Comparison of APACHE II, trauma score, and injury severity score as predictors of outcome in critically injured trauma patients

1993 ◽  
Vol 166 (3) ◽  
pp. 244-247 ◽  
Author(s):  
Robert Rutledge ◽  
Samir Fakhry ◽  
Edmond Rutherford ◽  
Farid Muakkassa ◽  
Anthony Meyer
Keyword(s):  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Apache Ii ◽  
Trauma Patients ◽  
Predictors Of Outcome ◽  
Trauma Score

scholarly journals The incidence of geriatric trauma is increasing and comparison of different scoring tools for the prediction of in-hospital mortality in geriatric trauma patients

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Libing Jiang ◽  
Zhongjun Zheng ◽  
Mao Zhang
Keyword(s):  
Hospital Mortality ◽  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Apache Ii ◽  
Geriatric Trauma ◽  
Trauma Patients ◽  
Survival Group ◽  
Saps Ii ◽  
Scoring Tools

Abstract Purpose The study aimed to examine the changing incidence of geriatric trauma and evaluate the predictive ability of different scoring tools for in-hospital mortality in geriatric trauma patients. Methods Annual reports released by the National Trauma Database (NTDB) in the USA from 2005 to 2015 and the Trauma Register DGU® in Germany from 1994 to 2012 were analyzed to examine the changing incidence of geriatric trauma. Secondary analysis of a single-center cohort study conducted among 311 severely injured geriatric trauma patients in a level I trauma center in Switzerland was completed. According to the in-hospital survival status, patients were divided into the survival and non-survival group. The differences of the ISS (injury severity score), NISS (new injury severity score), TRISS (Trauma and Injury Severity Score), APACHE II (Acute Physiology and Chronic Health Evaluation II), and SPAS II (simplified acute physiology score II) between two groups were evaluated. Then, the areas under the receiver-operating characteristic curve (AUC-ROC) of different scoring tools for the prediction of in-hospital mortality in geriatric trauma patients were calculated. Results The analysis of the NTDB showed that the increase in the number of geriatric trauma ranged from 18 to 30% between 2005 and 2015. The analysis of the DGU® showed that the mean age of trauma patients rose from 39.11 in 1993 to 51.10 in 2013, and the proportion of patients aged ≥ 60 years rose from 16.5 to 37.5%. The findings from the secondary analysis showed that 164 (52.73%) patients died in the hospital. The ISS, NISS, APACHE II, and SAPS II in the death group were significantly higher than those in the survival group, and the TRISS in the death group was significantly lower than those in the survival group. The AUCs of the ISS, NISS, TRISS, APACHE II, and SAPS II for the prediction of in-hospital mortality in geriatric trauma patients were 0.807, 0.850, 0.828, 0.715, and 0.725, respectively. Conclusion The total number of geriatric trauma is increasing as the population ages. The accuracy of ISS, NISS and TRISS was higher than the APACHE II and SAPS II for the prediction of in-hospital mortality in geriatric trauma patients.

Non-Selective Thoracic Computed Tomography in Trauma Patients Results in Injury Severity Score Inflation

2021 ◽  
pp. 000313482110249
Author(s):  
Leonardo Alaniz ◽  
Omaer Muttalib ◽  
Juan Hoyos ◽  
Cesar Figueroa ◽  
Cristobal Barrios
Keyword(s):  
Computed Tomography ◽  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Treatment Plan ◽  
Mortality Prediction ◽  
Trauma Patients ◽  
Mortality Benefit ◽  
Severity Scores ◽  
Score Inflation

Introduction Extensive research relying on Injury Severity Scores (ISS) reports a mortality benefit from routine non-selective thoracic CTs (an integral part of pan-computed tomography (pan-CT)s). Recent research suggests this mortality benefit may be artifact. We hypothesized that the use of pan-CTs inflates ISS categorization in patients, artificially affecting admission rates and apparent mortality benefit. Methods Eight hundred and eleven patients were identified with an ISS >15 with significant findings in the chest area. Patient charts were reviewed and scores were adjusted to exclude only occult injuries that did not affect treatment plan. Pearson chi-square tests and multivariable logistic regression were used to compare adjusted cases vs non-adjusted cases. Results After adjusting for inflation, 388 (47.8%) patients remained in the same ISS category, 378 (46.6%) were reclassified into 1 lower ISS category, and 45 (5.6%) patients were reclassified into 2 lower ISS categories. Patients reclassified by 1 category had a lower rate of mortality ( P < 0.001), lower median total hospital LOS ( P < .001), ICU days ( P < .001), and ventilator days ( P = 0.008), compared to those that remained in the same ISS category. Conclusion Injury Severity Score inflation artificially increases survival rate, perpetuating the increased use of pan-CTs. This artifact has been propagated by outdated mortality prediction calculation methods. Thus, prospective evaluations of algorithms for more selective CT scanning are warranted.

