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

Implementation of a pediatric trauma registry at a national referral center in Kenya: Utility and concern for sustainability

BACKGROUND

Pediatric trauma disproportionately affects low- and middle-income countries, particularly the pediatric trauma systems, are frequently limited. This study assessed the patterns of pediatric traumatic injuries and treatment at the only free-standing public children's hospital in East Africa as well as the implementation and sustainability of the trauma registry.

METHODS

A prospective pediatric trauma registry was established at Shoe4Africa Children's Hospital (S4A) in Eldoret, Kenya. All trauma patients over a six-month period were enrolled. Descriptive analyses were completed via SAS 9.4 to uncover patterns of demographics, trauma mechanisms and injuries, as well as outcomes. Implementation was assessed using the RE-AIM framework.

RESULTS

The 425 patients had a median age of 5.14 years (IQR 2.4, 8.7). Average time to care was 267.5 min (IQR 134.0, 625.0). The most common pediatric trauma mechanisms were falls (32.7 %) and burns (17.7 %), but when stratified by age group, toddlers had a higher risk of sustaining injuries from burns and poisonings. Over half (56.2 %) required an operation during the hospitalization. Overall, implementation of the registry was limited by the clinical burden and inadequate personnel. Sustainability of the registry was limited by finances.

CONCLUSIONS

This is the first study to describe the trauma epidemiology from a Kenyan public pediatric hospital. Maintenance of the trauma registry failed due to cost. Streamlining global surgery efforts through implementation science may allow easier development of trauma registries to then identify modifiable risk factors to prevent trauma and long-term outcomes to understand associated disability.

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.

Comparative Evaluation of Mortality Predictors in Trauma Patients: A Prospective Single-center Observational Study Assessing Injury Severity Score Revised Trauma Score Trauma and Injury Severity Score and Acute Physiology and Chronic Health Evaluation II Scores

Aim

This prospective cohort study aimed to compare the predictive accuracy of outcome (survival/death) among trauma patients using various prognostic scores.

Methods

Over 3 months, 240 trauma patients in a tertiary care hospital were assessed for demographic details, trauma characteristics, vital signs, Glasgow coma scale, arterial blood gas values, and lab markers. Injury severity score (ISS), revised trauma score (RTS), trauma and injury severity score (TRISS), and acute physiology and chronic health evaluation II (APACHE II) were applied at admission, 24 hours, and 48 hours post-admission.

Results

Road traffic accidents (55.83%) were the primary cause of trauma, followed by falls (33.75%) and violence (10.41%). The all-cause mortality rate was 23.33%, with 34.16% requiring ICU admission. Head injuries (65.83%) were both the most frequent injury site and cause of mortality.

Conclusion

Analysis indicated that APACHE II outperformed other scores in predicting outcomes, with ISS following closely. The study concludes that trauma severity correlates with ICU admission and mortality, emphasizing APACHE II as a superior predictor, particularly for traumatic brain injuries leading to ICU admission and mortality.

Clinical significance

This study contributes to the existing body of knowledge by addressing the gap in comparing prognostic abilities among scoring systems for trauma patients. The unexpected superiority of APACHE II suggests its potential as a valuable tool in predicting outcomes in this specific patient population.

How to cite this article

Gupta J, Kshirsagar S, Naik S, Pande A. Comparative Evaluation of Mortality Predictors in Trauma Patients: A Prospective Single-center Observational Study Assessing Injury Severity Score Revised Trauma Score Trauma and Injury Severity Score and Acute Physiology and Chronic Health Evaluation II Scores. Indian J Crit Care Med 2024;28(5):475-482.

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.

Injury severity score as a predictor of mortality in patients with abdominal trauma at a tertiary Nigerian hospital

Background

Abdominal trauma is a major cause of morbidity and mortality in low-and middle-income countries. Typical patients present late and very sick with early recognition key to improving outcome. There is a paucity of trauma data in this environment and trauma scoring systems which have been validated in the developed world are yet to find widespread use here.

Aim

This study aimed at evaluating role of injury severity score (ISS) in predicting mortality.

Patients and Methods

This is a retrospective observational study of patients with abdominal trauma who presented at the University of Ilorin Teaching Hospital from 2013 to 2019. Records were identified and data were extracted and analyzed using Statistical package for social sciences 23.

