| Abstract|| |
Introduction: Despite its shortcomings, trauma-related injury severity score (TRISS) correlates well with mortality in large trauma datasets. The aim of this study was to determine if TRISS correlates with morbidity and hospital lengths of stay using data from an institutional registry at a Level I Trauma Center. We hypothesized that higher TRISS correlates with increased complications and longer hospital stays. Methods: A retrospective review of our institutional registry was performed, examining all trauma admissions between January 1999 and June 30, 2015. Out of a total of 32,026 patient records, TRISS data were available in 23,205 cases. Abstracted data included patient age, gender, ISS, TRISS, presence of complication, Glasgow Coma Scale (GCS), hospital length of stay, intensive care unit LOS, step-down unit LOS, functional independence measure, and 30-day mortality. Results: TRISS was highly predictive of mortality, with the AUC value of 0.95 (95% confidence interval 0.936–0.954, P < 0.01) compared to ISS (AUC 0.794), GCS (AUC 0.827), and age (AUC 0.650). TRISS also performed better than the other variables in terms of the ability to predict morbidity events (AUC 0.813). TRISS was comparable to ISS in terms of prediction of ICU admission (AUC 0.801 versus 0.811, respectively). After correcting for patient age and gender, higher TRISS significantly correlated with longer hospital stays. Conclusions: Despite previous criticisms, we found that TRISS is superior to ISS for mortality and morbidity prediction. TRISS correlated significantly with a hospital, step down, and ICU lengths of stay using a large administrative dataset.
Keywords: Injury severity score, trauma length of stay, trauma risk stratification, trauma-related injury severity score
|How to cite this article:|
Stewart N, MacConchie JG, Castillo R, Thomas PG, Cipolla J, Stawicki SP. Beyond mortality: Does trauma-related injury severity score predict complications or lengths of stay using a large administrative dataset. J Emerg Trauma Shock 2021;14:143-7
|How to cite this URL:|
Stewart N, MacConchie JG, Castillo R, Thomas PG, Cipolla J, Stawicki SP. Beyond mortality: Does trauma-related injury severity score predict complications or lengths of stay using a large administrative dataset. J Emerg Trauma Shock [serial online] 2021 [cited 2021 Dec 1];14:143-7. Available from: https://www.onlinejets.org/text.asp?2021/14/3/143/327085
| Introduction|| |
Trauma is a global health concern, with persistent challenges and complications. According to a 2017 report published by the Center of Disease Control, trauma is currently the leading cause of death in the US in patients <45 years of age and is overall the third leading cause of death nationwide. To render safe and efficient care for patients, several scoring systems have been developed utilizing anatomic and physiologic variables. Each of these indices has in some way attempted to fashion a more reliable means to stratify injury severity, patient prognosis, triage accuracy, classification of patients, and the accumulation of usable patient data for research and clinical advancement. The push for a more standardized implementation of such scores is needed to aid providers in developing a universal vocabulary to communicate with patients, anticipate healthcare needs, and predict outcomes.
The trauma-related injury severity score (TRISS) was developed by Champion et al. in 1981, combining the revised trauma score (RTS) and the injury severity score (ISS) along with an age component. This system was meant to assess patients upon initial presentation as a means of predicting overall prognosis and evaluating the effectiveness of care for trauma patients. Despite earlier investigations having questioned its utility, newer research shows evidence that TRISS is a superior scoring system when compared to alternate indices including ISS, New Injury Severity Score, and RTS., Over the past three decades, multiple international studies have provided supporting evidence to validate it as an accurate predictor of patient mortality.,,,
As predicted by the 1990 landmark Major Trauma Outcome Study, the need for ongoing data acquisition and risk stratification has become so pertinent, the American College of Surgeons now mandates the production of performance improvement and patient safety plans in trauma centers. Using data from the institutional registry at our Level I Trauma Center, this study's aim is to determine if TRISS correlates with morbidity and hospital lengths of stay. We hypothesized that a higher TRISS is associated with increased complications and longer hospital stays.
