Validation of international trauma scoring systems in urban trauma centres in India

Intubation and In-Hospital Mortality After Trauma With Glasgow Coma Scale Score Eight or Less - A Cohort Study

INTRODUCTION

Most trauma societies recommend intubating trauma patients with Glasgow Coma Scale (GCS) scores ≤8 without robust supporting evidence. We examined the association between intubation and 30-d in-hospital mortality in trauma patients arriving with a GCS score ≤8 in an Indian trauma registry.

METHODS

Outcomes of patients with a GCS score ≤8 who were intubated within 1 h of arrival (intubation group) were compared with those who were intubated later or not at all (nonintubation group) using various analytical approaches. The association was assessed in various subgroup and sensitivity analyses to identify any variability of the effect.

RESULTS

Of 3476 patients who arrived with a GCS score ≤8, 1671 (48.1%) were intubated within 1 h. Overall, 1957 (56.3%) patients died, 947 (56.7%) in the intubation group and 1010 (56.0%) in the nonintubation group, with no significant difference in mortality (odds ratio = 1.2 [confidence interval, 0.8-1.8], P value = 0.467) in multivariable regression and propensity score-matched analysis. This result persisted across subgroup and sensitivity analyses. Patients intubated within an hour of arrival had longer durations of ventilation, intensive care unit stay, and hospital stay (P < 0.001).

CONCLUSIONS

Intubation within an hour of arrival with a GCS score ≤8 after major trauma was not associated with differences in-hospital mortality. The indications and benefits of early intubation in these severely injured patients should be revisited to promote optimal resource utilization in LMICs.

The predictive value of the Kampala Trauma Score (KTS) in the outcome of multi-traumatic patients compared to the estimated Injury Severity Score (eISS)

PURPOSE

The classification of trauma patients in emergency settings is a constant challenge for physicians. However, the Injury Severity Score (ISS) is widely used in developed countries, it may be difficult to perform it in low- and middle-income countries (LMIC). As a result, the ISS was calculated using an estimated methodology that has been described and validated in a high-income country previously. In addition, a simple scoring tool called the Kampala Trauma Score (KTS) was developed recently. The aim of this study was to compare the diagnostic accuracy of KTS and estimated ISS (eISS) in order to achieve a valid and efficient scoring system in our resource-limited setting.

METHODS

We conducted a cross-sectional study between December 2020 and March 2021 among the multi-trauma patients who presented at the emergency department of Imam Reza hospital, Tabriz, Iran. After obtaining informed consent, all data including age, sex, mechanism of injury, GCS, KTS, eISS, final outcome (including death, morbidity, or discharge), and length of hospital stay were collected and entered into SPSS version 27.0 and analyzed.

RESULTS

381 multi-trauma patients participated in the study. The area under the curve for prediction of mortality (AUC) for KTS was 0.923 (95%CI: 0.888-0.958) and for eISS was 0.910 (95% CI: 0.877-0.944). For the mortality, comparing the AUCs by the Delong test, the difference between areas was not statistically significant (p value = 0.356). The diagnostic odds ratio (DOR) for the prediction of mortality KTS and eISS were 28.27 and 32.00, respectively.

CONCLUSION

In our study population, the KTS has similar accuracy in predicting the mortality of multi-trauma patients compared to the eISS.

Comparison of nine trauma scoring systems in prediction of inhospital outcomes of pediatric trauma patients: a multicenter study

Hereby, we aimed to comprehensively compare different scoring systems for pediatric trauma and their ability to predict in-hospital mortality and intensive care unit (ICU) admission. The current registry-based multicenter study encompassed a comprehensive dataset of 6709 pediatric trauma patients aged ≤ 18 years from July 2016 to September 2023. To ascertain the predictive efficacy of the scoring systems, the area under the receiver operating characteristic curve (AUC) was calculated. A total of 720 individuals (10.7%) required admission to the ICU. The mortality rate was 1.1% (n = 72). The most predictive scoring system for in-hospital mortality was the adjusted trauma and injury severity score (aTRISS) (AUC = 0.982), followed by trauma and injury severity score (TRISS) (AUC = 0.980), new trauma and injury severity score (NTRISS) (AUC = 0.972), Glasgow coma scale (GCS) (AUC = 0.9546), revised trauma score (RTS) (AUC = 0.944), pre-hospital index (PHI) (AUC = 0.936), injury severity score (ISS) (AUC = 0.901), new injury severity score (NISS) (AUC = 0.900), and abbreviated injury scale (AIS) (AUC = 0.734). Given the predictive performance of the scoring systems for ICU admission, NTRISS had the highest predictive performance (AUC = 0.837), followed by aTRISS (AUC = 0.836), TRISS (AUC = 0.823), ISS (AUC = 0.807), NISS (AUC = 0.805), GCS (AUC = 0.735), RTS (AUC = 0.698), PHI (AUC = 0.662), and AIS (AUC = 0.651). In the present study, we concluded the superiority of the TRISS and its two derived counterparts, aTRISS and NTRISS, compared to other scoring systems, to efficiently discerning individuals who possess a heightened susceptibility to unfavorable consequences. The significance of these findings underscores the necessity of incorporating these metrics into the realm of clinical practice.

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 role of Mangled Extremity Severity Score in amputation triage in a transport health facility with catastrophic earthquake admissions

BACKGROUND

The purpose of this study is to assess the diagnostic utility of the Mangled Extremity Severity Score (MESS) in the prediction of amputation after a major earthquake, and its utility in disaster triage.

METHODS

Study results were presented from a tertiary hospital in Diyarbakır, which was affected by the earthquake but served as a transport hub for other cities in the region affected by the earthquake. MESS was calculated and its diagnostic value is analyzed in predicting amputations. MESS scores were divided into low risk, intermediate risk, and high risk groups by the researchers based on their diagnostic value analysis.

