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

Gaikwad, Umesh; Wasnik, Nitin; Saxena, Divish; Akhtar, Murtaza

doi:10.18203/2349-2902.isj20182771

Cited by 5 publications

(6 citation statements)

References 5 publications

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“…Study conducted by Gaikwad et al reported that according to TRISS, the expected deaths were predicted to be 11.03%, but in actual the deaths were 23.52% showing a negative correlation with TRISS. 10 Similar results were seen by Murlidhar et al where mortality rate predicted using TRISS was 10.89%, but actual mortality rate was 21.26%. 13 It was seen that TRISS methodology when applied to these setups predicted fewer deaths as compared to the actual deaths and also did not accurately predict the survival in the trauma patients.…”

Section: Discussionsupporting

confidence: 82%

“…Study conducted by Deshmukh et al reported the RTS to be 6.63±1.79, Gaikwad et al reported it to be (6.98± 1.14). 1,10 The patient who expired showed a significantly lower RTS (5.14±1.38) as compared to that of survivors (7.24±0.94) (p value <0.0001). Rathore et al reported that the patients who expired showed a significantly lower RTS (4.59±2.09) as compared to that among survivors (7.76±0.445).…”

Section: Discussionmentioning

confidence: 92%

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Study of the efficacy of trauma and injury severity score to predict survival in patients of polytrauma

et al. 2021

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Background: Trauma is one of the major cause of mortality and morbidity in both developed and developing countries. Polytrauma patients present particular challenges as profile of the patient varies with different types and severity of injuries. Prediction of survival in trauma patients is an essential requirement of trauma care. Trauma and injury severity score (TRISS) have been considered as a standard of the quality of trauma care. Study was carried out to evaluate the performance of TRISS in predicting survival in patients of polytrauma.Methods: Prospective observational study was conducted in emergency department of a tertiary care centre. 100 patients were evaluated in the study for a period of 18 months between November 2019 and April 2021. Patient demographics, details of trauma, pattern of injuries and physiological status were recorded. Overall outcome were studied and data analysis was done on the basis of TRISS. Statistical analysis was performed using statistical package for the social sciences (SPSS) program for windows, version 25.0 (SPSS Chicago, Illinois).Results: Young patients with mean age of 34.54 were most commonly affected in polytrauma with male preponderance. Road traffic accidents were the most common mode of trauma followed by fall from height. Blunt trauma was the most common type of injury. TRISS strongly predicted survival in polytrauma patients (AUC 0.926 CI 95% 0.868-0.985). TRISS has high sensitivity 97.62% and specificity 62.50% at a cut off of 64.50%.Conclusions: TRISS is an effective method for predicting survival of polytrauma patients and thus can be utilized to evaluate and compare trauma care.

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Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 92%

Study of the efficacy of trauma and injury severity score to predict survival in patients of polytrauma

et al. 2021

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“…For this reason, several trauma scoring systems have been developed to estimate survival rate in trauma patients, including the Trauma and Injury Severity Score (TRISS) or A Severity Characterization of Trauma (ASCOT) [ 21 ]. TRISS is a scoring system used for the determination of survival probability in blunt and penetrating trauma and is one of the most commonly used scores in this area [ 22 , 23 ]. It combines physiological and anatomical trauma scoring systems.…”

