Evaluation of trauma care applying TRISS methodology in a Caribbean developing country

Predicting Mortality in Trauma Research: Evaluating the Performance of Trauma Scoring Tools in a South African Population

Background Trauma is a leading cause of death and disability in low-resource settings, yet trauma severity scores are seldom validated in these contexts. There is a pressing need to better characterize and compare trauma scoring tools, especially within research frameworks. This study aimed to evaluate the performance of various trauma scoring tools in predicting in-hospital mortality among trauma patients in South Africa. Methods This study conducted a secondary analysis of existing data from the multicenter Epidemiology and Outcomes of Prolonged Trauma Care (EpiC) study, which included 13,548 adult trauma patients aged 18 years and older, collected between August 2021 and March 2024. The predictive ability of the scoring tools was assessed by calculating the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). Results The mortality rate was 2.5% (n = 298). The Kampala Trauma Score (KTS) demonstrated the highest predictive ability for seven-day in-hospital mortality, with an AUROC of 0.95 and an AUPRC of 0.53. Similarly, the Trauma and Injury Severity Score (TRISS) and the New Injury Severity Score (NISS) also exhibited strong predictive capabilities, with AUROC values of 0.96 and AUPRC values of 0.62 for TRISS and an AUROC of 0.96 and AUPRC of 0.53 for NISS. In contrast, the Revised Trauma Score and Mechanism, Glasgow Coma Scale, Age, and Arterial Pressure (MGAP) showed lower predictive performance, with AUROC values of 0.87 (AUPRC = 0.51) and 0.86 (AUPRC = 0.47), respectively. Conclusions The KTS exhibited optimal performance characteristics for retrospectively predicting mortality in our cohort, outperforming other scoring tools. Notably, it is also the simplest scoring tool, featuring the fewest variables compared to other trauma severity assessments. These findings highlight the necessity for external validation of trauma scoring tools in resource-limited populations to ensure their applicability and effectiveness in trauma research across diverse healthcare settings.

The Kampala Trauma Score: A 20-year track record

ABSTRACT

Quantifying the severity of traumatic injury has been foundational for the standardization of outcomes, quality improvement research, and health policy throughout the evolution of trauma care systems. Many injury severity scores are difficult to calculate and implement, especially in low- and middle-income countries (LMICs) where human resources are limited. The Kampala Trauma Score (KTS)-a simplification of the Trauma Injury Severity Score-was developed in 2000 to accommodate these settings. Since its development, numerous instances of KTS use have been documented, but extent of adoption is unknown. More importantly, does the KTS remain useful for determining injury severity in LMICs? This review aims to better understand the legacy of the KTS and assess its strengths and weaknesses. Three databases were searched to identify scientific papers concerning the KTS. Google Scholar was searched to identify grey literature. The search returned 357 papers, of which 199 met inclusion criteria. Eighty-five studies spanning 16 countries used the KTS in clinical settings. Thirty-seven studies validated the KTS, assessing its ability to predict outcomes such as mortality or need for admission. Over 80% of these studies reported the KTS equalled or exceeded more complicated scores at predicting mortality. The KTS has stood the test of time, proving itself over the last twenty years as an effective measure of injury severity across numerous contexts. We recommend the KTS as a means of strengthening trauma systems in LMICs and suggest it could benefit high-income trauma systems that do not measure injury severity.

Predicting mortality in trauma patients - A retrospective comparison of the performance of six scoring systems applied to polytrauma patients from the emergency centre of a South African central hospital

Introduction

Over 90% of trauma-related deaths worldwide, ensue in low- and middle-income countries. Multiple useful trauma scoring systems have been devised. Although validated in high-income countries, they cannot always be replicated in resource-limited countries. This study compares six trauma scores to identify the best-suited system to use for polytrauma patients in a hospital in Pretoria, South Africa.

Methods

This is an observational retrospective analysis of polytrauma admissions from 1 July 2016 to 31 December 2016. Data collected from patients' records from the EC of Steve Biko Academic Hospital, was analysed using Stata Release 14. Outcomes were recorded as 30-day survival, ICU– and overall hospital LOS. Scores pertaining to patient mortality, were compared in terms of sensitivity, specificity, and cut-off points based on ROC curve. Finally, for LOS Pearson correlation analysis was used.

