Risk factors for mortality of severe trauma based on 3 years' data at a single Korean institution

Sim, Joohyun; Lee, Jaeheon; Lee, John Cook Jong; Heo, Yun-Jung; Wang, Heejung; Jung, Kyoungwon

doi:10.4174/astr.2015.89.4.215

Cited by 19 publications

(13 citation statements)

References 20 publications

(39 reference statements)

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“…This conversion was performed as our previous research on risk factors for trauma mortality showed that a continuous value of age could be a better predictor for trauma outcome while other converted values regarding SBP, RR, or GCS could not. 21 The model shows a greater explanatory power (R 2 of 0.408=40.8% vs. 38.0%, respectively) than the existing TRISS combination (coded age value, RTS, ISS), and the Hosmer-Lemeshow test results (χ 2 =7.487, p value=0.485) verified a good fit and calibration of the model ( Table 5 ). If such an encouraging result could be obtained with a single trauma care center's small-scale data, a more robust model may be identifiable through a study using multi-institutional data, such as the KTDB.…”

Section: Discussionmentioning

confidence: 65%

The Applicability of Trauma and Injury Severity Score for a Blunt Trauma Population in Korea and a Proposal of New Models Using Score Predictors

et al. 2016

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PurposeThe purpose of this study was to verify the utility of existing Trauma and Injury Severity Score (TRISS) coefficients and to propose a new prediction model with a new set of TRISS coefficients or predictors.Materials and MethodsOf the blunt adult trauma patients who were admitted to our hospital in 2014, those eligible for Korea Trauma Data Bank entry were selected to collect the TRISS predictors. The study data were input into the TRISS formula to obtain "probability of survival" values, which were examined for consistency with actual patient survival status. For TRISS coefficients, Major Trauma Outcome Study-derived values revised in 1995 and National Trauma Data Bank-derived and National Sample Project-derived coefficients revised in 2009 were used. Additionally, using a logistic regression method, a new set of coefficients was derived from our medical center's database. Areas under the receiver operating characteristic (ROC) curve (AUC) for each prediction ability were obtained, and a pairwise comparison of ROC curves was performed.ResultsIn the statistical analysis, the AUCs (0.879–0.899) for predicting outcomes were lower than those of other countries. However, by adjusting the TRISS score using a continuous variable rather than a code for age, we were able to achieve higher AUCs [0.913 (95% confidence interval, 0.899 to 0.926)].ConclusionThese results support further studies that will allow a more accurate prediction of prognosis for trauma patients. Furthermore, Korean TRISS coefficients or a new prediction model suited for Korea needs to be developed using a sufficiently sized sample.

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Section: Discussionmentioning

confidence: 65%

The Applicability of Trauma and Injury Severity Score for a Blunt Trauma Population in Korea and a Proposal of New Models Using Score Predictors

et al. 2016

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“…Worse prognosis for traumatized elderly compared to younger patients has been constantly presented in the literature (8)(9)(22)(23)(24)(25) . This weakness is explained by characteristics of the elderly population that make it more vulnerable, such as comorbidities and the use of medications that impact the physiological response to the injury and complicate treatment and recovery (26) .…”

Section: Discussionmentioning

confidence: 99%

Risk factors for death of trauma patients admitted to an Intensive Care Unit

Lentsck

Oliveira

Corona

et al. 2020

Rev. Latino-Am. Enfermagem

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Objective: To analyze the risk factors for death of trauma patients admitted to the intensive care unit (ICU). Method: Retrospective cohort study with data from medical records of adults hospitalized for trauma in a general intensive care unit. We included patients 18 years of age and older and admitted for injuries. The variables were grouped into levels in a hierarchical manner. The distal level included sociodemographic variables, hospitalization, cause of trauma and comorbidities; the intermediate, the characteristics of trauma and prehospital care; the proximal, the variables of prognostic indices, intensive admission, procedures and complications. Multiple logistic regression analysis was performed. Results: The risk factors associated with death at the distal level were age 60 years or older and comorbidities; at intermediate level, severity of trauma and proximal level, severe circulatory complications, vasoactive drug use, mechanical ventilation, renal dysfunction, failure to perform blood culture on admission and Acute Physiology and Chronic Health Evaluation II. Conclusion: The identified factors are useful to compose a clinical profile and to plan intensive care to avoid complications and deaths of traumatized patients.

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“…Nowadays, government policies are formed in accordance with preventive measures, as well as the healthcare needs of patients; these policies have led to reduced mortality rates, full recovery of patients with severe injuries and reduced socioeconomic burden in various countries 2, 10, 11. In this regard, since various factors can affect mortality in any traumatic incident,12, 13, 14 there is an increasing demand for local data on trauma, which includes not only mortality rates but also the factors involved in post-trauma mortality 15 . Early detection of these risk factors can significantly increase the quality of care and therefore lead to the improvement of patient outcomes and reduction of mortality caused by acute trauma 16, 17.…”

Section: Introductionmentioning

confidence: 99%

A study of mortality risk factors among trauma referrals to trauma center, Shiraz, Iran, 2017

Yadollahi

2019

Chinese Journal of Traumatology

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Purpose Trauma is well known as one of the main causes of death and disability throughout the world. Identifying the risk factors for mortality in trauma patients can significantly improve the quality of care and patient outcomes, as well as reducing mortality rates. Methods In this retrospective cohort study, systematic randomization was used to select 849 patients referred to the main trauma center of south of Iran during a period of six months (February 2017–July 2017); the patients’ case files were evaluated in terms of demographic information, pre- and post-accident conditions, clinical conditions at the time of admission and finally, accident outcomes. A logistic regression model was used to analyze the role of factors affecting mortality among subjects. Results Among subjects, 60.4% were in the age-group of 15–39 years. There was a 10.4% mortality rate among patients and motor-vehicle accidents were the most common mechanism of injury (66.7%). Aging led to increased risk of fatality in this study. For each unit increase in Glasgow coma scale (GCS), risk of death decreased by about 40% (odds ratio ( OR ) = 0.63, 95% confidence interval ( CI ): 0.59–0.67). For each unit increase in injury severe score (ISS), risk of death increased by 10% ( OR = 1.11%, 95% CI : 1.08–1.14) and for each unit increase in trauma revised injury severity score (TRISS), there was 18% decrease in the risk of fatality ( OR = 0.82, 95% CI : 0.71–0.88). Conclusion The most common cause of trauma and the most common cause of death from trauma was traffic accidents. It was also found that an increase in the ISS index increases the risk of death in trauma patients, but the increase in GCS, revised trauma score (RTS) and TRISS indices reduces the risk of death in trauma patients. The TRISS indicator is better predictor of traumatic death than other indicators.

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Risk factors for mortality of severe trauma based on 3 years' data at a single Korean institution

Cited by 19 publications

References 20 publications

The Applicability of Trauma and Injury Severity Score for a Blunt Trauma Population in Korea and a Proposal of New Models Using Score Predictors

The Applicability of Trauma and Injury Severity Score for a Blunt Trauma Population in Korea and a Proposal of New Models Using Score Predictors

Risk factors for death of trauma patients admitted to an Intensive Care Unit

A study of mortality risk factors among trauma referrals to trauma center, Shiraz, Iran, 2017

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