Cargando…

Predicting mortality in severe polytrauma with limited resources

BACKGROUND: Objective evaluation of the severity of injured patients is crucial for the adequate triage, decision-making, operative and intensive care management, prevention, outcome studies, and system quality assessment. This study aimed to compare six, widely-used, trauma scores as predictors of...

Descripción completa

Detalles Bibliográficos
Autores principales: Mijaljica, Daniel Rajko, Gregoric, Pavle, Ivancevic, Nenad, Pavlovic, Vedrana, Jovanovic, Bojan, Djukic, Vladimir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Kare Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10277369/
https://www.ncbi.nlm.nih.gov/pubmed/36169468
http://dx.doi.org/10.14744/tjtes.2021.70138
_version_ 1785060263753416704
author Mijaljica, Daniel Rajko
Gregoric, Pavle
Ivancevic, Nenad
Pavlovic, Vedrana
Jovanovic, Bojan
Djukic, Vladimir
author_facet Mijaljica, Daniel Rajko
Gregoric, Pavle
Ivancevic, Nenad
Pavlovic, Vedrana
Jovanovic, Bojan
Djukic, Vladimir
author_sort Mijaljica, Daniel Rajko
collection PubMed
description BACKGROUND: Objective evaluation of the severity of injured patients is crucial for the adequate triage, decision-making, operative and intensive care management, prevention, outcome studies, and system quality assessment. This study aimed to compare six, widely-used, trauma scores as predictors of mortality, and to identify the most powerful among them in limited-resources settin. METHODS: Seventy-five polytraumatized patients, admitted to the Intensive care unit (ICU) of the Clinic for Emergency Surgery (Level 1 trauma center, CSS Belgrade) from June 2018 to August 2020, were included in the study. The inclusion criteria were age ≥16, Injury Severity Score (ISS) ≥16, and Sequential Organ Failure Assessment (SOFA) ≥5 points. Scores were evaluated using logistic regression model and analysis of areas under the receiver operating characteristic curve (AUC). RESULTS: During the 26 months period, highly selected cases, mostly of blunt trauma (97.3%), due to a road traffic accident (68%) and free-falls (25.3%), were included in the study. Surgery was indicated in 56 (74.7%) and non-operative treatment in 19 (25.3%) cases, with overall mortality rate at 36%. Logistic regression analysis demonstrated that all six trauma scores (ISS, NISS, Acute Physiologic Assessment and Chronic Health Evaluation [APACHE 2], SOFA, Trauma ISS [TRISS], and Kampala Trauma Score [KTS]) were significant mortality predictors (p<0.001). Observed cutoff values for ISS: 39.5, NISS: 42, APACHE 2: 25, SOFA 6.5 points are predictive for mortality in non-survivors. A multivariate analysis showed that the most powerful mortality predictors are TRISS and APACHE 2 with AUCs: 0.9 and 0.866. CONCLUSION: According to our study, the most powerful mortality predictors are APACHE 2 and TRISS, even in limited-resources hospital settings, while statistically significant KTS did not perform as expected. We propose the appliance of the KTS, as the tool for exploiting “golden hour,” ISS or NISS during admission stage and APACHE 2 or TRISS for use in the first 24 h after admission to ICU.
format Online
Article
Text
id pubmed-10277369
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Kare Publishing
record_format MEDLINE/PubMed
spelling pubmed-102773692023-06-20 Predicting mortality in severe polytrauma with limited resources Mijaljica, Daniel Rajko Gregoric, Pavle Ivancevic, Nenad Pavlovic, Vedrana Jovanovic, Bojan Djukic, Vladimir Ulus Travma Acil Cerrahi Derg Original Article BACKGROUND: Objective evaluation of the severity of injured patients is crucial for the adequate triage, decision-making, operative and intensive care management, prevention, outcome studies, and system quality assessment. This study aimed to compare six, widely-used, trauma scores as predictors of mortality, and to identify the most powerful among them in limited-resources settin. METHODS: Seventy-five polytraumatized patients, admitted to the Intensive care unit (ICU) of the Clinic for Emergency Surgery (Level 1 trauma center, CSS Belgrade) from June 2018 to August 2020, were included in the study. The inclusion criteria were age ≥16, Injury Severity Score (ISS) ≥16, and Sequential Organ Failure Assessment (SOFA) ≥5 points. Scores were evaluated using logistic regression model and analysis of areas under the receiver operating characteristic curve (AUC). RESULTS: During the 26 months period, highly selected cases, mostly of blunt trauma (97.3%), due to a road traffic accident (68%) and free-falls (25.3%), were included in the study. Surgery was indicated in 56 (74.7%) and non-operative treatment in 19 (25.3%) cases, with overall mortality rate at 36%. Logistic regression analysis demonstrated that all six trauma scores (ISS, NISS, Acute Physiologic Assessment and Chronic Health Evaluation [APACHE 2], SOFA, Trauma ISS [TRISS], and Kampala Trauma Score [KTS]) were significant mortality predictors (p<0.001). Observed cutoff values for ISS: 39.5, NISS: 42, APACHE 2: 25, SOFA 6.5 points are predictive for mortality in non-survivors. A multivariate analysis showed that the most powerful mortality predictors are TRISS and APACHE 2 with AUCs: 0.9 and 0.866. CONCLUSION: According to our study, the most powerful mortality predictors are APACHE 2 and TRISS, even in limited-resources hospital settings, while statistically significant KTS did not perform as expected. We propose the appliance of the KTS, as the tool for exploiting “golden hour,” ISS or NISS during admission stage and APACHE 2 or TRISS for use in the first 24 h after admission to ICU. Kare Publishing 2022-10-03 /pmc/articles/PMC10277369/ /pubmed/36169468 http://dx.doi.org/10.14744/tjtes.2021.70138 Text en Copyright © 2022 Turkish Journal of Trauma and Emergency Surgery https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
spellingShingle Original Article
Mijaljica, Daniel Rajko
Gregoric, Pavle
Ivancevic, Nenad
Pavlovic, Vedrana
Jovanovic, Bojan
Djukic, Vladimir
Predicting mortality in severe polytrauma with limited resources
title Predicting mortality in severe polytrauma with limited resources
title_full Predicting mortality in severe polytrauma with limited resources
title_fullStr Predicting mortality in severe polytrauma with limited resources
title_full_unstemmed Predicting mortality in severe polytrauma with limited resources
title_short Predicting mortality in severe polytrauma with limited resources
title_sort predicting mortality in severe polytrauma with limited resources
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10277369/
https://www.ncbi.nlm.nih.gov/pubmed/36169468
http://dx.doi.org/10.14744/tjtes.2021.70138
work_keys_str_mv AT mijaljicadanielrajko predictingmortalityinseverepolytraumawithlimitedresources
AT gregoricpavle predictingmortalityinseverepolytraumawithlimitedresources
AT ivancevicnenad predictingmortalityinseverepolytraumawithlimitedresources
AT pavlovicvedrana predictingmortalityinseverepolytraumawithlimitedresources
AT jovanovicbojan predictingmortalityinseverepolytraumawithlimitedresources
AT djukicvladimir predictingmortalityinseverepolytraumawithlimitedresources