Results

At the best calculated mortality prediction cut-points for the scores, the sensitivities and specificities were respectively 87% and 68% for TRISS, 81% and 61% for ISS, RTS yielded 81% and 60%, while for REMS it was 61% and 69%. The SI and RSI (cut-points used in agreement with the literature) produced sensitivities 58% and only 48%, and specificities of 73% and 83%, respectively.

45(41,7%) patients required ICU admission. Though the ICU LOS best correlated with ISS(r = 0.2710), the ICU LOS correlation coefficient was weak for all trauma scores. None of the scores had a significant p value for hospital LOS.

Discussion

Among the scores compared, TRISS had the highest sensitivity and NPV for mortality prediction in this South African polytrauma population. ISS correlated best with ICU LOS. However, compared to developed countries, ROC analyses & predictability of these scores fare relatively worse, and no correlation was found with hospital LOS. Therefore, we conclude that further studies are needed to ascertain a more suitable system for resource-limited settings.

Evaluation of ISS, RTS, CASS and TRISS scoring systems for predicting outcomes of blunt trauma abdomen

PURPOSE

Trauma is the leading cause of mortality in people below the age of 45 years. Abdominal trauma constitutes one-fourth of the trauma burden. Scoring systems in trauma are necessary for grading the severity of the injury and prior mobilization of resources in anticipation. The aim of this study was to evaluate RTS, ISS, CASS and TRISS scoring systems in blunt trauma abdomen.

MATERIALS AND METHODS

A prospective single-center study was conducted on 43 patients of blunt trauma abdomen. Revised trauma score (RTS), Injury Severity Score (ISS), Clinical Abdominal Scoring System (CASS) and Trauma and Injury Severity Score (TRISS) were calculated and compared with the outcomes such as need for surgical intervention, post-operative complications and mortality.

RESULTS

The majority of the study subjects were males (83.7%). The most common etiology for blunt trauma abdomen as per this study was road traffic accident (72.1%). Spleen was the most commonly injured organ as per the study. CASS and TRISS were significant in predicting the need for operative intervention. Only ISS significantly predicted post-operative complications. All scores except CASS significantly predicted mortality.

CONCLUSIONS

Among the scoring systems studied CASS and TRISS predicted the need for operative intervention with good accuracy. For the prediction of post-operative complications, only the ISS score showed statistical significance. ISS, RTS and TRISS predicted mortality with good accuracy but the superiority of one score over the other couldn't be proved.

Factors affecting mortality in major trauma patients in Trinidad and Tobago – A view from the developing world

Introduction

There are few data on major trauma in the developing world. This study investigated the characteristics and outcomes of seriously injured patients in Trinidad and Tobago, using Trauma and Injury Severity Score (TRISS) methodology. We also aimed to assess the predictive accuracy of the TRISS model in patients in Trinidad and Tobago.

Methods

Retrospective data from major trauma patients attending the Emergency Department of a tertiary hospital in Trinidad between 2010 and 2014 were analysed. Patients ≥18 years having an Injury Severity Score >15 were included. The impact of age, gender, comorbidities, mechanisms and patterns of injury on mortality was investigated. Using TRISS methodology, predicted mortality was calculated and compared to actual mortality.

Results

Of 323 patients analysed, 284 were male and 24 were aged ≥65 years. The commonest injury mechanisms in younger people were motor vehicle accidents (34.1%) and stabbings (30.8%) compared to falls (66.7%) and motor vehicle accidents (20.8%) in people aged ≥65 years. The commonest areas injured were the chest in younger patients (81.9%) and the head and neck in patients aged ≥65 years (58.3%). Women’s mortality rates were similar to men (RR 1.8; 95% CI 0.7–4.9). Mortality was higher with age ≥65 years (RR 7.0; 95% CI 3.1–15.9), blunt trauma (RR 7.6; 95% CI 1.8–32.4) and Charlson Comorbidity Index of 1 or more (RR 3.2; 95% CI 1.3–8.0). The TRISS model performed well at lower ISS scores and was excellent at predicting survival (discrimination statistic 0.94).

Conclusion

Multiple factors influence mortality in major trauma patients in Trinidad and Tobago, including age, co-morbidities and injury mechanism. TRISS methodology accurately predicted survival in this population but was better at predicting mortality in patients with lower Injury Severity Score.

Thefeasibility, appropriateness, and applicability of trauma scoring systems in low and middle-income countries: a systematic review

Background

About 5.8 million people die each year as a result of injuries, and nearly 90% of these deaths occur in low and middle-income countries (LMIC). Trauma scoring is a cornerstone of trauma quality improvement (QI) efforts, and is key to organizing and evaluating trauma services. The objective of this review was to assess the appropriateness, feasibility, and QI applicability of traditional trauma scoring systems in LMIC settings.

