Literature DB >> 26507519

Inclusion of coexisting morbidity in a TBSA% and age based model for the prediction of mortality after burns does not increase its predictive power.

Laura Pompermaier1, Ingrid Steinvall2, Mats Fredrikson3, Folke Sjöberg4.   

Abstract

INTRODUCTION: Several models for predicting mortality have been developed for patients with burns, and the most commonly used are based on age and total body surface area (TBSA%). They often show good predictive precision as depicted by high values for area under the receiver operating characteristic curves (AUC). However the effect of coexisting morbidity on such prediction models has not to our knowledge been thoroughly examined. We hypothesised that adding it to a previously published model (based on age, TBSA%, full thickness burns, gender, and need for mechanical ventilation) would further improve its predictive power.
METHODS: We studied 772 patients admitted during the period 1997-2008 to the Linköping University Hospital, National Burn Centre with any type of burns. We defined coexisting morbidity as any of the medical conditions listed in the Charlson list, as well as psychiatric disorders or drug or alcohol misuse. We added coexisting medical conditions to the model for predicting mortality (age, TBSA%, and need for mechanical ventilation) to determine whether it improved the model as assessed by changes in deviances between the models.
RESULTS: Mean (SD) age and TBSA% was 35 (26) years and 13 (17) %, respectively. Among 725 patients who survived, 105 (14%) had one or more coexisting condition, compared with 28 (60%) among those 47 who died. The presence of coexisting conditions increased with age (p<0.001) among patients with burns. The AUC of the mortality prediction model in this study, based on the variables age, TBSA%, and need for mechanical ventilation was 0.980 (n=772); after inclusion of coexisting morbidity in the model, the AUC improved only marginally, to 0.986. The model was not significantly better either.
CONCLUSION: Adding coexisting morbidity to a model for prediction of mortality after a burn based on age, TBSA%, and the need for mechanical ventilation did not significantly improve its predictive value. This is probably because coexisting morbidity is automatically adjusted for by age in the original model.
Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Entities:  

Keywords:  Burns; Comorbidity; Mortality; Prediction model

Mesh:

Year:  2015        PMID: 26507519     DOI: 10.1016/j.burns.2015.09.017

Source DB:  PubMed          Journal:  Burns        ISSN: 0305-4179            Impact factor:   2.744


  5 in total

1.  Self-inflicted burns in a National Swedish Burn Centre: an overview.

Authors:  L Pompermaier; M Elmasry; I Steinvall
Journal:  Ann Burns Fire Disasters       Date:  2019-12-31

2.  Hyperphosphatemia is associated with high mortality in severe burns.

Authors:  George Kuo; Cheng-Chia Lee; Shih-Yi Yang; Yen-Chang Hsiao; Shiow-Shuh Chuang; Su-Wei Chang; Kun-Hua Tu; Pei-Chun Fan; Ya-Chung Tian; Yung-Chang Chen; Chih-Hsiang Chang
Journal:  PLoS One       Date:  2018-01-09       Impact factor: 3.240

3.  Multi-institutional analysis of independent predictors for burn mortality in the United States.

Authors:  Dmitry Zavlin; Vishwanath Chegireddy; Stefanos Boukovalas; Anna M Nia; Ludwik K Branski; Jeffrey D Friedman; Anthony Echo
Journal:  Burns Trauma       Date:  2018-08-22

4.  Are there any differences in the provided burn care between men and women? A retrospective study.

Authors:  Laura Pompermaier; Moustafa Elmasry; Islam Abdelrahman; Mats Fredrikson; Folke Sjöberg; Ingrid Steinvall
Journal:  Burns Trauma       Date:  2018-08-13

5.  Patient Reported Experiences at a Swedish National Burn Centre.

Authors:  Laura Pompermaier; Emma Drake Af Hagelsrum; Viktor Ydenius; Folke Sjöberg; Ingrid Steinvall; Moustafa Elmasry
Journal:  J Burn Care Res       Date:  2022-01-05       Impact factor: 1.845

  5 in total

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