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.

scholarly journals Change in Age Distribution of the Injuries and Comparison of Different Scoring Tools in Predicting Mortality Among Geriatric Trauma Patients

2020 ◽  
Author(s):  
Libing Jiang ◽  
Zhongjun Zheng ◽  
Mao Zhang
Keyword(s):  
Hospital Mortality ◽  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Geriatric Trauma ◽  
Trauma Patients ◽  
Survival Group ◽  
Elderly Trauma Patients ◽  
Scoring Tools ◽  
Death Group

Abstract Purpose: The aim of this study was to describe the age trend of trauma patients and to compare different scoring tools to predict in-hospital mortality in elderly trauma patients.Methods: National Trauma Database (NTDB) in the United States from 2005 to 2015 and the Trauma Register DGU® in German from 1994 to 2012 was searched to describe age change of trauma patients. Then we secondly analyzed the data published in http://datadryad.org/. According to the in-hospital survival status, patients were divided into survival group and non-survival group. Receiver Operating Characteristic Curve (ROC) analysis was used to evaluated the value of ISS (injury severity score); NISS (new injury severity score), APACHE Ⅱ (Acute Physiology and Chronic Health Evaluation Ⅱ), SPAS Ⅱ (simplified acute physiology score Ⅱ) and TRISS (Trauma and Injury Severity Score) in predicting in-hospital mortality among geriatric trauma patients.Results:The analysis of NTDB showed the percentage of geriatric trauma has increased from 0.18 to 0.30, 2005-2015. The analysis of DGU showed the mean age rose from 39.11 in 1993 to 51.10 in 2013, and the percentage of patients aged ≥60 rose from 16.5% to 37.5%. A total of 311 patients aged more than 65 years were secondly analyzed. One hundred and sixty-four (52.73%) patients died in the hospital. ISS, NISS, APACHE, and SAPS in the death group were significantly higher than those in the survival group, but TRISS in the death group was significantly lower than those in the survival group. The AUC of APACHE Ⅱ was 0.715, ISS was 0.807, NISS was 0.850, SPAS Ⅱ was 0.725, and TRISS was 0.828.Conclusion:The increasing number of trauma in the elderly is a challenge for current and future trauma management. Compared with APACHE and SAPS, ISS, NISS and TRISS are more suitable for predicting in-hospital mortality in elderly trauma patients.

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 ◽  
Author(s):  
Libing Jiang ◽  
Zhongjun Zheng ◽  
Mao Zhang
Keyword(s):  
Hospital Mortality ◽  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Secondary Analysis ◽  
Geriatric Trauma ◽  
Trauma Patients ◽  
Survival Group ◽  
Scoring Tools ◽  
Death Group

Abstract Purpose: The study aimed to test the incidence of geriatric trauma is increasing and evaluate different scoring tools for the prediction of in-hospital mortality in geriatric trauma patients.Methods: Part 1: Annual reports released by the National Trauma Database (NTDB) in the United States from 2005 to 2015 and the Trauma Register DGU® in Germany from 1994 to 2012 were analyzed to test the incidence of geriatric trauma is increasing. Part 2: 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: Part 1: 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%. Part 2: 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.

scholarly journals Change in age distribution of the injuries and comparison of different scoring tools in predicting mortality among geriatric trauma patients

2020 ◽  
Author(s):  
Libing Jiang ◽  
Zhongjun Zheng ◽  
Mao Zhang
Keyword(s):  
Hospital Mortality ◽  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Secondary Analysis ◽  
Geriatric Trauma ◽  
Trauma Patients ◽  
Survival Group ◽  
Change Tendency ◽  
Death Group

Abstract Purpose: The aim of this study was to describe the age change tendency of trauma patients and to test the accuracy of different scoring tools in prediction of in-hospital mortality in case of geriatric trauma.Methods: Annual reports released by the National Trauma Database (NTDB) in the United States from 2005 to 2015 and the Trauma Register DGU® in German from 1994 to 2012 were used to describe the age change tendency of trauma patients. 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 survival group and non-survival group. Receiver Operating Characteristic Curve (ROC) analysis was used to evaluated the predictive performance of the ISS (injury severity score); NISS (new injury severity score), APACHE Ⅱ (Acute Physiology and Chronic Health Evaluation Ⅱ), SPAS Ⅱ (simplified acute physiology score Ⅱ) and TRISS (Trauma and Injury Severity Score) in prediction of in-hospital mortality among geriatric trauma patients. Results: The analysis of the NTDB showed the proportion of geriatric trauma increased from 18% to 30% from 2005 to 2015. The analysis of the DGU® showed the mean age of trauma patients rose from 39.11 in 1993 to 51.10 in 2013, and the proportion of patients aged ≥60 rose from 16.5% to 37.5%. The secondary analysis indicated one hundred and sixty-four (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 AUC of the ISS, NISS, TRISS, APACHE Ⅱ, and SAPS Ⅱ was 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 accuracy of the APACHE Ⅱ and SAPS Ⅱ to predict in-hospital mortality in case of geriatric trauma.