Materials and methods

This systematic review searched PubMed, Scopus, CINAHL, and trauma-focused journals for articles describing the use of a standardized trauma scoring system to characterize holistic health status. Studies conducted in high-income countries (HIC) or describing scores for isolated anatomic locations were excluded. Data reporting a score’s capacity to discriminate mortality, feasibility of implementation, or use for QI were extracted and synthesized.

Results

Of the 896 articles screened, 336 were included. Over half of studies (56%) reported Glasgow Coma Scale, followed by Injury Severity Score (ISS; 51%), Abbreviated Injury Scale (AIS; 24%), Revised Trauma Score (RTS; 19%), Trauma and Injury Severity Score (TRISS; 14%), and Kampala Trauma Score (7%). While ISS was overwhelmingly predictive of mortality, 12 articles reported limited feasibility of ISS and/or AIS. RTS consistently underestimated injury severity. Over a third of articles (37%) reporting TRISS assessmentsobserved mortality that was greater than that predicted by TRISS. Several articles cited limited human resources as the key challenge to feasibility.

Conclusions

The findings of this review reveal that implementing systems designed for HICs may not be relevant to the burden and resources available in LMICs. Adaptations or alternative scoring systems may be more effective.

PROSPERO registration number

CRD42017064600.

A Comparative Study of Injury Severity Scales as Predictors of Mortality in Trauma Patients: Which Scale Is the Best?

Objective:

To compare the injury severity scales as predictors of mortality in trauma patients to search for the best scale.

Methods:

In a prospective cohort study and systematical random sampling conducted from March to September 2017, trauma patients over the age of 13 years were enrolled. The investigated variables were age, gender, systolic blood pressure, heart rate, respiratory rate, injured body region, Glasgow Coma Scale (GCS), injury severity score (ISS), revised trauma score (RTS), trauma injury severity score (TRISS) and the outcome.

Results:

Totally, 1410 trauma patients were followed up, out of which 68.5% were male. The participants’ mean age was 43.5±20.88 years. After adjusting the confounding effects, age over 60 years (OR=7.38, CI [3.91-13.93]), GCS<8 (OR=6.5, CI [2.38-18.16]), RTS<7.6 (OR=6.04, CI [2-13.7]), and TRISS<0.9 (OR=3.09, CI [1.39-6.88]) were determined as the most significant predictor variables for in-hospital mortality. The results of Receiver Operating Characteristic (ROC) curve revealed that TRISS had the highest area under the curve in comparison to other tests that were evaluated. Furthermore, TRISS had the highest sensitivity and specificity for scores higher than 96.15. By contrast, the sensitivity and specificity of GCS decreased for scores higher than 5.5.

Conclusion:

Our results showed that TRISS, RTS, GCS, and ISS were all very effective approaches for evaluating prognosis, mortality and probable complications in trauma patients; thus, these systems of injury evaluation and scoring are recommended to facilitate treatment. TRISS, RTS, and ISS had almost the same sensitivity that was higher than GCS, but GCS had the most specificity. Finally, TRISS was selected as the most efficient scale for predicting mortality.

Comparison of Injury Severity Score, New Injury Severity Score, Revised Trauma Score and Trauma and Injury Severity Score for Mortality Prediction in Elderly Trauma Patients

Objectives

This study tests the accuracy of the Injury Severity Score (ISS), New Injury Severity Score (NISS), Revised Trauma Score (RTS) and Trauma and Injury Severity Score (TRISS) in prediction of mortality in cases of geriatric trauma.

Design

Prospective observational study.

Materials and methods

This was a prospective observational study on two hundred elderly trauma patients who were admitted to JSS Hospital, Mysuru over a consecutive period of 18 months between December 2016 to May 2018. On the day of admission, data were collected from each patient to compute the ISS, NISS, RTS, and TRISS.

Results

Mean age of patients was 66.35 years. Most common mechanism of injury was road traffic accident (94.0%) with mortality of 17.0%. The predictive accuracies of the ISS, NISS, RTS and the TRISS were compared using receiver operator characteristic (ROC) curves for the prediction of mortality. Best cutoff points for predicting mortality in elderly trauma patient using TRISS system was a score of 91.6 (sensitivity 97%, specificity of 88%, area under ROC curve 0.972), similarly cutoff point under the NISS was score of 17(91%, 93%, 0.970); for ISS best cutoff point was at 15(91%, 89%, 0.963) and for RTS it was 7.108(97%,80%,0.947). There were statistical differences among ISS, NISS, RTS and TRISS in terms of area under the ROC curve (p <0.0001).