Results

A total of 87 patients were included in the study. There were 73 males and 14 females. The mean overall ISS in this study was 16.06 ± 7.9. Concerning morbidity, the area under the receiver operating characteristic curve in predicting morbidity was 0.843 (95% confidence interval 0.737-0.928). ISS had a strong sensitivity of 90% and specificity 55% at a cut-off of 14.50. Also, the area under the receiver operating characteristic curve in predicting mortality was 0.746 (95% confidence interval 0.588-0.908) and at a cut-off of 16.50; ISS had a specificity of 80% and sensitivity of 60%. The mean ISS of patients with mortality was 22.60 ± 10.5 while the survivors had a mean ISS of 14.7 ± 6.5 (P <.001). The mean ISS for patients who had morbidity was 22.8 ± 8.1 while those without morbidity had a mean ISS of 13.1 ± 5.7 (P <.05).

Conclusion

ISS was a good predictor of morbidity and mortality in abdominal trauma in patients in this study. A prospective study with standardized abdominal imaging would be needed to further validate this scoring tool.

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.

Malawi Trauma Score is Predictive of Mortality at a District Hospital: A Validation Study

BACKGROUND

Trauma scoring systems can identify patients who should be transferred to referral hospitals, but their utility in LMICs is often limited. The Malawi Trauma Score (MTS) reliably predicts mortality at referral hospitals but has not been studied at district hospitals. We sought to validate the MTS at a Malawi district hospital and evaluate whether MTS is predictive of transfer to a referral hospital.

METHODS

We performed a retrospective study using trauma registry data from Salima District Hospital (SDH) from 2017 to 2021. We excluded patients brought in dead, discharged from the Casualty Department, or missing data needed to calculate MTS. We used logistic regression modeling to study the relationship between MTS and mortality at SDH and between MTS and transfer to a referral hospital. We used receiver operating characteristic analysis to validate the MTS as a predictor of mortality.

RESULTS

We included 2196 patients (84.3% discharged, 12.7% transferred, 3.0% died). These groups had similar ages, sex, and admission vitals. Mean (SD) MTS was 7.9(3.0) among discharged patients, 8.4(3.9) among transferred patients, and 14.2(8.0) among patients who died (p < 0.001). Higher MTS was associated with increased odds of mortality at SDH (OR 1.21, 95% CI 1.14-1.29, p < 0.001) but was not related to transfer. ROC area for mortality was 0.73 (95% CI 0.65-0.80).

CONCLUSIONS

MTS is predictive of district hospital mortality but not inter-facility transfer. We suggest that MTS be used to identify patients with severe trauma who are most likely to benefit from transfer to a referral hospital.

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.

Interest of the MGAP score on in-hospital trauma patients: Comparison with TRISS, ISS and NISS scores

Trauma scoring systems were created to predict mortality and enhance triage capabilities. However, efficacy of scoring systems to predict mortality and accuracy of originally reported severity thresholds remains uncertain. A single-center, retrospective study was conducted at University of Virginia (UVA), an American College of Surgeons verified Level I trauma center. We compared four scoring systems: MGAP (Mechanism, Glasgow Coma Scale, Age, and arterial pressure), Injury Severity Score (ISS), New Injury Severity Score (NISS), and Trauma Related Injury Severity Score (TRISS) to predict in-hospital mortality and disposition from the emergency department to higher acuity level of care including mortality (i.e. operating room, intensive care unit, morgue) versus standard floor admission using area under the curve (AUC) for receiver operating characteristic analysis. Second, we examined sensitivity of these scores at standard thresholds to determine if adjustments were needed to minimize under-triage (sensitivity ≥95%). TRISS was the best predictor of mortality in a cohort of n = 16,265 with AUC of 0.920 (95% CI: 0.911-0.929, p<0.0001), followed by MGAP with AUC of 0.900 (95% CI: 0.889-0.911, p<0.0001), and finally ISS and NISS (0.830 (95% CI: 0.814-0.847) and 0.827 (95% CI: 0.809-0.844) respectively). NISS was the best predictor of high acuity disposition with an AUC of 0.729 (95% CI: 0.721-0.736, p<0.0001), followed by ISS with AUC of 0.714 (95% CI: 0.707-0.722, p<0.0001), and finally TRISS and MGAP (0.673 (95% CI: 0.665-0.682) and 0.613 (95% CI: 0.604-0.621) respectively (p<0.0001). At historic thresholds, no scoring system displayed adequate sensitivity to predict mortality, with values ranging from 73% for ISS to 80% for NISS. In conclusion, in the reported study cohort, TRISS was the best predictor of mortality while NISS was the best predictor of high acuity disposition. We also stress updating scoring system thresholds to achieve ideal sensitivity, and investigating how scoring systems derived to predict mortality perform when predicting indicators of morbidity such as disposition from the emergency department.

