Evaluation of probability of survival using trauma and injury severity score method in severe neurotrauma patients

Which curve is better? A comparative analysis of trauma scoring systems in a South Asian country

Objectives

A diverse set of trauma scoring systems are used globally to predict outcomes and benchmark trauma systems. There is a significant potential benefit of using these scores in low and middle-income countries (LMICs); however, its standardized use based on type of injury is still limited. Our objective is to compare trauma scoring systems between neurotrauma and polytrauma patients to identify the better predictor of mortality in low-resource settings.

Methods

Data were extracted from a digital, multicenter trauma registry implemented in South Asia for a secondary analysis. Adult patients (≥18 years) presenting with a traumatic injury from December 2021 to December 2022 were included in this study. Injury Severity Score (ISS), Trauma and Injury Severity Score (TRISS), Revised Trauma Score (RTS), Mechanism/GCS/Age/Pressure score and GCS/Age/Pressure score were calculated for each patient to predict in-hospital mortality. We used receiver operating characteristic curves to derive sensitivity, specificity and area under the curve (AUC) for each score, including Glasgow Coma Scale (GCS).

Results

The mean age of 2007 patients included in this study was 41.2±17.8 years, with 49.1% patients presenting with neurotrauma. The overall in-hospital mortality rate was 17.2%. GCS and RTS proved to be the best predictors of in-hospital mortality for neurotrauma (AUC: 0.885 and 0.874, respectively), while TRISS and ISS were better predictors for polytrauma patients (AUC: 0.729 and 0.722, respectively).

Conclusion

Trauma scoring systems show differing predictability for in-hospital mortality depending on the type of trauma. Therefore, it is vital to take into account the region of body injury for provision of quality trauma care. Furthermore, context-specific and injury-specific use of these scores in LMICs can enable strengthening of their trauma systems.

Level of evidence

Level III.

The preventability of trauma-related death: A two-year cohort study in a trauma center in middle Taiwan

INTRODUCTION

The preventable death rate (PDR) is an important parameter in the quality assurance of traumatic care. Medical errors or untimely management may occur during stressful trauma care, resulting in preventable deaths. We aimed to develop an applicable PDR model in a trauma center in middle Taiwan.

MATERIALS AND METHODS

We identified adult trauma-related deaths which occurred from January 1, 2018 to December 31, 2019 at our hospital. Patients with a trauma and injury severity score (TRISS) <75% or ≥75% but with a chance of preventability, as determined by a trauma surgeon, were discussed by a panel comprising an emergency physician and surgeons specializing in different fields of medicine. Deaths were subsequently classified as definitely preventable (DP), potentially preventable (PP), or non-preventable (NP). Causes of DP or PP deaths were categorized as delayed diagnosis, delayed treatment, technical error, or inadequate infection prevention/control. The relationship between the time and cause of preventable deaths was also analyzed.

RESULTS

This study included 127 trauma-related deaths, of which 39 were discussed by the panel. Eight patients (6.3%) were categorized as DP, eight (6.3%) as PP, and 111 (87.4%) as NP. Among patients with preventable deaths, inadequate infection prevention/control, delayed treatment, delayed diagnosis, and technical error were identified in six (37.5%), five (31.2%), three (18.8%), and two (12.5%) patients, respectively. Four patients in the inadequate infection prevention/control group (4/6, 66.7%) died of aspiration pneumonia during the recovery phase.

CONCLUSION

A PDR evaluation model was developed and revealed that postoperative care is as important as a timely diagnosis and treatment to avoid preventable deaths following trauma.

Outcomes in trauma patients undergoing veno-venous extracorporeal membrane oxygenation for acute respiratory distress syndrome

BACKGROUND

The use of veno-venous extracorporeal membrane oxygenation (VV ECMO) remains controversial in trauma patients with acute respiratory distress syndrome (ARDS). Here, we aimed to investigate the therapeutic benefits of VV ECMO and the factors affecting patient outcomes.

METHODS

From 2017 to 2019, 21/1938 trauma patients (median age: 47 years; 18 men) at a level I trauma center received VV ECMO for post-traumatic ARDS. Demographic, injury-specific, ECMO, and outcome data were prospectively collected and retrospectively reviewed to analyze the factors affecting hospital mortality and ECMO results.

