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...
Autores principales: | , , , , , |
---|---|
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 |