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.

Validation of the PRESTO score in injured children in a South-African quaternary trauma center

INTRODUCTION

The Pediatric RESuscitation and Trauma Outcome (PRESTO) model was developed for standardized risk-adjustment in pediatric trauma and is adapted to low-resource settings. It includes easily-accessible demographic and physiologic variables that are available at point of care in virtually any setting. The purpose of this study was to evaluate the PRESTO model's ability to predict in-hospital mortality in a South African pediatric trauma unit by comparing it to the widely used Injury Severity Score (ISS).

METHODS

Data prospectively collected between 2007 and 2017 in the Inkosi Albert Luthuli Central Hospital Trauma Registry were retrospectively reviewed. Injured children younger than 14 years were included if they were admitted to hospital or died as a result of their injury. We excluded patients with minor injuries who were treated and discharged home and patients with incomplete hospital disposition data. Receiver-Operating Characteristic (ROC) curves were constructed for PRESTO and ISS, and the areas under the curve (AUCs) were compared using Delong's test. The sensitivity and specificity of PRESTO were calculated at different prognostic threshold values identified through literature review.

RESULTS

We identified 419 patients; 67 died in hospital (16%). The AUCs for PRESTO and ISS were 0.82 (95% confidence interval CI [0.76-0.87]) and 0.75 (CI [0.68-0.81]), respectively. This difference trended towards statistical significance (p = 0.07). Using the optimal threshold of 0.13 described in the original publication, PRESTO had a 97% sensitivity and 37% specificity, while a threshold of 0.50 yielded 90% sensitivity and 54% specificity. The mean predicted probability of in-hospital death among patients who died was 0.79. Using this value as a threshold yielded the 57% sensitivity and 85% specificity.

CONCLUSION

This analysis has demonstrated the validity of the PRESTO model for in-hospital mortality prediction for pediatric trauma patients in the setting of a dedicated high-complexity trauma unit in a South African trauma referral center.

LEVEL OF EVIDENCE

Level III: Case-control.

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

Background

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

Materials and methods

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

Results

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

Conclusions

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

PROSPERO registration number

CRD42017064600.

Comparative analysis of MGAP, GAP, and RISC2 as predictors of patient outcome and emergency interventional need in emergency room treatment of the injured

PURPOSE

Little is known about the capabilities of triage and risk scores to predict the outcomes of injured patients, other than mortality, or to determine the need for trauma center resources.

METHODS

Retrospective analysis of prospectively gathered monocenter data on consecutively admitted adult emergency room trauma patients. For each patient, the GAP (Glasgow Coma Scale, Age and Pressure), MGAP (mechanism + GAP) scores and the revised injury severity classification 2 (RISC2) were calculated. The predictive performance of these scores was compared for the assessment of trauma severity, hospital resource need and early patient outcomes (area under the receiver operator characteristics, AUROC).

RESULTS

2112 patients were evaluated [mean age 49.1 years; Injury Severity Score (ISS) 9.5]. GAP, MGAP, and RISC2 worked best at predicting mortality (AUROC 93.2, 93.5 and 96.1%, respectively). Other endpoints such as ISS > 15, emergency interventions, disability status, and return-not-home were predicted less precisely by these three scores, better by RISC2 (AUROC range 66.2-88.8%) than by (M)GAP-scores (55.2-84.1%), except for preclinical interventions. Over- and undertriage rates for the (M)GAP scores varied between 27.5-53.4% and 10.4-30%, respectively.

CONCLUSION

The almost comparable precision of the three risk scores in the prediction of outcome or interventional need following trauma, and the fact, that the RISC2 can only be calculated following extensive diagnostics, favor earlier applicable (M)GAP scoring in the emergency setting. Overall, due to its easier use, the GAP appears to be the most preferable for the early assessment and triage of the injured in a trauma setting based on this European trauma center experience (NCT02165137).

The search for a simple injury score to reliably discriminate the risk of in-hospital mortality in South Africa

BACKGROUND

The Injury Severity Score and Trauma and Injury Severity Score are used commonly to quantify the severity of injury, but they require comprehensive data collection that is impractical in many low- and middle-income countries . We sought to develop an injury score that is more feasible to implement in low- and middle-income countries with discrimination similar to the Injury Severity Score and the Trauma and Injury Severity Score.