Section: Discussionmentioning

confidence: 99%

Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS

Niggli

Pape

Niggli

et al. 2021

JCM

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Introduction: Big data-based artificial intelligence (AI) has become increasingly important in medicine and may be helpful in the future to predict diseases and outcomes. For severely injured patients, a new analytics tool has recently been developed (WATSON Trauma Pathway Explorer) to assess individual risk profiles early after trauma. We performed a validation of this tool and a comparison with the Trauma and Injury Severity Score (TRISS), an established trauma survival estimation score. Methods: Prospective data collection, level I trauma centre, 1 January 2018–31 December 2019. Inclusion criteria: Primary admission for trauma, injury severity score (ISS) ≥ 16, age ≥ 16. Parameters: Age, ISS, temperature, presence of head injury by the Glasgow Coma Scale (GCS). Outcomes: SIRS and sepsis within 21 days and early death within 72 h after hospitalisation. Statistics: Area under the receiver operating characteristic (ROC) curve for predictive quality, calibration plots for graphical goodness of fit, Brier score for overall performance of WATSON and TRISS. Results: Between 2018 and 2019, 107 patients were included (33 female, 74 male; mean age 48.3 ± 19.7; mean temperature 35.9 ± 1.3; median ISS 30, IQR 23–36). The area under the curve (AUC) is 0.77 (95% CI 0.68–0.85) for SIRS and 0.71 (95% CI 0.58–0.83) for sepsis. WATSON and TRISS showed similar AUCs to predict early death (AUC 0.90, 95% CI 0.79–0.99 vs. AUC 0.88, 95% CI 0.77–0.97; p = 0.75). The goodness of fit of WATSON (X2 = 8.19, Hosmer–Lemeshow p = 0.42) was superior to that of TRISS (X2 = 31.93, Hosmer–Lemeshow p < 0.05), as was the overall performance based on Brier score (0.06 vs. 0.11 points). Discussion: The validation supports previous reports in terms of feasibility of the WATSON Trauma Pathway Explorer and emphasises its relevance to predict SIRS, sepsis, and early death when compared with the TRISS method.

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“…In the Indian context, only a few studies have demonstrated the use of different trauma scores to predict outcomes in patients with trauma, especially TRISS [10,12,13]. Hence, this study was undertaken with the aim of filling in this gap and trying to examine the utility of TRISS scores to estimate patient outcomes in cases of trauma, followed by setting up a triage and trauma management protocol.…”

Section: Introductionmentioning

confidence: 99%

Use of the Trauma and Injury Severity Score (TRISS) as a Predictor of Patient Outcome in Cases of Trauma Presenting in the Trauma and Emergency Department of a Tertiary Care Institute

Indurkar,

Ghormade,

Akhade

et al. 2023

Cureus

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Background: In this study, we used the anatomic scoring system Abbreviated Injury Scale (AIS) to calculate the Injury Severity Score (ISS) and the physiological scoring system for the Revised Trauma Score (RTS) on the arrival of patients. Both scores were used to calculate the Trauma and Injury Severity Score (TRISS) for predicting the patient outcome in a case of trauma.Methods: This prospective, cross-sectional, observational study was carried out at the trauma centre of a tertiary care institute and included patients of either sex, age ≥18 years, and ISS ≥15. A total of 2084 cases of trauma over a period of 18 months were assessed, and 96 cases of blunt trauma meeting the inclusion criteria were studied.Results: Patients injured in road traffic accidents constituted the maximum caseload. Out of a sample size of 96 patients with ISS ≥15, 77 died during the treatment and 19 survived.The ISS ranged from 15 to 66, with a mean ± SD score of 27.48 ± 8.79. Non-survivors had a statistically higher significant ISS than survivors (p<0.001). The RTS ranged from <1 to 7.84, with a mean ± SD score of 4.52 ± 2.08. Non-survivors had low RTS (RTS <5, n=52) compared to survivors, and the difference was statistically significant (p<0.001).The mean ± SD TRISS (Ps) score was 0.69 ± 2.288. In the non-survivor (NS) group, 15 patients had TRISS (Ps) between 0.26-0.50, followed by 0.51-0.75 (n=18), 0.76-0.90 (n=12), and 0.90-0.95 (n=11). While 16 survivors had TRISS (Ps) between 0.96 and 1, a statistically significant association was found between TRISS and patient outcome (p-value <0.001).On the receiver operating characteristic (ROC) curve analysis, the sensitivity of TRISS (94.7%) and RTS was found to be comparable (94.7%), whereas ISS was less sensitive (36.8%) in predicting the patient outcome. RTS (79.2%) and TRISS (76.6%) scores were more specific than ISS (5.2%) for outcome analysis. Conclusion:The TRISS score is useful in the management of trauma patients as it can satisfactorily predict mortality in a case of trauma. The trauma scores are of immense help in determining the nature of injury in medicolegal cases.

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

Cited by 5 publications

References 5 publications

Study of the efficacy of trauma and injury severity score to predict survival in patients of polytrauma

Study of the efficacy of trauma and injury severity score to predict survival in patients of polytrauma

Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS

Use of the Trauma and Injury Severity Score (TRISS) as a Predictor of Patient Outcome in Cases of Trauma Presenting in the Trauma and Emergency Department of a Tertiary Care Institute

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