RESULTS

19 patients (90.5%) were successfully weaned off ECMO; 16 patients (76.2%) survived to discharge. In univariate analysis, there was a significant difference in survival between the groups with a Trauma and Injury Severity Score (TRISS) ⩾0.5 and TRISS <0.5 (p = 0.05). The area under the receiver operating characteristic curve (AUC) for both TRISS and Respiratory Extracorporeal Membrane Oxygenation Survival Prediction (RESP) scores for death was 0.78. In those who failed ECMO weaning, the AUCs of the TRISS and RESP scores were 0.90 and 0.80, respectively.

CONCLUSIONS

In patients with ARDS caused by severe trauma and supported by VV ECMO, survival is associated with TRISS; TRISS and RESP scores may be predictive of mortality and failure in ECMO weaning.

Machine Learning Algorithms to Predict In-Hospital Mortality in Patients with Traumatic Brain Injury

Traumatic brain injury (TBI) can lead to severe adverse clinical outcomes, including death and disability. Early detection of in-hospital mortality in high-risk populations may enable early treatment and potentially reduce mortality using machine learning. However, there is limited information on in-hospital mortality prediction models for TBI patients admitted to emergency departments. The aim of this study was to create a model that successfully predicts, from clinical measures and demographics, in-hospital mortality in a sample of TBI patients admitted to the emergency department. Of the 4881 TBI patients who were screened at the emergency department at a high-level first aid duty hospital in northern Taiwan, 3331 were assigned in triage to Level I or Level II using the Taiwan Triage and Acuity Scale from January 2008 to June 2018. The most significant predictors of in-hospital mortality in TBI patients were the scores on the Glasgow coma scale, the injury severity scale, and systolic blood pressure in the emergency department admission. This study demonstrated the effective cutoff values for clinical measures when using machine learning to predict in-hospital mortality of patients with TBI. The prediction model has the potential to further accelerate the development of innovative care-delivery protocols for high-risk patients.

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.

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

INTRODUCTION

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.

Effect of Mannitol Infusion on Optic Nerve Injury After Acute Traumatic Subarachnoid Hemorrhage and Brain Injury

The primary aim of this paper is to investigate the neuroprotective and antiinflammatory effects of mannitol on optic nerve injury after acute traumatic subarachnoid hemorrhage and brain injury in rat models. Traumatic brain injury (TBI) and traumatic subarachnoid hemorrhage (tSAH) were produced by a custom-made weight-drop impact acceleration device. Thirty male Wistar rats were divided into 3 groups. Group I (n = 10) was the sham group, group II (n = 10) received TBI, and group III (n = 10) received TBI + mannitol (1 mg/kg intravenously). Optic nerve tissue glutathione peroxidase (GPx) and interleukin 1 beta (IL-1β) levels were measured 4 hours after the trauma. The authors used Kruskal-Wallis variance analysis and Mann-Whitney U tests for statistical analysis. Optic nerve tissue GPx levels were significantly higher in group III than in groups I and II (P < 0.05). Optic nerve tissue IL-1β levels were significantly lower in group III than in group II (P < 0.05) and higher than in group I (P < 0.05).Mannitol increased the antioxidant GPx levels and decreased the IL-1β levels, which can protect the optic nerve from secondary injury after severe acute trauma. Mannitol plays an important role in the treatment of acute severe indirect optic nerve injury after TBI and tSAH.

Predictor of Isolated Trauma in Head: A New Simple Predictor for Survival of Isolated Traumatic Brain Injury

BACKGROUND

Mortality prediction in patients with brain trauma during initial management in the emergency department (ED) is essential for creating the foundation for a better prognosis.

OBJECTIVE

This study aimed to create a simple and useful survival predictive model for patients with isolated blunt traumatic brain injury that is easily available in the ED.

METHODS

This is a retrospective study based on the trauma registry data of an academic teaching hospital. The inclusion criteria were age ≥ 15 years, blunt and not penetrating mechanism of injury, and Abbreviated Injury Scale (AIS) scores between 1 and 6 for head and 0 for all other body parts. The primary outcome was 30-day survival probability. Internal and external validation was performed.

RESULTS

After univariate logistic regression analysis based on the derivation cohort, the final Predictor of Isolated Trauma in Head (PITH) model for survival prediction of isolated traumatic brain injury included Glasgow Coma Scale (GCS), age, and coded AIS of the head. In the validation cohort, the area under the curve of the PITH score was 0.970 (p < 0.0001; 95% confidence interval 0.960-0.978). Sensitivity and specificity were 95% and 81.7% at the cutoff value of 0.9 (probability of survival 90%), respectively.