METHODS

Clinical data from KwaZulu-Natal, South Africa were used to compare the discrimination of the Injury Severity Score and the Trauma and Injury Severity Score with that of the 5, simple injury scores that rely primarily on physiologic data: Revised Trauma Score for Triage, "Mechanism, Glasgow Coma Scale, Age, Pressure" Score, Kampala Trauma Score, modified Kampala Trauma Score, and "Reversed Shock Index Multiplied by Glasgow Coma Scale" Score.

RESULTS

Data for 3,991 patients were analyzed. The Trauma and Injury Severity Score, the Injury Severity Score, and Kampala Trauma Score had similar discrimination (area under the receiver operating curve 0.85, 0.84, and 0.84, respectively). The simple injury scores demonstrated worse discrimination among patients presenting more than 6 hours postinjury, although Kampala Trauma Score maintained the best discrimination of the simple injury scores.

CONCLUSION

In this patient population, Kampala Trauma Score demonstrated discrimination similar to the Injury Severity Score and the Trauma and Injury Severity Score and may be useful to quantify the severity of injury when calculation of the Injury Severity Score or the Trauma and Injury Severity Score is not feasible. Delay in presentation can degrade the discrimination of simple injury scores that rely primarily on physiologic data.

Both the multiplicative and single-worst-injury International Classification of Diseases Injury Severity Score underperform in urban Indian hospitals

Introduction

Trauma accounts for 9% of all deaths worldwide, killing almost five million people annually. As India accounts for more than one million of these deaths, research on local trauma care is of great importance. A key aspect of such research is outcome comparisons between contexts. One tool to adjust these comparisons for trauma severity is the International Classification of Diseases Injury Severity Score. The aim was to assess two versions of this score in India.

Methods

The data used were from the project Towards Improved Trauma Care Outcomes in India. Published survival risk ratios were used to calculate multiplicative-International Classification of Diseases Injury Severity Score and single-worst-injury-International Classification of Diseases Injury Severity Score for the 200 most recent non-surviving patients and the surviving patients during the same period. Score performance was measured in discrimination and calibration.

Results

The 30-day prediction single-worst-injury-International Classification of Diseases Injury Severity Score discriminated best with an area under the receiver operating characteristics curve of 0.668 (95% CI 0.645–0.690) and a calibration slope of 0.830 (95% CI 0.708–0.940).

Conclusions

The single-worst-injury-International Classification of Diseases Injury Severity Score applied on 30-day mortality was the only score to calibrate on a satisfactory level. None of the scores had an acceptable discrimination. In interpreting these findings, we see that none of the tested scores can currently be implemented in the studied hospitals.

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.

Mortality and functional outcomes after a spontaneous subarachnoid haemorrhage: A retrospective multicentre cross-sectional study in Kenya

INTRODUCTION

Despite a reduction in poor outcomes in recent decades, spontaneous subarachnoid haemorrhage (SAH) remains associated with severe disability and high mortality rates. The exact extent of these outcomes is however unknown in Africa. This study aimed to determine the mortality and functional outcomes of patients with SAH in Kenya.

METHODS

We conducted a retrospective multicentre cross-sectional study involving patients admitted with SAH to three referral hospitals in Nairobi. All patients with a confirmed (primary) discharge diagnosis of first-time SAH between January 2009 and November 2017 were included (n = 158). Patients who had prior head trauma or cerebrovascular disease (n = 53) were excluded. Telephone interviews were conducted with surviving patients or their next of kin to assess out-of-hospital outcomes (including functional outcomes) based on modified Rankin Scale (mRS) scores. Chi-square and Fisher's exact tests were used to assess associations between mortality and functional outcomes and sample characteristics.

RESULTS

Of the 158 patients sampled, 38 (24.1%) died in hospital and 42 (26.6%) died within 1 month. In total, 87 patients were discharged home and followed-up in this study, of which 72 reported favourable functional outcomes (mRS ≤2). This represented 45.6% of all patients who presented alive, pointing to high numbers of unfavourable outcomes post SAH in Kenya.

CONCLUSIONS

Mortality following SAH remains high in Kenya. Patients who survive the initial ictus tend to do well after treatment, despite resource constraints.

LIMITATIONS

The study findings should be interpreted with caution because of unavoidable limitations in the primary data. These include its retrospective nature, the high number of patients lost to follow up, missing records and diagnoses, and/or possible miscoding of cases.