Conclusion

TRISS was the strongest predictor of mortality in elderly trauma patients when compared to the ISS, NISS and RTS.

How to cite this article

Javali RH, Krishnamoorthy et al. Comparison of Injury Severity Score, New Injury Severity Score, Revised Trauma Score and Trauma and Injury Severity Score for Mortality Prediction in Elderly Trauma Patients. Indian J of Crit Care Med 2019;23(2):73-77.

Demographics of Fall-Related trauma among the Elderly Presenting to Emergency Department; a Cross-Sectional Study

Introduction

Falling is reported to be the most common cause of mortality due to trauma in individuals over the age of 75 years. The present study is designed with the aim of determining the demographics of fall-related trauma among the elderly presenting to emergency department (ED).

Methods

The present prospective cross-sectional study was carried out on all elderly patients ≥ 60 years old presenting to ED of a major referral trauma center in North West of Iran during 1 year. Demographic data, location and height of falling, duration of hospitalization, trauma severity and in-hospital outcome of the patients were gathered and reported via descriptive statistics.

Results

228 patients with the mean age of 70.96 ± 5.2 years were studied (53.9% female). Most patients were in the 66-70 years age range (32.6%) and had a history of hypertension (22.3%), who had visited following a fall inside the house (69.3%), due to slipping (73.7%), and from a height equal to or less than 2m (71.9%). 6 (2.6%) patients died in the hospital. Mean trauma severity of patients based on ISS, RTS, and TRISS were 10.65 ± 3.95 (3-19), 7.84 ±.21 (1.4-14.5) and 1.66 ±1.31 (-1.49-3.82), respectively. Regarding need for hospitalization, only ISS shows a significant difference between outpatients and inpatients (p = 0.023). Patients who died had a significantly higher trauma severity based on ISS (p < 0.0001) and RTS (p < 0.0001).

Conclusion

Based on the findings of the present study, slipping and syncope are the most common causes of falling in the studied elderly that had mostly happened inside the house and from a height less than 2m. Therefore, most patients were in the mild to moderate range of trauma severity. ISS and RTS were significantly higher in the 6 (2.6%) patients who died.

Diagnostic accuracy of the Kampala Trauma Score using estimated Abbreviated Injury Scale scores and physician opinion

BACKGROUND

The Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores.

METHODS

This was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure's ability to predict A&E mortality and need for hospital admission to the ward or theatre.

RESULTS

A total of 1053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κ_lin=0.47), and maximum (κ_max=0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66-0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69-0.79) was significantly greater than SATS (ROC 0.57; 0.53-0.60) with regard to need for admission.

CONCLUSIONS

KTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs.

Declaration of a state of emergency in Trinidad and Tobago: effect on the trauma admissions at the National Referral Trauma Centre

OBJECTIVE

To determine the effect of a State of Emergency (SOE) on penetrating injuries at the main trauma center in Trinidad and Tobago.

METHODS

Emergency room registers were accessed in order to identify all patients treated for penetrating injuries from July 1, 2010 through December 30, 2012. This study period was chosen to include injuries one year before and one year after the SOE that spanned from August 21, 2011 to December 5, 2011. Data were analyzed using SPSS version 19 and a P value<.05 was considered statistically significant.

RESULTS

There were 1,067 patients treated for penetrating injuries. There were significantly more injuries from gunshots compared to stab wounds (64.7% vs 35.3%; P<.001), and this pattern was maintained during the SOE (54.7% vs 45.3%; P=.37). There was a significant fall in mean monthly admissions for penetrating trauma during the SOE when compared to the 12-month period before its imposition (17.7, SD=4.0 vs 38.9, SD=12.3; CI, 5.6-36.8; P=.0108). One year later, mean monthly admissions for penetrating trauma were similar to those during the SOE (22.7, SD=2.1 vs 17.6, SD=4.0; CI, -2.3-12.3; P=.1295). The incidence of gunshot wounds remained low and stab wounds increased.

CONCLUSION

This study has demonstrated that there was a reduction in the incidence of penetrating trauma at the national trauma center after the SOE, with a shift from gunshot to stab wounds.