RESULTS

79 patients were included in the study. Based on the outcome of amputation or salvage, patients were divided into two groups. 24.1% (n = 19) of the patients had amputations. Both gender and mean age did not differ statistically significantly between the groups (p > 0.05). Compared with the salvage group, the amputation group had a significantly longer prehospital stay and higher rate of vascular injury and higher median MESS (p = 0.007, p < 0.001, p < 0.001; respectively). Based on MESS scores, amputation outcomes were predicted with an accuracy of 0.889 (95% CI 0.798-0.949). Those with a MESS score below 9 were considered low risk (sensitivity = 100%) whereas those with a MESS score above 12 were considered high risk (specificity = 98.33%).

CONCLUSION

In transport centers, MESS may be useful for surgical triage of earthquake-induced limb crush injuries.

Back to the basics: Clinical assessment yields robust mortality prediction and increased feasibility in low resource settings

INTRODUCTION

Mortality prediction aids clinical decision-making and is necessary for trauma quality improvement initiatives. Conventional injury severity scores are often not feasible in low-resource settings. We hypothesize that clinician assessment will be more feasible and have comparable discrimination of mortality compared to conventional scores in low and middle-income countries (LMICs).

METHODS

Between 2017 and 2019, injury data were collected from all injured patients as part of a prospective, four-hospital trauma registry in Cameroon. Clinicians used physical exam at presentation to assign a highest estimated abbreviated injury scale (HEAIS) for each patient. Discrimination of hospital mortality was evaluated using receiver operating characteristic curves. Discrimination of HEAIS was compared with conventional scores. Data missingness for each score was reported.

RESULTS

Of 9,635 presenting with injuries, there were 206 in-hospital deaths (2.2%). Compared to 97.5% of patients with HEAIS scores, only 33.2% had sufficient data to calculate a Revised Trauma Score (RTS) and 24.8% had data to calculate a Kampala Trauma Score (KTS). Data from 2,328 patients with all scores was used to compare models. Although statistically inferior to the prediction generated by RTS (AUC 0.92-0.98) and KTS (AUC 0.93-0.99), HEAIS provided excellent overall discrimination of mortality (AUC 0.84-0.92). Among 9,269 patients with HEAIS scores was strongly predictive of mortality (AUC 0.93-0.96).

CONCLUSION

Clinical assessment of injury severity using HEAIS strongly predicts hospital mortality and far exceeds conventional scores in feasibility. In contexts where traditional scoring systems are not feasible, utilization of HEAIS could facilitate improved data quality and expand access to quality improvement programming.

Accuracy and external validation of the modified rapid emergency medicine score in road traffic injuries in a Bangkok level I trauma center

Background

Trauma is a significant public health problem. Therefore, many injury scores have been created to predict mortality and triage patients. This study aims to validate the modified Rapid Emergency Medicine Score (mREMS) for in-hospital mortality prediction in road traffic injuries and compare the mREMS with the revised trauma score (RTS) and the mechanisms, Glasgow Coma Scale (GCS), age, and arterial pressure (MGAP) score.

Methods

Data were retrospectively collected from the Vajira Hospital (1,033 cases). The mREMS was calculated from six predictors: age, systolic blood pressure, heart rate, respiratory rate, pulse oxygen saturation, and GCS. The receiver operating characteristic curve was plotted, and the area under the curve (AUC) was calculated. The AUC and 95% confidence interval (CI) of the mREMS were compared with the AUCs of other scores. Model calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test.

Results

The mREMS was significantly better than the RTS at predicting death in road traffic injury patients [mREMS: AUCs, 0.909 (95% CI, 0.866-0.951); RTS: AUCs, 0.859 (95% CI, 0.791-0.927] (p = 0.023). However, the difference between the AUCs of the mREMS and MGAP score was not statistically significant (p = 0.150). The mREMS' calibration performance was also satisfactory in this dataset based on the Hosmer-Lemeshow goodness-of-fit test (p = 0.277).

Conclusion

In the road traffic injury population, the mREMS is an excellent predictor of in-hospital mortality. These results can be applied to improve triage. However, this score should be further validated in other trauma centers before nationwide implementation.

Validation of the adapted clavien dindo in trauma (ACDiT) scale to grade management related complications at a level I trauma center

Objectives

Complications during trauma management are the main factor responsible for the overall increase in treatment cost. There are very few grading systems to measure the burden of complications in trauma patients. A prospective study was conducted using the Adapted Clavien Dindo in Trauma (ACDiT) scale, with the primary aim of validating it at our center. As a secondary aim, it was also wanted to measure the mortality burden among our admitted patients.

Material and Methods

The study was conducted at a dedicated trauma center. All patients with acute injuries, who were admitted, were included. An initial treatment plan was made within 24 hours of admission. Any deviation from this was recorded and graded according to the ACDiT. The grading was correlated with hospital-free days and ICU-free days within 30 days.

Results

A total of 505 patients were included in this study, with a mean age of 31 years. The most common mechanism of injury was road traffic injury, with a median ISS and NISS of 13 and 14, respectively. Two hundred and forty-eight out of 505 patients had some grade of complication as determined by the ACDiT scale. Hospital-free days (13.5 vs. 25; p <0.001) were significantly lower in patients with complications than those without complications, and so were ICU-free days (29 vs. 30; p <0.001). Significant differences were also observed when comparing mean hospital free and ICU free days across various ACDiT grades. Overall mortality of the population was 8.3 %, the majority of whom were hypotensive on arrival and required ICU care.

Conclusion

We successfully validated the ACDiT scale at our center. We recommend using this scale to objectively measure in-hospital complications and improve trauma management quality. ACDiT scale should be one of the data points in any trauma database/registry.

