Literature DB >> 16967013

Unification of the revised trauma score.

Lynne Moore1, André Lavoie, Belkacem Abdous, Natalie Le Sage, Moishe Liberman, Eric Bergeron, Marcel Emond.   

Abstract

BACKGROUND: The Revised Trauma Score (RTS) calculated with Major Outcome Trauma Study weights (MTOS-RTS) is currently the standard physiologic severity score in trauma research and quality control. It is often confused with the Triage-RTS (T-RTS), a version that is easier to calculate but only intended for clinical triage.
OBJECTIVES: To compare the accuracy of the MTOS-RTS to the RTS calculated with weights derived from the study population (POP-RTS) and the T-RTS, for predicting mortality in a trauma population.
METHODS: The study population consists of 22,388 patients, drawn from the trauma registries of three Level I trauma centers. The predictive accuracy of the MTOS-RTS, POP-RTS, and the T-RTS were compared using measures of discrimination and model fit from logistic regression models.
RESULTS: The MTOS-RTS, the POP-RTS, and the T-RTS had the same discrimination (Area under the Receiver Operating Curve [AUC] = 0.841). The POP-RTS and the T-RTS had a slightly better model fit than the MTOS-RTS (AIC = 8010, 8010, and 8067, respectively). The T-RTS had equal discrimination and equal or better model fit than the MTOS-RTS in the whole sample, in each of the three trauma centers and in the population of patients with severe head trauma. The T-RTS was also equivalent to the POP-RTS in all of these population sub-groups.
CONCLUSIONS: The T-RTS could replace the MTOS-RTS as the standard physiologic severity score for trauma outcome prediction. The advantages of using the T-RTS over the MTOS-RTS are ease of calculation, the need for only one measure for triage and mortality prediction purposes and universal adaptation to a broad range of trauma populations.

Entities:  

Mesh:

Year:  2006        PMID: 16967013     DOI: 10.1097/01.ta.0000197906.28846.87

Source DB:  PubMed          Journal:  J Trauma        ISSN: 0022-5282


  14 in total

1.  Predictors of hypofibrinogenemia in blunt trauma patients on admission.

Authors:  Yoshinobu Kimura; Saori Kimura; Shinzou Sumita; Michiaki Yamakage
Journal:  J Anesth       Date:  2014-08-12       Impact factor: 2.078

2.  [Emergency mission documentation in simulated care. Video-based error analysis].

Authors:  S Bergrath; D Rörtgen; M Skorning; H Fischermann; S K Beckers; C Mutscher; J C Brokmann; R Rossaint
Journal:  Anaesthesist       Date:  2010-09-19       Impact factor: 1.041

3.  The role of trauma scoring in developing trauma clinical governance in the Defence Medical Services.

Authors:  R J Russell; T J Hodgetts; J McLeod; K Starkey; P Mahoney; K Harrison; E Bell
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2011-01-27       Impact factor: 6.237

4.  In search of benchmarking for mortality following multiple trauma: a Swiss trauma center experience.

Authors:  Ida Füglistaler-Montali; Corinna Attenberger; Philipp Füglistaler; Augustinus L Jacob; Felix Amsler; Thomas Gross
Journal:  World J Surg       Date:  2009-11       Impact factor: 3.352

5.  Revisiting the validity of APACHE II in the trauma ICU: improved risk stratification in critically injured adults.

Authors:  Lesly A Dossett; Leigh Anne Redhage; Robert G Sawyer; Addison K May
Journal:  Injury       Date:  2009-06-16       Impact factor: 2.586

6.  Predictors of mortality in pediatric trauma: experiences of a level 1 trauma center and an assessment of the International Classification Injury Severity Score (ICISS).

Authors:  Casey J Allen; Amy E Wagenaar; Davis B Horkan; Daniel J Baldor; William M Hannay; Jun Tashiro; Nicholas Namias; Juan E Sola
Journal:  Pediatr Surg Int       Date:  2016-06-02       Impact factor: 1.827

7.  Revised trauma scoring system to predict in-hospital mortality in the emergency department: Glasgow Coma Scale, Age, and Systolic Blood Pressure score.

Authors:  Yutaka Kondo; Toshikazu Abe; Kiyotaka Kohshi; Yasuharu Tokuda; E Francis Cook; Ichiro Kukita
Journal:  Crit Care       Date:  2011-08-10       Impact factor: 9.097

Review 8.  Prognostic models for the early care of trauma patients: a systematic review.

Authors:  Marius Rehn; Pablo Perel; Karen Blackhall; Hans Morten Lossius
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2011-03-20       Impact factor: 2.953

9.  Validating performance of TRISS, TARN and NORMIT survival prediction models in a Norwegian trauma population.

Authors:  N O Skaga; T Eken; S Søvik
Journal:  Acta Anaesthesiol Scand       Date:  2017-11-08       Impact factor: 2.105

Review 10.  Risk stratification tools in emergency general surgery.

Authors:  Joaquim Michael Havens; Alexandra B Columbus; Anupamaa J Seshadri; Carlos V R Brown; Gail T Tominaga; Nathan T Mowery; Marie Crandall
Journal:  Trauma Surg Acute Care Open       Date:  2018-04-29
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