Predictors of blunt diaphragm injury in Australia

Trauma ◽  
2021 ◽  
pp. 146040862110418
Author(s):  
Annelise M Cocco ◽  
Vignesh Ratnaraj ◽  
Benjamin PT Loveday ◽  
Kellie Gumm ◽  
Phillip Antippa ◽  
...  
Keyword(s):  
Injury Severity Score ◽  
Severity Score ◽  
Major Trauma ◽  
Injury Severity ◽  
Rib Fractures ◽  
Organ Injury ◽  
Trauma Patients ◽  
Missed Injury ◽  
Diaphragm Injury ◽  
Trauma Service

Introduction Blunt diaphragm injury (BDI) is an uncommon, potentially fatal consequence of blunt torso injury. While associations between BDI and other factors such as mechanism of injury or other injuries have been described elsewhere, little recent research has been done in Australia into BDI. The aims of this study were to determine the incidence rate of BDI in our centre, identify how it was diagnosed, determine rates of missed injury and identify predictive factors for BDI. The hypothesis was that patients with BDI would significantly differ to those without BDI. Methods All major trauma patients with blunt torso injuries at our Level 1 major trauma service from 2010 to 2018 were included. Data for patient demographics, other injuries, diagnosis and treatment of BDI were extracted. Patients with BDI were compared with patients without BDI in order to identify differences that could be used to predict BDI in future patients. Results Of 5190 patients with a blunt torso injury, 51 (0.98%) had a BDI at a mean age of 53 ± 19.6 years, and median Injury Severity Score (ISS) of 27(IQR 21–38.5) compared with 5139 patients with a mean age of 48.2 ± 20.7 years and median ISS of 21.9(IQR 14–26) who did not have a BDI. The diagnosis of BDI was made at CT ( n = 35), surgery ( n = 14) or autopsy ( n = 2). Blunt diaphragm injury was missed on index imaging for 11 of 43 patients (25.6%). On multivariate analysis, each point increase in ISS (OR 1.03, p = 0.02); rib fractures (OR 4.65, p = 0.004); splenic injury (OR 2.60, p = 0.004); and liver injury (OR 2.78, p = 0.003) were independently associated with BDI. Conclusion Injury Severity Score, rib fractures and solid abdominal organ injury increase the likelihood of BDI. In patients with these injuries, BDI should be considered even in the presence of normal CT findings.

scholarly journals Desempenho dos ajustes do Trauma and Injury Severity Score (TRISS): revisão integrativa

2015 ◽  
Vol 49 (spe) ◽  
pp. 138-146 ◽  
Author(s):  
Cristiane de Alencar Domingues ◽  
Lilia de Souza Nogueira ◽  
Cristina Helena Costanti Settervall ◽  
Regina Marcia Cardoso de Sousa
Keyword(s):  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Revised Trauma Score ◽  
Trauma Score ◽  
Trauma And Injury

RESUMO Objetivo identificar estudos que realizaram ajustes na equação do Trauma and InjurySeverity Score (TRISS) e compararam a capacidade discriminatória da equação modificada com a original. Método Revisão integrativa de pesquisas publicadas entre 1990 e 2014 nas bases de dados LILACS, MEDLINE, PubMed e SciELO utilizando-se a palavra TRISS. Resultados foram incluídos 32 estudos na revisão. Dos 67 ajustes de equações do TRISS identificados, 35 (52,2%) resultaram em melhora na acurácia do índice para predizer a probabilidade de sobrevida de vítimas de trauma. Ajustes dos coeficientes do TRISS à população de estudo foram frequentes, mas nem sempre melhoraram a capacidade preditiva dos modelos analisados. A substituição de variáveis fisiológicas do Revised Trauma Score (RTS) e modificações do Injury Severity Score (ISS) na equação original tiveram desempenho variado. A mudança na forma de inclusão da idade na equação, assim como a inserção do gênero, comorbidades e mecanismo do trauma apresentaram tendência de melhora do desempenho do TRISS. Conclusão Diferentes propostas de ajustes no TRISS foram identificadas nesta revisão e indicaram, principalmente, fragilidades do RTS no modelo original e necessidade de alteração da forma de inclusão da idade na equação para melhora da capacidade preditiva do índice.

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