Literature DB >> 15964571

Comparing logistic models based on modified GCS motor component with other prognostic tools in prediction of mortality: results of study in 7226 trauma patients.

Behzad Eftekhar1, Mohammad Reza Zarei, Mohammad Ghodsi, Koorosh Moezardalan, Moosa Zargar, Ebrahim Ketabchi.   

Abstract

A simple reproducible and sensitive prognostic trauma tool is still needed. In this article we have introduced modified GCS motor response (MGMR) and evaluated the performance of logistic models based on this variable. The records of 8452 trauma patients admitted to major hospitals of Tehran from 1999 to 2000 were analysed. 7226 records with known outcome were included in our study. Logistic models based on outcome (death versus survival) as a dependent variable and Injury Severity Score (ISS), Revised Trauma Score (RTS), Glasgow Coma Scale (GCS), GCS motor component (GMR) and MGMR (following command [=2], movement but not following [=1] command and without movement [=0]) were compared based on their accuracy and area under the Receiver Operating Characteristic (ROC) curve. The accuracy of the Trauma and Injury Severity Score (TRISS), RTS, GCS, GMR and MGMR models were almost the same. Considering both the area under the ROC curve and accuracy, the age included MGMR model was also comparable with other age included models (RTS+age, GCS+age, GMR+age). We concluded that although in some situations we need more sophisticated models, should our results be reproducible in other populations, MGMR (with or without age added) model may be of considerable practical value.

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Year:  2005        PMID: 15964571     DOI: 10.1016/j.injury.2004.12.067

Source DB:  PubMed          Journal:  Injury        ISSN: 0020-1383            Impact factor:   2.586


  9 in total

1.  Factors influencing injury severity score regarding Thai military personnel injured in mass casualty incident April 10, 2010: lessons learned from armed conflict casualties: a retrospective study.

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Journal:  BMC Emerg Med       Date:  2012-01-03

2.  A comparison of the diagnostic power of the Full Outline of Unresponsiveness scale and the Glasgow coma scale in the discharge outcome prediction of patients with traumatic brain injury admitted to the intensive care unit.

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Review 3.  Comparison of the Ability to Predict Mortality between the Injury Severity Score and the New Injury Severity Score: A Meta-Analysis.

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Journal:  Int J Environ Res Public Health       Date:  2016-08-16       Impact factor: 3.390

4.  Time distribution of injury-related in-hospital mortality in a trauma referral center in South of Iran (2010-2015).

Authors:  Hamidreza Abbasi; Shahram Bolandparvaz; Mahnaz Yadollahi; Mehrdad Anvar; Zahra Farahgol
Journal:  Medicine (Baltimore)       Date:  2017-05       Impact factor: 1.889

5.  Analysis of Shahid Rajaee hospital administrative data on injuries resulting from car accidents in Shiraz, Iran: 2011-2014 data.

Authors:  Mahnaz Yadollahi; Aida Ghiassee; Mehrdad Anvar; Hale Ghaem; Mohammad Farahmand
Journal:  Chin J Traumatol       Date:  2017-01-20

Review 6.  A Comparison between the Ability of Revised Trauma Score and Kampala Trauma Score in Predicting Mortality; a Meta-Analysis.

Authors:  Shahram Manoochehry; Masoud Vafabin; Saeid Bitaraf; Ali Amiri
Journal:  Arch Acad Emerg Med       Date:  2019-01-15

7.  Epidemiology of unintentional injury in children admitted to ICU in China mainland: a multi-center cross-sectional study.

Authors:  Jing Ye; Yiyao Bao; Jicui Zheng; Jianfeng Liang; Lei Hu; Linhua Tan
Journal:  Transl Pediatr       Date:  2022-03

Review 8.  Systematic review of predictive performance of injury severity scoring tools.

Authors:  Hideo Tohira; Ian Jacobs; David Mountain; Nick Gibson; Allen Yeo
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2012-09-10       Impact factor: 2.953

9.  Injury patterns among various age and gender groups of trauma patients in southern Iran: A cross-sectional study.

Authors:  Shahram Bolandparvaz; Mahnaz Yadollahi; Hamid Reza Abbasi; Mehrdad Anvar
Journal:  Medicine (Baltimore)       Date:  2017-10       Impact factor: 1.817

  9 in total

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