Mortality from fall: A descriptive analysis of a multicenter Indian trauma registry

INTRODUCTION

Fall is the second most common mechanism of trauma worldwide after road traffic injuries. Data on fall predominantly comes from the high-income countries (HICs) and mostly includes injuries in children and elderly. There are very few studies from low- and middle-income countries(LMICs) that describe fall related injuries other than fragility fractures in elderly. This study describes the profile of poly-trauma patients admitted with a history of 'fall' and assesses the variables associated with mortality.

METHOD

We analyzed data from the 'Towards Improved Trauma Care Outcome' (TITCO) database which prospectively collected data of poly-trauma patients admitted to four major tertiary care hospitals of India between 2013 to 2015. Patients across all age groups admitted to hospital with the history of 'fall'; were included in our study. Single bone fractures were excluded.  The Kaplan Meier survival analysis was used to estimate the survival probability in different age groups.

RESULTS

A total of 3686 patients were included in our study. The median age of the patients was 28 years (IQR: 9, 47) with the majority being males (73.6%). Almost one-third of the patients were within the age group of 0-14 (30.4%). Most of the patients (79.9%) had a diagnosis of traumatic brain injury (TBI). The overall in-hospital mortality was 18% (664), but higher at 39.0% among patients over 65 years of age. Probability of survival decreased with increase of age.

CONCLUSION

Falling from height is a common injury mechanism in India, occurring more in young males and usually associated with TBI. Isolated TBI and TBI associated with other injuries are the main contributors of mortality in fall injuries. Mortality from these injuries increased with age and ISS.

Are home environment injuries more fatal in children and the elderly?

INTRODUCTION

'In-home injuries' are those that occur within the house or its immediate surroundings. The literature on the prevalence and magnitude of home injuries is sparse. This study was designed to characterize the mechanisms of 'in-home' injuries and compare their outcomes with 'outside home injuries'.

MATERIALS AND METHODS

The Australia-India Trauma Systems Collaboration (AITSC) Project created a multicentric registry consisting of trauma patients admitted at four urban tertiary care hospitals in India from April 2016 to March 2018. This registry data was analysed for this study. All admitted patients except for dead on arrival were included. Patients were categorised into 'in-home' and 'outside home' cohorts based on the place where the trauma occurred. The outcome measures were 30 day in-hospital mortality and the length of hospital stay. Two subgroup analyses were performed, the first comprised pediatric patients (<15 years) and the second elderly patients >64 years).

RESULTS

Among 9354 patients in the AITSC data registry, 8398 patients were included in the study. Out of these, 29 percent were in-home injuries, whereas the rest occurred outside home. The 30 day in-hospital mortality was 10.6 percent in the 'in-home' cohort, as compared to 13.7 percent in the 'outside home' cohort. This difference although significant on univariable analysis (p <0.01), there was no significant difference on multivariable regression analysis, after adjusting for age and injury severity score (OR = 0.88, 95% CI = 0.73-1.04; p = 0.15). The length of hospital stay was shorter in the home injuries group (median = 5 days; IQR = 3-12 days) compared to the outside-home group (median = 7 days; IQR = 4-14 days) (p < 0.01). In the pediatric and the elderly, on multivariable regression analysis, in-home injuries were associated with higher mortality than outside home injuries.

CONCLUSION

There was no significant difference in the 30 day in-hospital mortality amongst admitted trauma patients sustaining injuries at home or outside the home. However, in pediatric and elderly patients the chances of mortality was significantly higher when injured at home.

Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study

Background

In armed conflicts, civilian health care struggles to cope. Being able to predict what resources are needed is therefore vital. The International Committee of the Red Cross (ICRC) implemented in the 1990s the Red Cross Wound Score (RCWS) for assessment of penetrating injuries. It is unknown to what extent RCWS or the established trauma scores Kampala trauma Score (KTS) and revised trauma score (RTS) can be used to predict surgical resource consumption and in-hospital mortality in resource-scarce conflict settings.

Methods

A retrospective study of routinely collected data on weapon-injured adults admitted to ICRC’s hospitals in Peshawar, 2009–2012 and Goma, 2012–2014. High resource consumption was defined as ≥3 surgical procedures or ≥ 3 blood-transfusions or amputation. The relationship between RCWS, KTS, RTS and resource consumption, in-hospital mortality was evaluated with logistic regression and adjusted area under receiver operating characteristic curves (AUC). The impact of missing data was assessed with imputation. Model fit was compared with Akaike Information Criterion (AIC).

Results

A total of 1564 patients were included, of these 834 patients had complete data. For high surgical resource consumption AUC was significantly higher for RCWS (0.76, 95% CI 0.74–0.78) than for KTS (0.53, 95% CI 0.50–0.56) and RTS (0.51, 95% CI 0.48–0.54) for all patients. Additionally, RCWS had lower AIC, indicating a better model fit. For in-hospital mortality AUC was significantly higher for RCWS (0.83, 95% CI 0.79–0.88) than for KTS (0.71, 95% CI 0.65–0.76) and RTS (0.70, 95% CI 0.63–0.76) for all patients, but not for patients with complete data.

Conclusion

RCWS appears to predict surgical resource consumption better than KTS and RTS. RCWS may be a promising tool for planning and monitoring surgical care in resource-scarce conflict settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-021-00488-2.

Associations of On-arrival Vital Signs with 24-hour In-hospital Mortality in Adult Trauma Patients Admitted to Four Public University Hospitals in Urban India: A Prospective Multi-Centre Cohort Study

INTRODUCTION

In India, more than a million people die annually due to injuries. Identifying the patients at risk of early mortality (within 24 hour of hospital arrival) is essential for triage. A bilateral Government Australia-India Trauma System Collaboration generated a trauma registry in the context of India, which yielded a cohort of trauma patients for systematic observation and interventions. The aim of this study was to determine the independent association of on-arrival vital signs and Glasgow Coma Score (GCS) with 24-hour mortality among adult trauma patients admitted at four university public hospitals in urban India.

