2015
DOI: 10.4174/astr.2015.89.4.215
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Risk factors for mortality of severe trauma based on 3 years' data at a single Korean institution

Abstract: PurposeThis study aimed to determine the mortality rate in patients with severe trauma and the risk factors for trauma mortality based on 3 years' data in a regional trauma center in Korea.MethodsWe reviewed the medical records of severe trauma patients admitted to Ajou University Hospital with an Injury Severity Score (ISS) > 15 between January 2010 and December 2012. Pearson chi-square tests and Student t-tests were conducted to examine the differences between the survived and deceased groups. To identify fa… Show more

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Cited by 19 publications
(13 citation 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%
“…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%
“…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%
“…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%