Longitudinal depressive and anxiety symptoms of adult injury patients in Kenya and their risk factors

Background: Injuries account for a significant proportion of the health and economic burden for populations in low- and middle-income countries. However, little is known about psychological distress trajectories amongst injury survivors in low- and middle-income countries.Methods: Adult injury patients (n = 644) admitted to Kenyatta National Hospital in Nairobi, Kenya, were enrolled and interviewed in the hospital, and at 1, 2-3, and 4-7 months after hospital discharge through phone to assess depressive and anxiety symptoms and level of disability. Growth mixture modeling was applied to identify latent trajectories of depressive and anxiety symptoms.Results: Elevated depressive and moderate-level anxiety symptoms (13%) and low depressive and anxiety symptoms (87%) trajectories were found between hospitalization and up to seven months after hospital discharge. Being female, prior trauma experience, longer hospitalization, worse self-rated health status while in the hospital, and lack of monetary assistance during hospitalization were associated with the elevated symptoms trajectory. The higher symptoms trajectory associated with higher disability levels after hospital discharge and significantly lower proportion of resuming daily activities and work.Conclusion: The persistence of elevated depressive symptoms and associated reduced functioning several months after physical injury underscores the importance of identifying populations at risk for preventive and early interventions.Implications for RehabilitationHealth providers following up with injury survivors should screen for depressive and anxiety symptomsSpecial attention to women and people with a potential traumatic exposure historyIncorporation of evidence-based culturally adapted psychosocial interventions in rehabilitation and outpatient clinics.

Determinants of emergency department disposition of patients with traumatic brain injury in Uganda: results from a registry

Background

Traumatic brain injuries (TBIs) are a common cause of emergency department (ED) visits and hospital admissions in Kampala, Uganda. The objective of this study was to assess determinants of ED discharge disposition based on patient demographic and injury characteristics. Four ED outcomes were considered: discharge home, hospital admission, death, and others.

Methods

This prospective study was conducted at Mulago National Referral Hospital, Kampala, Uganda, from May 2016 to July 2017. Patients of all age groups presenting with TBI were included. Patient demographics, external causes of injury, TBI characteristics, and disposition from EDs were noted. Injury severity was estimated using the Glasgow Coma Scale (GCS), Kampala Trauma Score (KTS), and the Revised Trauma Score (RTS). A multinomial logistic regression model was used to estimate conditional ORs of hospital admission, death, and other dispositions compared with the reference category “discharged home”.

Results

A total of 3944 patients were included in the study with a male versus female ratio of 5.5:1 and a mean age of 28.5 years (SD=14.2). Patients had closed head injuries in 62.9% of cases. The leading causes of TBIs were road traffic crashes (58.8%) and intentional injuries (28.7%). There was no significant difference between the four discharge categories with respect to age, sex, mode of arrival, cause of TBI, place of injury, type of head injury, transport time, and RTS (p>0.05). There were statistically significant differences between the four discharge categories for a number of serious injuries, GCS on arrival, change in GCS, and KTS. In a multinomial logistic regression model, change in GCS, area of residence, number of serious injuries, and KTS were significant predictors of ED disposition.

Discussion

This study provides evidence that ED disposition of patients with TBI is differentially affected by injury characteristics and is largely dependent on injury severity and change in GCS during ED stay.

Level of evidence

Level II.

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.

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.

Traumatic brain injury in Uganda: exploring the use of a hospital based registry for measuring burden and outcomes

Objective

Lack of data on traumatic brain injuries (TBI) hinders the appreciation of the true magnitude of the TBI burden. This paper describes a scientific approach for hospital based systematic data collection in a low-income country. The registry is based on the evaluation framework for injury surveillance systems which comprises a four-step approach: (1) identifying characteristics that assess a surveillance system, (2) review of the identified variables based on adopted specific, measurable, assignable, realistic, and time-related criteria, (3) assessment of the proposed variables and system characteristics by an expert panel, and (4) development and application of a rating system.

Results

The electronic hospital-based TBI registry is designed through a collaborative approach to capture comprehensive, yet context specific, information on each TBI case, from the time of injury until death or discharge from the hospital. It includes patients’ demographics, pre-hospital and hospital assessment and care, TBI causes, injury severity, and patient outcomes. The registry in Uganda will open the opportunity to replicate the process in other similar context and contribute to a better understanding of TBI in these settings, and feed into the global agenda of reducing deaths and disabilities from TBI in low-and middle-income countries.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3419-1) contains supplementary material, which is available to authorized users.