METHODS

We performed an analysis of a prospective multicentre observational study of trauma patients across four urban public university hospitals in India, between April 2016 and February 2018. The primary outcome was 24-hour in-hospital mortality. We used logistic regression to determine mutually independent associations of the vital signs and GCS with 24-hour mortality.

RESULTS

A total of 7497 adult patients (18 years and above) were included. The 24-hour mortality was 1.9%. In univariable logistic regression, Glasgow Coma Score (GCS) and the vital signs systolic blood pressure (SBP), heart rate (HR), respiratory rate (RR) and peripheral capillary oxygen saturation (SpO2) had statistically significant associations with 24-hour mortality. These relationships held in multivariable analysis with hypotension (SBP<90mm Hg), tachycardia (HR>100bpm) and bradycardia (HR<60bpm), hypoxia (SpO2<90%), Tachypnoea (RR>20brpm) and severe (3-8) and moderate (9-12) GCS having strong association with 24-hour mortality. Notably, the patients with missing values for SBP, HR and RR also demonstrated higher odds of 24-hour mortality. The Injury Severity Scores (ISS) did not corelate with 24-hour mortality.

CONCLUSION

The routinely measured GCS and vital signs including SBP, HR, SpO2 and RR are independently associated with 24-hour in-hospital mortality in the context of university hospitals of urban India. These easily measured parameters in the emergency setting may help improve decision-making and guide further management in the trauma victims. A poor short-term prognosis was also observed in patients in whom these physiological variables were not recorded.

Comparison of Trauma Severity Scores (ISS, NISS, RTS, BIG Score, and TRISS) in Multiple Trauma Patients

BACKGROUND

Trauma severity scoring systems are routinely used to monitor trauma patient outcomes. Yet, the most accurate scoring system remains an elusive target.

OBJECTIVE

We aim to compare trauma severity scales (ISS, NISS, RTS, TRISS, and BIG) in multitrauma patients and investigate BIG as one of the new trauma severity scoring systems.

METHODS

The demographic data of the patients, vital signs, injury mechanisms, body regions exposed to trauma, final diagnosis, the injury severity scales-Injury Severity Score (ISS), New Injury Severity Score (NISS), Revised Trauma Score (RTS), base deficit, international normalized ratio, and Glasgow Coma Scale (BIG), and Trauma and Injury Severity Score (TRISS)-the length of stay in hospital, and the progress of the patients were examined.

RESULTS

A total of 426 cases were included in the study. The best performing score in determining mortality was TRISS (area under the curve [AUC]: 0.93, sensitivity 97.1% and specificity 76.7%). This was followed by the NISS, BIG, ISS, and RTS, respectively. For the prediction of intensive care unit admission, the NISS was the most successful with an AUC value of 0.81. There was a significant relationship in terms of the length of stay in all trauma scores (p < .05).

CONCLUSIONS

The most successful score in predicting mortality in trauma patients was the TRISS, whereas the NISS was the most successful in predicting intensive care unit admission. The newly developed BIG score can be used as a strong scoring method for predicting prognosis in trauma patients.

Comparison of the Pediatric Resuscitation and Trauma Outcome (PRESTO) Model and Pediatric Trauma Scoring Systems in a Middle-Income Country

BACKGROUND

The pediatric resuscitation and trauma outcome (PRESTO) model was developed to aid comparisons of risk-adjusted mortality after injury in low- and middle-income countries (LMICs). We sought to validate PRESTO using data from a middle-income country (MIC) trauma registry and compare its performance to the Pediatric Trauma Score (PTS), Revised Trauma Score, and pediatric age-adjusted shock index (SIPA).

METHODS

We included children (age < 15 years) admitted to a single trauma center in South Africa from December 2012 to January 2019. We excluded patients missing variables necessary for the PRESTO model-age, systolic blood pressure, pulse, oxygen saturation, neurologic status, and airway support. Trauma scores were assigned retrospectively. PRESTO's previously high-income country (HIC)-validated optimal threshold was compared to MIC-validated threshold using area under the receiver operating characteristic curves (AUROC). Prediction of in-hospital death using trauma scoring systems was compared using ROC analysis.

RESULTS

Of 1160 injured children, 988 (85%) had complete data for calculation of PRESTO. Median age was 7 (IQR: 4, 11), and 67% were male. Mortality was 2% (n = 23). Mean predicted mortality was 0.5% (range 0-25.7%, AUROC 0.93). Using the HIC-validated threshold, PRESTO had a sensitivity of 26.1% and a specificity of 99.7%. The MIC threshold showed a sensitivity of 82.6% and specificity of 89.4%. The MIC threshold yielded superior discrimination (AUROC 0.86 [CI 0.78, 0.94]) compared to the previously established HIC threshold (0.63 [CI 0.54, 0.72], p < 0.0001). PRESTO showed superior prediction of in-hospital death compared to PTS and SIPA (all p < 0.01).

CONCLUSION

PRESTO can be applied in MIC settings and discriminates between children at risk for in-hospital death following trauma. Further research should clarify optimal decision thresholds for quality improvement and benchmarking in LMIC settings.