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 Early experience of a regional trauma center in Gangwon province: First step toward organizing a regional trauma system

2019 ◽  
Vol 27 (4) ◽  
pp. 202-210
Author(s):  
Kwangmin Kim ◽  
Hongjin Shim ◽  
Pil Young Jung ◽  
Seongyup Kim ◽  
Hui-Jae Bang ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Injury Severity Score ◽  
Severity Score ◽  
Trauma Center ◽  
Injury Severity ◽  
Trauma System ◽  
Mortality Rates ◽  
Trauma Patients ◽  
Before And After ◽  
The Impact

Background: The Korean Ministry of Health and Welfare decided to establish a trauma medical service system to reduce preventable deaths. OO hospital in Gangwon Province was selected as a regional trauma center and was inaugurated in 2015. Objectives: This study examines the impact of this center, comparing mortality and other variables before and after inaugurating the center. Methods: Severely injured patients (injury severity score > 15) presenting to OO hospital between January 2014 and December 2016 were enrolled and categorized into two groups: before trauma center (n = 365) and after trauma center (n = 904). Patient characteristics, variables, and patient outcomes (including mortality rate) before and after the establishment of trauma centers were compared accordingly for both groups. Risk factors for in-hospital mortality were also identified. Results: Probability of survival using trauma and injury severity score (%) method was significantly lower in the after trauma center group (81.3 ± 26.1) than in the before trauma center group (84.7 ± 21.0) (p = 0.014). In-hospital mortality rates were similar in both groups (before vs after trauma center group: 13.2% vs 14.2%; p = 0.638). The Z and W statistics revealed higher scores in the after trauma center group than in the before trauma center group (Z statistic, 4.69 vs 1.37; W statistic, 4.52 vs 2.10); 2.42 more patients (per 100 patients) survived after trauma center establishment. Conclusion: Although the mortality rates of trauma patients remained unchanged after the trauma center establishment, the Z and W statistics revealed improvements in the quality of care.

A Comprehensive Investigation of Comorbidities, Mechanisms, Injury Patterns, and Outcomes in Geriatric Blunt Trauma Patients

2016 ◽  
Vol 82 (11) ◽  
pp. 1055-1062 ◽  
Author(s):  
Carlos V. R. Brown ◽  
Kevin Rix ◽  
Amanda L. Klein ◽  
Brent Ford ◽  
Pedro G. R. Teixeira ◽  
...  
Keyword(s):  
Injury Severity Score ◽  
Blunt Trauma ◽  
Severity Score ◽  
Geriatric Patients ◽  
Injury Severity ◽  
Older Age ◽  
Geriatric Trauma ◽  
Trauma Patients ◽  
Injury Patterns ◽  
Abbreviated Injury Scale

The geriatric population is growing and trauma providers are often tasked with caring for injuries in the elderly. There is limited information regarding injury patterns in geriatric trauma patients stratified by mechanism of injury. This study intends to investigate the comorbidities, mechanisms, injury patterns, and outcomes in geriatric blunt trauma patients. A retrospective study of the 2012 National Trauma Databank was performed. Adult blunt trauma patients were identified; geriatric (>/=65) patients were compared with younger (<65) patients regarding admission demographics and vital signs, mechanism and severity of injury, and comorbidities. The primary outcome was injuries sustained and secondary outcomes included mortality, length of stay in the intensive care unit and hospital, and ventilator days. There were 589,830 blunt trauma patients who met the inclusion criteria, including 183,209 (31%) geriatric and 406,621 (69%) nongeriatric patients. Falls were more common in geriatric patients (79 vs 29%, P < 0.0001). Geriatric patients less often had an Injury Severity Score >/=16 (18 vs 20%, P < 0.0001) but more often a head Abbreviated Injury Scale >/=3 (24 vs 18%, P < 0.0001) and lower extremity Abbreviated Injury Scale >/=3 (24% vs 8%, P < 0.0001). After logistic regression older age was an independent risk factor for mortality for the overall population and across all mechanisms. Falls are the most common mechanism for geriatric trauma patients. Geriatric patients overall present with a lower Injury Severity Score, but more often sustain severe injuries to the head and lower extremities. Injury patterns vary significantly between older and younger patients when stratified by mechanism. Mortality is significantly higher for geriatric trauma patients and older age is independently associated with mortality across all mechanisms.

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.

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