Literature DB >> 18282639

Using information on preexisting conditions to predict mortality from traumatic injury.

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

Abstract

STUDY
OBJECTIVE: Preexisting conditions have been found to be an independent predictor of mortality after trauma. However, no consensus has been reached as to what indicator of preexisting condition status should be used, and the contribution of preexisting conditions to mortality prediction models is unclear. This study aims to identify the most accurate way to model preexisting condition status to predict inhospital trauma mortality and to evaluate the potential gain of adding preexisting condition status to a standard trauma mortality prediction model.
METHODS: The study comprised all patients from the trauma registries of 4 Level I trauma centers. Information provided by individual preexisting conditions was compared to 3 commonly used summary measures: (1) absence/presence of any preexisting condition, (2) number of preexisting conditions, and (3) Charlson Comorbidity Index. The impact of adding preexisting condition status to 2 baseline risk models, the current standard Trauma and Injury Severity Score model and an improved model based on nonparametric transformations of quantitative variables, was evaluated by the area under the receiver operating characteristics curve.
RESULTS: Discrimination for predicting mortality in the improved model was as follows: baseline risk model: area under the receiver operating characteristics curve=0.935; baseline risk model+individually modeled preexisting conditions: area under the receiver operating characteristics curve=0.941; baseline risk model+presence of any preexisting condition: area under the receiver operating characteristics curve=0.937; baseline risk model+number of preexisting conditions: area under the receiver operating characteristics curve=0.939; baseline risk model+Charlson Comorbidity Index: area under the receiver operating characteristics curve=0.938.
CONCLUSION: Preexisting condition status is an independent predictor of mortality from trauma that provides a modest improvement in mortality prediction. The total number of preexisting conditions is a good summary measure of preexisting condition status. The Charlson Comorbidity Index is no better than the total number of preexisting conditions and is therefore not recommended for use in trauma mortality modeling.

Entities:  

Mesh:

Year:  2008        PMID: 18282639     DOI: 10.1016/j.annemergmed.2007.09.007

Source DB:  PubMed          Journal:  Ann Emerg Med        ISSN: 0196-0644            Impact factor:   5.721


  15 in total

1.  Denver ED Trauma Organ Failure Score predicts healthcare resource utilization in adult trauma patients.

Authors:  Jody A Vogel; W Gannon Sungar; Dowin Boatright; Jordan Ryan; Benjamin Murphy; Jesse Loar; Sabrina Adams; Jason S Haukoos
Journal:  Am J Emerg Med       Date:  2018-08-30       Impact factor: 2.469

2.  Development and validation of the mortality risk for trauma comorbidity index.

Authors:  Hilaire J Thompson; Frederick P Rivara; Avery Nathens; Jin Wang; Gregory J Jurkovich; Ellen J Mackenzie
Journal:  Ann Surg       Date:  2010-08       Impact factor: 12.969

3.  Trends in survival and early functional outcomes from hospitalized severe adult traumatic brain injuries, pennsylvania, 1998 to 2007.

Authors:  Alvaro I Sánchez; Robert T Krafty; Harold B Weiss; Andrés M Rubiano; Andrew B Peitzman; Juan Carlos Puyana
Journal:  J Head Trauma Rehabil       Date:  2012 Mar-Apr       Impact factor: 2.710

4.  Evolution of patient outcomes over 14 years in a mature, inclusive Canadian trauma system.

Authors:  Lynne Moore; Alexis F Turgeon; François Lauzier; Marcel Émond; Simon Berthelot; Julien Clément; Gilles Bourgeois; Jean Lapointe
Journal:  World J Surg       Date:  2015-06       Impact factor: 3.352

5.  Evaluation of the long-term trend in mortality from injury in a mature inclusive trauma system.

Authors:  Lynne Moore; James A Hanley; Alexis F Turgeon; André Lavoie
Journal:  World J Surg       Date:  2010-09       Impact factor: 3.352

6.  Impact of bladder, bowel and sexual dysfunction on health status of people with thoracolumbar spinal cord injuries living in the community.

Authors:  So Eyun Park; Stacy Elliott; Vanessa K Noonan; Nancy P Thorogood; Nader Fallah; Allan Aludino; Marcel F Dvorak
Journal:  J Spinal Cord Med       Date:  2016-08-31       Impact factor: 1.985

7.  Charlson comorbidity indices and in-hospital deaths in patients with hip fractures.

Authors:  Valentin Neuhaus; John King; Michiel G Hageman; David C Ring
Journal:  Clin Orthop Relat Res       Date:  2012-11-21       Impact factor: 4.176

8.  Derivation and validation of actionable quality indicators targeting reductions in complications for injury admissions.

Authors:  Abakar Idriss-Hassan; Mélanie Bérubé; Amina Belcaïd; Julien Clément; Gilles Bourgeois; Christine Rizzo; Xavier Neveu; Kahina Soltana; Jaimini Thakore; Lynne Moore
Journal:  Eur J Trauma Emerg Surg       Date:  2021-05-07       Impact factor: 3.693

9.  The off-hour effect on trauma patients requiring subspecialty intervention at a community hospital in Japan: a retrospective cohort study.

Authors:  Yuko Ono; Tokiya Ishida; Yudai Iwasaki; Yutaka Kawakami; Ryota Inokuchi; Choichiro Tase; Kazuaki Shinohara
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2015-02-10       Impact factor: 2.953

10.  Norwegian survival prediction model in trauma: modelling effects of anatomic injury, acute physiology, age, and co-morbidity.

Authors:  J M Jones; N O Skaga; S Søvik; H M Lossius; T Eken
Journal:  Acta Anaesthesiol Scand       Date:  2014-01-20       Impact factor: 2.105

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.