Trauma Scores and Their Prognostic Value for the Outcome Following Pediatric Polytrauma

Purpose: The management and prognostic assessment of pediatric polytrauma patients can pose substantial challenges. Trauma scores developed for adults are not universally applicable in children. An accurate prediction of the severity of trauma and correct assessment of the necessity of surgical procedures are important for optimal treatment. Several trauma scores are currently available, but the advantages and drawbacks for use in pediatric patients are unclear. This study examines the value of the trauma scores Injury Severity Score (ISS), Pediatric Trauma Score (PTS), National Advisory Committee for Aeronautics (NACA), and Glasgow Coma Score (GCS) for the assessment of the polytraumatized child. Methods: In a retrospective study, 97 patients aged 0-17 years who presented with polytrauma and an ISS ≥16 in the trauma bay were included in the study. Patient records including radiological studies were analyzed. Pathological imaging findings and emergency surgery were assessed as outcome variables and the predictive value of the trauma scores were analyzed using receiver operator characteristic (ROC) curves. Statistical significance was set at an alpha level of P ≤ 0.05. Results: In this study, 35 of the 97 studied children had pathological cranial computed findings. These either underwent craniectomy or trepanation or a parenchymal catheter was placed for intracranial pressure monitoring. Abdominal trauma was present in 45 patients, 16 of which were treated surgically. Forty-three patients arrived with thoracic injuries, 10 of which received a thoracic drainage. One child underwent an emergency thoracotomy. Predictive accuracy for emergency surgery calculated using receiver-operator characteristic (ROC) curves was highest for ISS and NACA scores (0,732 and 0.683, respectively), and lower for GCS (0.246) and PTS (0.261). Conclusion: In our study cohort, initial ISS and NACA scores better predicted operative interventions and outcome than PTS or GCS for polytraumatized pediatric patients.

Management of liver trauma in urban university hospitals in India: an observational multicentre cohort study

BACKGROUND

Low- and middle-income countries (LMICs) contribute to 90% of injuries occurring in the world. The liver is one of the commonest organs injured in abdominal trauma. This study aims to highlight the demographic and management profile of liver injury patients, presenting to four urban Indian university hospitals in India.

METHODS

This is a retrospective registry-based study. Data of patients with liver injury either isolated or concomitant with other injuries was used using the ICD-10 code S36.1 for liver injury. The severity of injury was graded based on the World Society of Emergency Surgery (WSES) grading for liver injuries.

RESULTS

A total of 368 liver injury patients were analysed. Eighty-nine percent were males, with road traffic injuries being the commonest mechanism. As per WSES liver injury grade, there were 127 (34.5%) grade I, 96 (26.1%) grade II, 70 (19.0%) grade III and 66 (17.9%) grade IV injuries. The overall mortality was 16.6%. Two hundred sixty-two patients (71.2%) were managed non-operatively (NOM), and 106 (38.8%) were operated. 90.1% of those managed non-operatively survived.

CONCLUSION

In this multicentre cohort of liver injury patients from urban university hospitals in India, the commonest profile of patient was a young male, with a blunt injury to the abdomen due to a road traffic accident. Success rate of non-operative management of liver injury is comparable to other countries.

A descriptive study of orthopaedic injuries due to parachute jumping in soldiers

Background

While parachute jumping, soldiers may suffer minor or life-threatening injuries in various parts of the body. Several trauma scoring systems assess the severity of such injuries. The primary goal of this study was to assess clinical characteristics and the severity of orthopaedic, musculoskeletal, and other injuries from military training-related parachute jumping using two trauma scoring systems (AIS and ISS). Our secondary goal was to assess whether there was an increase in injury rates with age.

Methods

In total, 185 military personnel between 19 and 51 years old who were injured as a result of daytime static parachute jumping during 44 months between January 2016 and August 2019 were included in the study. Demographic data; vital signs; the level of consciousness; the Glasgow Coma Scale; ISS trauma region classifications; anatomical injury sites; AIS and ISS scores; diagnoses; treatment methods; hospitalization status; and duration of hospital stay were examined descriptively.

Results

There were 184 male and one female participant. The most commonly injured body site was the foot (33.5%), and the most common diagnosis was soft tissue trauma (64.3%). The most commonly injured body site was the foot (33.5%), and the most common diagnosis was soft tissue trauma (64.3%). Regarding treatment methods, 51.4% received analgesic pills and cold pack application, 42.7% received a plaster splint, and 5.9% had orthopaedic surgery. The mean ISS score was 5.16 ± 3.92. The hospitalization rate was significantly higher for patients with a critical AIS score than those with a severe AIS score (p < 0.001).

Conclusions

The use of trauma scoring systems to assess injury severity among patients admitted to an ED due to a parachute jumping injury may facilitate treatment selection. We found that AIS and ISS were useful in determining injury severity. Therefore, we recommend the use of trauma scoring systems for assessing the injury severity and the therapeutic approach, and we advocate for the use of the 17 anatomical regions we used in this study. We also found that with increasing age, the severity of injury could increase.

Evaluating trauma scoring systems for patients presenting with gunshot injuries to a district-level urban public hospital in Cape Town, South Africa

Introduction

Trauma scoring systems are widely used in emergency settings to guide clinical decisions and to predict mortality. It remains unclear which system is most suitable to use for patients with gunshot injuries at district-level hospitals. This study compares the Triage Early Warning Score (TEWS), Injury Severity Score (ISS), Trauma and Injury Severity Score (TRISS), Kampala Trauma Score (KTS) and Revised Trauma Score (RTS) as predictors of mortality among patients with gunshot injuries at a district-level urban public hospital in Cape Town, South Africa.

Methods

Gunshot-related patients admitted to the resuscitation area of Khayelitsha Hospital between 1 January 2016 and 31 December 2017 were retrospectively analysed. Receiver Operating Characteristic (ROC) analysis were used to determine the accuracy of each score to predict all-cause in-hospital mortality. The odds ratio (with 95% confidence intervals) was used as a measure of association.