| Methods|| |
A single-centered, retrospective review of our institutional registry was performed, examining all trauma admissions between January 1999 and June 30, 2015. All trauma patients within the registry, regardless of age, gender, or mechanism of injury, were reviewed to determine if they were viable candidates for the study. Intubated patients were excluded due to an inability to accurately obtain respiratory rate and verbal responses as elements of RTS. Burn patients were also excluded from the study simply because our center does not have a designated burn unit. Out of a total of 32,026 patient records, TRISS data was available in 23,205 cases. Abstracted data included patient age, gender, ISS, TRISS, presence of complication, Glasgow Coma Scale (GCS), hospital length of stay (LOS), intensive care unit LOS, step-down unit LOS, functional independence measure, and 30-day mortality. Univariate analyses were performed and adjusted for demographics to determine the relationship between TRISS, mortality, morbidity, and LOS.
TRISS was used to determine the probability of survival (Ps) in trauma patients indiscriminate of the mechanism of injury. It incorporates an anatomical scoring system, ISS, which utilizes the three highest values from the Abbreviated Injury Score and calculates the sum of the squares of each value thereby providing a quantitative index to measure the severity of injury. TRISS also contains a physiologic component, RTS, that is used as a marker of mortality and a useful tool to help determine if treatment at a trauma center is warranted. The final component used to calculate TRISS is age [Table 1] and [Table 2].,,
Receiver operating characteristic (ROC) curves were then constructed to compare the predictive power of TRISS for mortality and morbidity events. SPSS 18 (IBM Corp., Armonk, NY, USA) was utilized, with a statistical significance of α = 0.05.
| Results|| |
The study sample of 23,205 cases consisted of 60.3% males, had a median age of 45 years (interquartile range [IQR] 24–70), and median ISS of 5 (IQR 4–10). As expected, TRISS was highly predictive of mortality, with the area under ROC curve (AUC) of 0.95 (95% confidence interval 0.936–0.954, P < 0.01). This compared favorably to ISS (AUC 0.794), GCS (AUC 0.827), and age (AUC 0.650); [Figure 1]. TRISS also performed better than the other variables in terms of the ability to predict morbidity events (AUC 0.813) [Figure 2]. TRISS was comparable to ISS in terms of prediction of ICU admission (AUC 0.801 versus 0.811, respectively); [Figure 3]. Finally, after correcting for patient age and gender, higher TRISS significantly correlated with longer hospital stays [Table 3].
|Figure 1: Trends observing mortality rates comparing the use of trauma related injury severity score, Glasgow Coma Scale, injury severity score, and age as independent predictive indices|
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|Figure 2: Trends observing morbidity rates comparing the use of trauma related injury severity score, Glasgow Coma Scale, injury severity score, and age as independent predictive indices|
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|Figure 3: Trends observing ICU admission rates [Figure 3], comparing the use of trauma related injury severity score, Glasgow Coma Scale, injury severity score, and age as independent predictive indices|
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| Discussion|| |
TRISS has been well validated in predicting mortality over many years and similar to previously published results, TRISS appears to be a superior predictor of mortality when measured against ISS, RTS, GCS, APACHE II, or age., Other scoring systems have been studied for their predictive value on LOS and quality of life. These studies, however, have been limited to specific populations such as traumatic brain injuries. For this reason, it was decided to use the available trauma data collected at our Level I institution to study the effectiveness of TRISS at determining morbidity and mortality as it relates to LOS. To our knowledge, this is the first US investigation of its kind to compare the use of TRISS to hospital LOS.
The results show that as the rate of morbidity and mortality increased, there is a direct correlation seen in an increase of hospital, step down, and total ICU days. This is contrary to data found in a 2009 New Zealand study that ruled out TRISS as having the capacity to predict LOS. It is noteworthy to point out that the comparative study had a median LOS of 10 and 11 days for transferred and initially established patients, respectively, and also observed LOS as a continuous variable over the course of admission. Considering our LOS [Table 3] was significantly lower, it may be worth investigating the futility of TRISS and its predictive power beyond a specific time threshold. It could in fact be speculated that the value of this scoring system is more beneficial as an initial tool once all of a patient's injuries have been determined.
