Evaluation of Probability of Survival Using Trauma and Injury Severity Score Method in Severe Neurotrauma Patients

Moon, Jeong Hyun; Seo, Bo-Ra; Jang, Jee-Soo; Lee, Jung-Kil; Moon, Hyung S.

doi:10.3340/jkns.2013.54.1.42

Cited by 20 publications

(15 citation statements)

References 19 publications

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“…A study conducted by Moon et al predicted deaths in their study to be 11.13% and in reality the deaths were 12.64% and this difference was not significant. 7 Similar findings were reported by Narouzi et al and Fernandez et al 8,9 Deshmukh et al conducted a study to evaluate the outcome of severely injured patients using the TRISS method in a developing country like India and to compare it with the major trauma outcome study (MTOS). 4 A prospective study of 300 patients of trauma was done.…”

Section: Discussionsupporting

confidence: 63%

Assessment of trauma and injury severity score model for survival of trauma patients: a single centre experience

et al. 2018

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Background: Trauma and Injury Severity Score (TRISS) designed by Major Trauma Outcome Study (MTOS) in United States, is commonly used for outcome prediction in polytrauma patients. It determines the probability of survival (PS) of a patient from the Injury Severity Score (ISS) and Revised Trauma Score (RTS) using TRISS methodology.Methods: A total number of 136 patients presenting within 24 hours of trauma that were admitted were included in the study. The probability of survival was calculated using TRISS index (RTS, ISS, and age combination index). The predicted probability of survival and that of death among the study subjects were calculated using TRISS. A cut off 0.5 or lesser of TRISS score was taken as death and above 0.5 as survival status.Results: The mean TRISS among males and females were 86.12±21.76 and 79.49±27.70 and based on TRISS score the expected deaths were predicted to be 11.03%. But, in actual, the deaths were 23.52% showing a negative correlation with TRISS score in our set up thereby indicating a need to improve emergency facilities for trauma patients.Conclusions: TRISS methodology when applied to our setup predicted fewer deaths as compared to the actual deaths and also did not accurately predict the survival in the trauma patients.

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Section: Discussionsupporting

confidence: 63%

Assessment of trauma and injury severity score model for survival of trauma patients: a single centre experience

et al. 2018

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“…However, the higher intervals showed an overestimation of the survival predictions. Previous research suggested an inability of ISS to account enough for multiple injuries to the same body region [29]. While mortality is often attributed to TBI, severe TBI is often not entirely captured by a measure such as the ISS.…”

Section: Discussionmentioning

confidence: 99%

Performance of the modified TRISS for evaluating trauma care in subpopulations: A cohort study

Munter

Polinder

Nieboer

et al. 2018

Injury

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A B S T R A C TIntroduction: Previous research showed that there is no agreement on a practically applicable model to use in the evaluation of trauma care. A modification of the Trauma and Injury Severity Score (modified TRISS) is used to evaluate trauma care in the Netherlands. The aim of this study was to evaluate the prognostic ability of the modified TRISS and to determine where this model needs improvement for better survival predictions. Methods: Patients were included if they were registered in the Brabant Trauma Registry from 2010 through 2015. Missing values were imputed according to multiple imputation. Subsets were created based on age, length of stay, type of injury and injury severity. Probability of survival was calculated with the modified TRISS. Discrimination was assessed with the Area Under the Receiver Operating Curve (AUROC). Calibration was studied graphically. Results: The AUROC was 0.84 (95% CI: 0.83, 0.85) for the total cohort (N = 69 747) but only 0.53 (95% CI: 0.51, 0.56) for elderly patients with hip fracture. Overall, calibration of the modified TRISS was adequate for the total cohort, with an overestimation for elderly patients and an underestimation for patients without brain injury. Conclusions: Outcome comparison conducted with TRISS-based predictions should be interpreted with care. If possible, future research should develop a simple prediction model that has accurate survival prediction in the aging overall trauma population (preferable with patients with hip fracture), with readily available predictors.

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“…Traffic injury and trauma are the third most common cause of mortality and the second leading cause of disability in all age groups (1,2). The world health organization (WHO) has predicted that by 2020 deaths due to traffic injury will increase to 2.34 million per year (3).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Survival and Hospital Care Quality in Patients with Traffic Injury in East Azerbaijan

Esmaeili¹,

Sadeghi‐Bazargani²,

Vahdati³

et al. 2016

Trauma Mon

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Background: Traffic events are the second most common cause of mortality and the first cause of years of life lost (YLL) in Iran. Objectives: The aim of this study was to determine the survival of patients with traffic injury and evaluate hospital care quality using the trauma and injury severity score (TRISS) method. Methods: This cross-sectional study was conducted on 1000 patients aged 1 to 89 years old who were hospitalized in two university hospitals in East Azerbaijan, Iran. Patients were selected by using stratified sampling. Data were extracted from medical records and analyzed by STATA11 software. Injury severity score (ISS), revised trauma score (RTS), and expected survival were calculated using the TRISS software package. W-scores and Z-scores were calculated to evaluate the performance of hospitals. Finally, results were compared to those of the major trauma outcome study (MTOS). Results: Among 1000 patients, 246 (24.6%) were female. The mean age was 32.6 years (SD, 18.6). Mean ISS for living patients was 12.4 (SD, 4.3) while it was 36.9 (SD, 8.9) for fatal cases. The average RTS was reported to be 7.1 and 4.35 for alive and fatal cases, respectively (P < 0.001). Based on TRISS, 58 cases were expected to result in death; however, 65 fatalities were observed (65/1000). The W-score was -7 per 1000 and Z-score was + 0.02. The TRISS misclassification rate for survival status of patients with traffic injury was reported as 2.6%. Conclusions: Our findings indicate that the quality of care at the hospitals under study using the TRISS method was lower than the quality of care in the MTOS study. Further, survival of traffic injury patients was clearly influenced by the quality of hospital services provided.

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Evaluation of Probability of Survival Using Trauma and Injury Severity Score Method in Severe Neurotrauma Patients

Cited by 20 publications

References 19 publications

Assessment of trauma and injury severity score model for survival of trauma patients: a single centre experience

Assessment of trauma and injury severity score model for survival of trauma patients: a single centre experience

Performance of the modified TRISS for evaluating trauma care in subpopulations: A cohort study

Assessment of Survival and Hospital Care Quality in Patients with Traffic Injury in East Azerbaijan

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