Burden of traumatic injuries in Saudi Arabia: lessons from a major trauma registry in Riyadh, Saudi Arabia

BACKGROUND AND OBJECTIVES

In Saudi Arabia (SA), injuries are the second leading cause of death; however, little is known about their frequencies and outcomes. Trauma registries play a major role in measuring the burden on population health. This study aims to describe the population of the only hospital-based trauma registry in the country and highlight challenges and potential opportunities to improve trauma data collection and research in SA.

DESIGN AND SETTINGS

Using data between 2001 and 2010, this retrospective study included patients from a large trauma center in Riyadh, SA.

PATIENTS AND METHODS

A staff nurse utilized a structured checklist to gather information on patients' demographic, physiologic, anatomic, and outcome variables. Basic descriptive statistics by age group ( 14 years) were calculated, and differences were assessed using student t and chi-square tests. In addition, the mechanism of injury and the frequency of missing data were evaluated.

RESULTS

10 847 patients from the trauma registry were included. Over 9% of all patients died either before or after being treated at the hospital. Patients who were older than 14 years of age (more likely to be male) sustained traffic-related injuries and died in the hospital as compared to patients who were younger than or equal to years of age. Deceased patients were severely injured as measured by injury severity score and Glasgow Coma Scale (P < .001). Overall, the most frequent type of injury was related to traffic (52.0%), followed by falls (23.4%). Missing values were mostly prevalent in traffic-related variables, such as seatbelt use (70.2%).

CONCLUSION

This registry is a key step toward addressing the burden of injuries in SA. Improved injury classification using the International Classification of Disease-external cause codes may improve the quality of the registry and allow comparison with other populations. Most importantly, injury prevention in SA requires further investment in data collection and research to improve outcomes.

Trauma survival prediction in Asian population: a modification of TRISS to improve accuracy

The probability of survival (PS) in blunt trauma as calculated by Trauma and Injury Severity Score (TRISS) has been an indispensable tool in trauma audit. The aim of this study is to explore the predictive performance of the latest updated TRISS model by investigating the Age variable recategorisations and application of local Injury Severity Score (ISS) and Revised Trauma Score (RTS) coefficients in a logistic model using a level I trauma centre database involving Asian population.

METHODS

Prospectively and consecutively collected 5684 trauma patients' data over a 10-year period at a regional level I trauma centre were reviewed. Four modified TRISS (mTRISS) models using Age coefficient from reclassifications of the Age variable according to their correlation with survival by logistic regression on the local dataset were acquired. RTS and ISS coefficients were derived from the local dataset and then applied to the mTRISS models. mTRISS models were compared with the existing Major Trauma Outcome Study (MTOS)-derived TRISS (eTRISS) model. Model 1=Age effect taken as linear; Model 2=Age classified into two groups (0-54, 55+); Model 3=Age classified into four groups (0-15, 16-54, 55-79, 80+) and Model 4=Age classified into two groups (0-69, 70+). Performance measures including sensitivity, specificity, accuracy and area under the Receiver Operating Characteristic (ROC) curve were used to assess the various models. The cross-validation procedure consisted of comparing the P(S) obtained from mTRISS Models 1 and 2 with the P(S) obtained from the MTOS derived from eTRISS.

RESULTS

A 5147 blunt trauma patients' dataset was reviewed. Model 1, where Age was taken as a scale variable, demonstrated a substantial improvement in the survival prediction with 91.6% accuracy in blunt injuries as compared with 89.2% in the MTOS-derived TRISS. The 95% CI for ROC derived from mTRISS Model 1 was (0.923, 0.940), when compared with the hypothesised ROC value 0.886 obtained from eTRISS, it clearly indicated a significant improvement in predicting survival at 5% level. Furthermore, ROCs have shown clearly the superiority of Model 1 over Model 2, and of Model 2 over MTOS-derived TRISS. The recategorisation of the Age variable (Models 3 and 4) also demonstrated improved performance, but their strength was not as intense as in Model 1. Overall, the results point to the adoption of Model 1 as the best model for PS. Cross-validation analysis has further assured the validity of these findings.

CONCLUSIONS

The present study has demonstrated that (1) having the Age variable being dichotomised (cut-off at 55 years) as in the eTRISS, but with the application of a local dataset-derived coefficients give better TRISS survival prediction in Asian blunt trauma patients; (2) improved performance are found with certain recategorisation of the Age variable and (3) the accuracy can further be enhanced if the Age effect is taken to be linear, with the application of local dataset-derived coefficients.