Results

In total, 331 patients were included in analysing the different scores (abstracted from database n = 431, excluded: missing files n = 16, non gunshot injury n = 10, <14 years n = 1, information incomplete to calculate scores n = 73). The mortality rate was 6% (n = 20). The TRISS and KTS had the highest area under the ROC curve (AUC), 0.90 (95% CI 0.83-0.96) and 0.86 (95% CI 0.79–0.94), respectively. The KTS had the highest sensitivity (90%, 95% CI 68-99%), while the TEWS and RTS had the highest specificity (91%, 95% CI 87–94% each).

Conclusions

None of the different scoring systems performed better in predicting mortality in this high-trauma burden area. The results are limited by the low number of recorded deaths and further studies are needed.

•

Gunshot injuries most often occurs in young males.

•

Trauma scores can be used to prognosticate patients in order to allocate appropriate resources.

•

Accuracy-related data of trauma scores in entry-level hospitals is limited.

Prehospital prediction of severe injury in road traffic injuries: A multicenter cross-sectional study

BACKGROUND

To develop and validate a risk stratification model of severe injury (SI) and death to identify and prioritize road traffic injury (RTI) patients for transportation to an appropriate trauma center (TC).

METHODS

A 2-phase multicenter-cross-sectional study with prospective data collection was collaboratively conducted using 9 dispatch centers (DC) across Thailand. Among the 9 included DC, 7 and 2 DCs were used for development and validation, respectively. RTI patients who were treated and transported to hospitals by advanced life support (ALS) response units were enrolled. Multiple logistic regression was used to derive risk prediction score of death in 48 h and SI (new injury severity score ≥ 16). Calibration/discrimination performances were explored.

RESULTS

A total of 5359 and 2097 RTIs were used for development and external validation, respectively. Seven and 9 predictors among demographic data, mechanism of injury, physic data, EMS operation, and prehospital managements were significant predictors of death and SI, respectively. Risk prediction models fitted well with the developed data (O/E ratios of 1.00 (IQR: 0.69, 1.01) and 0.99 (IQR: 0.95, 1.05) for death and SI, respectively); and the C statistics of 0.966 (0.961, 0.972) and 0.913 (0.905, 0.922). The risk scores were further stratified as low, moderate and high risk. The derive models did not fit well with external data but they were improved after recalibrating the intercepts. However, the model was externally good/excellent discriminated with C statistics from 0.896 (0.871, 0.922) to 0.981 (0.971, 0.991).

CONCLUSION

Risk prediction models of death and SI were developed with good calibration and excellent discrimination. The model should be useful for ALS response units in proper allocation of patients.

The Malawi trauma score: A model for predicting trauma-associated mortality in a resource-poor setting

BACKGROUND

Globally, traumatic injury is a leading cause of morbidity and mortality in low-income countries. Current tools for predicting trauma-associated mortality are often not applicable in low-resource environments due to a lack of diagnostic adjuncts. This study sought to derive and validate a model for predicting mortality that requires only a history and physical exam.

METHODS

We conducted a retrospective analysis of all patients recorded in the Kamuzu Central Hospital trauma surveillance registry in Lilongwe, Malawi from 2011 through 2014. Using statistical randomization, 80% of patients were used for derivation and 20% were used for validation. Logistic regression modeling was used to derive factors associated with mortality and the Malawi Trauma Score (MTS) was constructed. The model fitness was tested.

RESULTS

62,354 patients are included. Patients are young (mean age 23.0, SD 15.9 years) with a male preponderance (72%). Overall mortality is 1.8%. The MTS is tabulated based on initial mental status (alert, responds to voice, responds only to pain or worse), anatomical location of the most severe injury, the presence or absence of a radial pulse on examination, age, and sex. The score range is 2-32. A mental status exam of only responding to pain or worse, head injury, the absence of a radial pulse, extremes of age, and male sex all conferred a higher probability of mortality. The ROC area under the curve for the derivation cohort and validation cohort were 0.83 (95% CI 0.78, 0.87) and 0.83 (95% CI 0.75, 0.92), respectively. A MTS of 25 confers a 50% probability of death.

CONCLUSIONS

The MTS provides a reliable tool for trauma triage in sub-Saharan Africa and helps risk stratify patient populations. Unlike other models previously developed, its strength is its utility in virtually any environment, while reliably predicting injury- associated mortality.

Performance of injury severity measures in trauma research: a literature review and validation analysis of studies from low-income and middle-income countries

INTRODUCTION

Characterisation of injury severity is an important pillar of scientific research to measure and compare the outcomes. Although majority of injury severity measures were developed in high-income countries, many have been studied in low-income and middle-income countries (LMICs). We conducted this study to identify and characterise all injury severity measures, describe how widely and frequently they are used in trauma research from LMICs, and summarise the evidence on their performance based on empirical and theoretical validation​ analysis.

METHODS

First, a list of injury measures was identified through PubMed search. Subsequently, a systematic search of PubMed, Global Health and EMBASE was undertaken on LMIC trauma literature published from January 2006 to June 2016, in order to assess the application and performance of injury severity measures to predict in-hospital mortality. Studies that applied one or more global injury severity measure(s) on all types of injuries were included, with the exception of war injuries and isolated organ injuries.

RESULTS

Over a span of 40 years, more than 55 injury severity measures were developed. Out of 3862 non-duplicate citations, 597 studies from 54 LMICs were listed as eligible studies. Full-text review revealed 37 studies describing performance of injury severity measures for outcome prediction. Twenty-five articles from 13 LMICs assessed the validity of at least one injury severity measure for in-hospital mortality. Injury severity score was the most commonly validated measure in LMICs, with a wide range of performance (area under the receiver operating characteristic curve (AUROC) between 0.9 and 0.65). Trauma and Injury Severity Score validation studies reported AUROC between 0.80 and 0.98.