Despite the usefulness of the results shown in this investigation, there are still a few limitations worth mentioning. This single-centered study took a retrospective look at how TRISS could be utilized in analyzing factors such as morbidity and mortality. To truly ascertain its capability to provide predictive prognostic data as it correlates to LOS, prospective studies would need to investigate the direct relationship time actually has on the accuracy of its prognostic value.
As expected with trauma populations, our patients were predominantly young males, with a median age of 45. As pointed out by Schluter et al. 2010, the current TRISS coefficients are not reliable when being applied to penetrating pediatric injuries. It, therefore, stands to reason that by better clarifying the parameters in which use of this score is most applicable, data gathered among various trauma institutions would begin to consistently reflect each other. Existing pediatric scoring systems such as the Pediatric Risk of Mortality (PRISM) III score have proven valuable in predicting mortality and LOS in critically ill children. Although this score was not designed with the intention of being used in a trauma setting, a great utility could perhaps be found in the creation of a TRISS-PRISM III hybrid to better assess this specific population.
Our data does not take into account the confounders that arise due to previous medical conditions present. With the increasing prevalence of the elderly trauma population secondary to the continued increase in life expectancy, there is also a steady quantity of baseline patient disease that physicians must be able to balance when confronted with victims of trauma. According to Jiang et al., TRISS has been shown to be an effective scoring system for geriatrics in-hospital mortality. Various alternative models such as Index of Coexistent Comorbidity Disease and TRISSCOM (TRISS in the presence of comorbidities) have shown that the significant spike in comorbidities over the age of 65, does in fact impact the way TRISS is used to determine morbidity and mortality., Being able to incorporate models that can clearly tie in such cofounders would be a great asset in enhancing the predictive potential of TRISS.
A substantial limitation to this investigation was the need to exclude intubated patients from the sample population. A major portion of trauma populations require intubation; however, the sedatives or paralytics required for intubation alter the RR and GCS components of the RTS. Voskresensky et al., 2009, showed that depending on whether the vitals used for TRISS were obtained at the scene of the trauma versus at the time of hospital admission, there is a significant change in the degree of prognostic accuracy. Although employing this strategy improved the survival probability in intubated patients between admission vitals (39%) and scene vitals (69%), both tactics still underestimated the Ps compared to what actually occurred in observed patients (76%). Until more adequate means are developed to account for this segment of the trauma population, it will perhaps remain one of the most significant weaknesses in using TRISS.
| Conclusions|| |
Despite previous criticisms, we confirmed that TRISS is superior to ISS for mortality and morbidity prediction in a large administrative dataset. It also performs comparably to ISS in terms of predicting trauma ICU admission. In addition, TRISS stratified by the calculated Ps correlated significantly with a hospital, step down, and ICU lengths of stay using a large dataset. Although not free of limitations, the TRISS methodology should not be abandoned until a better, more robust trauma risk assessment system can be devised.
Research quality and ethics statement
The authors of this manuscript declare that this scientific work complies with reporting quality, formatting, and reproducibility guidelines set forth by the EQUATOR Network. The authors also attest that this clinical investigation was determined to not require the Institutional Review Board/Ethics Committee review, and the corresponding protocol/approval number is not applicable.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Darbandsar Mazandarani P, Heydari K, Hatamabadi H, Kashani P, Jamali Danesh Y. Acute Physiology and Chronic Health Evaluation (APACHE) III Score compared to Trauma-Injury Severity Score (TRISS) in Predicting Mortality of Trauma Patients. Emerg (Tehran) 2016;4:88-91.
Huber-Wagner S, Stegmaier J, Mathonia P, Paffrath T, Euler E, Mutschler W, et al
. The sequential trauma score – A new instrument for the sequential mortality prediction in major trauma. Eur J Med Res 2010;15:185-95.
Llullaku SS, Hyseni NS, Bytyçi CI, Rexhepi SK. Evaluation of trauma care using TRISS method: The role of adjusted misclassification rate and adjusted w-statistic. World J Emerg Surg 2009;4:2.
