Start page 83
End page 89
Total pages 7
Editor S. J. Krikler
Place of publication Oxford, U.K.
Publisher Elsevier Science
Collection year 2011
Language eng
Formatted abstract
Background: Despite its limitations, the Trauma and Injury Severity Score (TRISS) continues to be the most commonly used tool for benchmarking trauma outcome. Since its inception, considerable energy has been devoted to improving TRISS. However, there has been no investigation into the classification or characterisation of the TRISS variables. Using a major nationally representative database, this study aims to explore the adequacy of the existing TRISS model by investigating variable re-categorisations and alternative characterisations in a logistic model used to predict survival in adults after traumatic injury.
Materials and methods: Data were obtained from the National Trauma Data Bank National Sample Project (NSP). Each variable in the TRISS model was related to discharge status and various categorisations considered using weighted logistic regression. Categorisations were treated nominally, using a series of indicator variables. For each variable and classification level, the best category combination was ascertained using the Bayesian Information Criterion (BIC). All best 5-category classified TRISS variables were combined, as were all best 10-category classified TRISS variables, and their predictive performance assessed against two conventionally defined TRISS models on the unweighted NSP sample using area under the Receiver Operating Characteristic curve (AUC) and BIC statistics.
Results: Overall, the weighted sample included 1,124,001 adults with injury events and known discharge status, of whom 1,061,709 (94.5%) were alive at discharge. When separately related to discharge status, each re-classified TRISS variable yielded a superior BIC statistic to its original specification. When investigating predictive performance, complete information was available for 167,239 (79.9%) adults with blunt and 20,643 (82.3%) adults with penetrating injury mechanisms. AUC and BIC estimates for the re-classified TRISS models were superior to the conventionally defined TRISS models. While having better predictive precision, the complexity associated with the best 10-category model resulted in the best 5-category model being preferred for penetrating mechanism injuries and being negligibly inferior for blunt mechanism injuries. Discussion: Substantial improvements in the predictive power of TRISS were demonstrated by re-classifying the component variables and treating the variable categories nominally. However, before a new TRISS model with updated coefficients can be published, variable interactions and the effect of missing data needs thorough statistical evaluation.
© 2010.
Keyword Revision
Trauma and Injury Severity Score
Traumatic injury
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online 20 September 2010.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
School of Nursing, Midwifery and Social Work Publications
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Created: Tue, 30 Nov 2010, 11:54:54 EST by Vicki Percival on behalf of School of Nursing, Midwifery and Social Work