CONCLUSION

Empirical studies from LMICs frequently use injury severity measures, however, no single injury severity measure has shown a consistent result in all settings or populations and thus warrants validation studies for the diversity of LMIC population.

Do the Care Process and Survival Chances Differ in Patients Arriving to a Level 1 Indian Trauma Center, during-Hours and after-Hours?

Introduction

Trauma systems vary in performance during different time periods and may affect the patient outcomes, especially in resource-limited settings. The present study was undertaken to study the pattern, epidemiological profile, processes of care variations of trauma victims presenting during-hours and after-hours in a level 1 trauma Center of a lower middle-income country.

Methodology

Retrospective analyses of prospectively collected data registry at a single tertiary care center. Data collected from 2013 to 2015 were analyzed. Patients with a history of trauma and admission to the center or death between arrival and admission were included. Isolated limb injury and patients dead on arrival were excluded.

Results

Of 4692, 1789 (38.1%) patients arrived and were admitted during-hours and 2903 (61.9%) after-hours. The overall in-hospital mortality was 14.9% in the cohort. Moreover, it was 16.10% during after-hours in comparison to 13.0% during-hours. The Revised Trauma Score was statistically different during-hours and after-hours suggesting patients with greater physiological derangement after-hours. The Kaplan-Meier survival curves for 7 days were comparable in two groups with the log-rank test of 078. The proportion of initial radiological investigations (chest X-ray, focused assessment sonography in trauma [FAST], and computerized tomography [CT] scans) was ranged from 84.9% for CT scans in the cohort to 99.3% for FAST.

Conclusions

Processes of care do not differ significantly for the patients admitted at a level 1 trauma center irrespective of time of the day. Although survival probability for the initial 7 days of follow-up is comparable between two groups; however, for 30 and 90 days of follow-up they are significantly different between during-hours and after-hours, likely due to injury severity.

Potential benefits of triage for the trauma patient in a Kenyan emergency department

BACKGROUND

Improved trauma management can reduce the time between injury and medical interventions, thus decreasing morbidity and mortality. Triage at the emergency department is essential to ensure prioritization and timely assessment of injured patients. The aim of the present study was to investigate how a lack of formal triage system impacts timely intervention and mortality in a sub-Saharan referral hospital. Further, the study attempts to assess potential benefits of triage towards efficient management of trauma patients in one middle income country.

METHODS

A prospective descriptive study was conducted. Adult trauma patients admitted to the emergency department during an 8-month period at Moi Teaching and Referral Hospital in Eldoret, Kenya, were included. Mode of arrival and vital parameters were registered. Variables included in the analysis were Injury Severity Score, time before physician's assessment, length of hospital stay, and mortality. The patients were retrospectively categorized according to the Rapid Emergency Triage and Treatment System (RETTS) from patient records.

RESULTS

A total of 571 patients were analyzed, with a mean Injury Severity Score of 12.2 (SD 7.7) with a mean length of stay of 11.6 (SD 18.3) days. The mortality rate was 1.8%. The results obtained in this study illustrate that trauma patients admitted to the emergency department at Eldoret are not assessed in a timely fashion, and the time frame recommendations postulated by RETTS are not adhered to. Assessment of patients according to the triage algorithm used revealed a significantly higher average Injury Severity Score in the red category than in the other color categories.

CONCLUSION

The results from this study clearly illustrate a lack of correct prioritization of patients in relation to the need for timely assessment. This is further demonstrated by the retrospective triage classification of patients, which identified patients with high ISS as in urgent need of care. Since no significant difference in to time to assessment regardless of injury severity was observed, the need for a well-functioning triage system is apparent.

Pattern and Distribution of Shock Index and Age Shock Index Score Among Trauma Patients in Towards Improved Trauma Care Outcomes (TITCO) Dataset

OBJECTIVE

To compare the shock index (SI - which is the ratio of heart rate to systolic blood pressure) and Age SI (Age in years multiplied by SI) with survival outcome of the patients across multicenter trauma registry in India.

METHODS

Study is based on Towards Improved Trauma Care Outcomes (TITCO) project. Records with valid details of age, heart rate, systolic blood pressure, Injury Severity Scale (ISS) and Glasgow Coma Scale (GCS) score was considered. SI was categorized into four groups; Group I (SI<0.6) as no shock, group II (SI ≥0.6 to <1.0) as mild shock, group III (SI ≥1.0 to <1.4) as moderate shock and group IV (SI ≥1.4) as severe shock. Age SI was categorized decade wise into six groups. Mortality was dependent variable. GCS and ISS were considered as secondary variables.

RESULTS

10843 participants from TITCO registry satisfying inclusion-exclusion criteria were considered for study. Mean SI score in group I to IV was increasing with 0.53 to 1.72 respectively. Age SI was seen to be increasing across its six groups. Gender wise no difference was found among SI group. For severe ISS and critical ISS, mortality in SI group IV was 50% and 56 % respectively. Mortality was increasing across mild to severe GCS among all SI groups.

CONCLUSION

The categorized SI and Age SI had shown increase in death percentages from mild to severe severity of injuries. Similar to GCS and ISS, SI and Age SI should also be calculated and categorized in all health care and further plan for management aspects.

Predicting mortality with the international classification of disease injury severity score using survival risk ratios derived from an Indian trauma population: A cohort study

Background

Trauma is predicted to become the third leading cause of death in India by 2020, which indicate the need for urgent action. Trauma scores such as the international classification of diseases injury severity score (ICISS) have been used with great success in trauma research and in quality programmes to improve trauma care. To this date no valid trauma score has been developed for the Indian population.