CONCLUSIONS

The PITH model performed better than the GCS; Revised Trauma Score; and mechanism of injury, GCS, age, and arterial pressure. It will be a useful triage method for isolated traumatic brain injury in the early phase of management.

Assessment of Progress in Early Trauma Care in Japan over the Past Decade: Achievements and Areas for Future Improvement

BACKGROUND

Strategies to optimize early trauma care have been introduced in Japan; however, detailed evaluation of the progress achieved has not been reported.

STUDY DESIGN

In this retrospective observational study, patients registered in the Japanese nationwide trauma registry were stratified according to probability of survival (Ps) > 0.5 or ≤ 0.5, respectively. Mortality rates during the first 2 days and in-hospital mortality rates were compared between early (2004 to 2009) and late cohorts (2010 to 2014) in each group, using mixed effects logistic regression analysis. Improvement in mortality rates during the first 2 days among subgroups were also assessed.

RESULTS

We analyzed 80,949 patients with Ps > 0.5 (early, 25,917; late, 55,032) and 8,898 patients with Ps ≤ 0.5 (early, 3,511; late, 5,387). Mortality rates during the first 2 days in both groups were significantly reduced (adjusted odds ratio [AOR; 95% CI] 0.61 [0.53 to 0.69] in the Ps > 0.5 group and 0.67 [0.60 to 0.76] in the Ps ≤ 0.5 group). In-hospital mortality rates in both groups were also significantly reduced (AOR [95% CI] 0.70 [0.64 to 0.76] and 0.73 [0.64 to 0.82], respectively). Significant improvements were observed in patients with a Revised Trauma Score ≥ 7 on arrival or an Abbreviated Injury Scale (AIS) of the abdomen ≥ 3. Limited improvements were observed in patients with head AIS ≥ 3 and in patients who underwent thoracotomy.

CONCLUSIONS

Although early trauma care has generally improved, specific progress was variable. Focused panel review of patients with severe head injury or undergoing thoracotomy may be an efficient strategy for further improvement.

Survival probability in patients with liver trauma

Purpose - The purpose of this paper is to assess the survival probability among patients with liver trauma injury using the anatomical and psychological scores of conditions, characteristics and treatment modes. Design/methodology/approach - A logistic model is used to estimate 173 patients' survival probability. Data are taken from patient records. Only emergency room patients admitted to University Hospital of Trauma (former Military Hospital) in Tirana are included. Data are recorded anonymously, preserving the patients' privacy. Findings - When correctly predicted, the logistic models show that survival probability varies from 70.5 percent up to 95.4 percent. The degree of trauma injury, trauma with liver and other organs, total days the patient was hospitalized, and treatment method (conservative vs intervention) are statistically important in explaining survival probability. Practical implications - The study gives patients, their relatives and physicians ample and sound information they can use to predict survival chances, the best treatment and resource management. Originality/value - This study, which has not been done previously, explores survival probability, success probability for conservative and non-conservative treatment, and success probability for single vs multiple injuries from liver trauma.

Evaluation of Probability of Survival using APACHE II & TRISS Method in Orthopaedic Polytrauma Patients in a Tertiary Care Centre

AIM

The aim of the study was to assess the ability of Acute Physiology and Chronic Health Evaluation (APACHE) II scoring system and Trauma and Injury Severity Score (TRISS) method to evaluate chances of survival of orthopaedic polytrauma patients.

MATERIALS AND METHODS

It is a retrospective study carried out at a tertiary care teaching hospital situated in a hilly terrain. The medical records of 535 polytrauma patients admitted to ICU from January 2012 to April 2015 were examined of which only 95 were included into the study. The APACHE II scores were calculated from data at the time of admission, on day 1 after admission and on day 5. Data from casualty department was used to calculate TRISS. For each patient APACHE II and TRISS was used to calculate their probability of death. Receiver operating characteristic curve analysis was used to assess the ability of APACHE II and TRISS to predict mortality.

RESULTS

In the receiver operating characteristic curve analysis, the areas under the curve for TRISS, APACHE II on admission and APACHE II on day one of admission scoring system was 0.831, 0.706, 0.885 respectively. Sensitivity and specificity for TRISS was 83.64 and 77.50 respectively while for APACHE II score on day one of admission was 90.91 and 72.50.

CONCLUSION

The results from the present study showed that APACHE II score on day one of admission was relatively a better predictor than TRISS score and a far better predictor than APACHE II on admission in evaluating probability of survival of a patient.