Champion HR, Sacco WJ, Carnazzo AJ, Copes W, Fouty WJ. Trauma score. Crit Care Med 1981;9:672-6.
Champion HR, Copes WS, Sacco WJ, Lawnick MM, Keast SL, Bain LW Jr., et al
. The major trauma outcome study: Establishing national norms for trauma care. J Trauma 1990;30:1356-65.
Javali RH, Krishnamoorthy, Patil A, Srinivasarangan M, Suraj, Sriharsha. 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 Crit Care Med 2019;23:73-7.
Brockamp T, Maegele M, Gaarder C, Goslings JC, Cohen MJ, Lefering R, et al
. Comparison of the predictive performance of the BIG, TRISS, and PS09 score in an adult trauma population derived from multiple international trauma registries. Crit Care 2013;17:R134.
Domingues CA, Coimbra R, Poggetti RS, Nogueira LS, de Sousa RM. New Trauma and Injury Severity Score (TRISS) adjustments for survival prediction. World J Emerg Surg 2018;13:12.
Singh J, Gupta G, Garg R, Gupta A. Evaluation of trauma and prediction of outcome using TRISS method. J Emerg Trauma Shock 2011;4:446-9.
] [Full text]
Watts HF, Kerem Y, Kulstad EB. Evaluation of the revised trauma and injury severity scores in elderly trauma patients. J Emerg Trauma Shock 2012;5:131-4. [Full text]
Sarkar B, Brunsvold ME, Cherry-Bukoweic JR, Hemmila MR, Park PK, Raghavendran K, et al
. American College of Surgeons' Committee on trauma performance improvement and patient safety program: Maximal impact in a mature trauma center. J Trauma 2011;71:1447-53.
Orhon R, Eren SH, Karadayı S, Korkmaz I, Coşkun A, Eren M, et al
. Comparison of trauma scores for predicting mortality and morbidity on trauma patients. Ulus Travma Acil Cerrahi Derg 2014;20:258-64.
Jiang L, Zheng Z, Zhang M. The incidence of geriatric trauma is increasing and comparison of different scoring tools for the prediction of in-hospital mortality in geriatric trauma patients. World J Emerg Surg 2020;15:59.
Berger-Estilita J, Granja C, Gonçalves H, Dias CC, Aragão I, Costa-Pereira A, et al
. A new global health outcome score after trauma (GHOST) for disability, cognitive impairment, and health-related quality of life: Data from a prospective cross-sectional observational study. Brain Inj 2019;33:922-31.
Schluter PJ, Cameron CM, Davey TM, Civil I, Orchard J, Dansey R, et al
. Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand. N Z Med J 2009;122:65-78.
Schluter PJ, Nathens A, Neal ML, Goble S, Cameron CM, Davey TM, et al
. Trauma and Injury Severity Score (TRISS) coefficients 2009 revision. J Trauma 2010;68:761-70.
Kaur A, Kaur G, Dhir SK, Rai S, Sethi A, Brar A, et al
. Pediatric risk of mortality III score – Predictor of mortality and hospital stay in pediatric intensive care unit. J Emerg Trauma Shock 2020;13:38-42.
Bergeron E, Rossignol M, Osler T, Clas D, Lavoie A. Improving the TRISS methodology by restructuring age categories and adding comorbidities. J Trauma 2004;56:760-7.
Wang CY, Chen YC, Chien TH, Chang HY, Chen YH, Chien CY, et al
. Impact of comorbidities on the prognoses of trauma patients: Analysis of a hospital-based trauma registry database. PLoS One 2018;13:1-12.
Offner PJ, Jurkovich GJ, Gurney J, Rivara FP. Revision of TRISS for intubated patients. J Trauma 1992;32:32-5.
Voskresensky IV, Rivera-Tyler T, Dossett LA, Riordan WP Jr., Cotton BA. Use of scene vital signs improves TRISS predicted survival in intubated trauma patients. J Surg Res 2009;154:105-11.
Department of Acute Care Surgical Services, St. Luke's University Hospital, 801 Ostrum Street, Bethlehem, PA 18015
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]