Study design

This retrospective cohort study used a dataset of 16047 trauma-patients from four public university hospitals in urban India, which was divided into derivation and validation subsets. All injuries in the dataset were assigned an international classification of disease (ICD) code. Survival Risk Ratios (SRRs), for mortality within 24 hours and 30 days were then calculated for each ICD-code and used to calculate the corresponding ICISS. Score performance was measured using discrimination by calculating the area under the receiver operating characteristics curve (AUROCC) and calibration by calculating the calibration slope and intercept to plot a calibration curve.

Results

Predictions of 30-day mortality showed an AUROCC of 0.618, calibration slope of 0.269 and calibration intercept of 0.071. Estimates of 24-hour mortality consistently showed low AUROCCs and negative calibration slopes.

Conclusions

We attempted to derive and validate a version of the ICISS using SRRs calculated from an Indian population. However, the developed ICISS-scores overestimate mortality and implementing these scores in clinical or policy contexts is not recommended. This study, as well as previous reports, suggest that other scoring systems might be better suited for India and other Low- and middle-income countries until more data are available.

Assessment of the predictive value of the International Classification of Diseases Injury Severity Score for trauma mortality in urban India

BACKGROUND

Trauma is the cause of 1.2 million deaths in India annually. Injury severity scores play an important role in trauma research and care because these scores enable the adjustment of trauma severity when comparing mortality outcomes. The generalizability of the International Classification of Diseases Injury Severity Score (ICISS) between different populations is not fully known, and the validity of the ICISS has not been assessed in the Indian context. The aim of this study was to assess the predictive performances of three international versions of the ICISS, derived from data from Australia, New Zealand and pooled data from seven different high-income countries, in trauma patients admitted to four public hospitals in urban India.

MATERIAL AND METHODS

We used patient data from an Indian cohort of 16,047 trauma patients. The patients were assigned an ICISS based on International Classification of Diseases codes using survival risk ratios from publicly available data sets from Australia and New Zealand and with pooled data from seven different high-income countries. Predicted mortality based on the ICISS was compared with observed patient mortality, and the predictive performance was assessed in terms of discrimination and calibration.

RESULTS

Discrimination and calibration did not reach the threshold for predictive performance in any of the ICISS versions used. The threshold value used was 0.8 for discrimination, which was not significantly different from one for the calibration slope and not significantly different from zero for the calibration intercept.

CONCLUSIONS

None of the international versions of the ICISS adequately predicted mortality within the study population, indicating the need for an ICISS version specifically adapted to the Indian context.

Exploring injury severity measures and in-hospital mortality: A multi-hospital study in Kenya

INTRODUCTION

Low- and middle-income countries (LMICs) have a disproportionately high burden of injuries. Most injury severity measures were developed in high-income settings and there have been limited studies on their application and validity in low-resource settings. In this study, we compared the performance of seven injury severity measures: estimated Injury Severity Score (eISS), Glasgow Coma Score (GCS), Mechanism, GCS, Age, Pressure score (MGAP), GCS, Age, Pressure score (GAP), Revised Trauma Score (RTS), Trauma and Injury Severity Score (TRISS) and Kampala Trauma Score (KTS), in predicting in-hospital mortality in a multi-hospital cohort of adult patients in Kenya.

METHODS

This study was performed using data from trauma registries implemented in four public hospitals in Kenya. Estimated ISS, MGAP, GAP, RTS, TRISS and KTS were computed according to algorithms described in the literature. All seven measures were compared for discrimination by computing area under curve (AUC) for the receiver operating characteristics (ROC), model fit information using Akaike information criterion (AIC), and model calibration curves. Sensitivity analysis was conducted to include all trauma patients during the study period who had missing information on any of the injury severity measure(s) through multiple imputations.

RESULTS

A total of 16,548 patients were included in the study. Complete data analysis included 14,762 (90.2%) patients for the seven injury severity measures. TRISS (complete case AUC: 0.889, 95% CI: 0.866-0.907) and KTS (complete case AUC: 0.873, 95% CI: 0.852-0.892) demonstrated similarly better discrimination measured by AUC on in-hospital deaths overall in both complete case analysis and multiple imputations. Estimated ISS had lower AUC (0.764, 95% CI: 0.736-0.787) than some injury severity measures. Calibration plots showed eISS and RTS had lower calibration than models from other injury severity measures.

CONCLUSIONS

This multi-hospital study in Kenya found statistical significant higher performance of KTS and TRISS than other injury severity measures. The KTS, is however, an easier score to compute as compared to the TRISS and has stable good performance across several hospital settings and robust to missing values. It is therefore a practical and robust option for use in low-resource settings, and is applicable to settings similar to Kenya.

Comparison of ISS, NISS, and RTS score as predictor of mortality in pediatric fall

Background

Studies to identify an ideal trauma score tool representing prediction of outcomes of the pediatric fall patient remains elusive. Our study was undertaken to identify better predictor of mortality in the pediatric fall patients.

Methods

Data was retrieved from prospectively maintained trauma registry project at level 1 trauma center developed as part of Multicentric Project—Towards Improving Trauma Care Outcomes (TITCO) in India. Single center data retrieved from a prospectively maintained trauma registry at a level 1 trauma center, New Delhi, for a period ranging from 1 October 2013 to 17 February 2015 was evaluated. Standard anatomic scores Injury Severity Score (ISS) and New Injury Severity Score (NISS) were compared with physiologic score Revised Trauma Score (RTS) using receiver operating curve (ROC).

Results

Heart rate and RTS had a statistical difference among the survivors to nonsurvivors. ISS, NISS, and RTS were having 50, 50, and 86% of area under the curve on ROCs, and RTS was statistically significant among them.

Conclusions

Physiologically based trauma score systems (RTS) are much better predictors of inhospital mortality in comparison to anatomical based scoring systems (ISS and NISS) for unintentional pediatric falls.