Diagnostic Accuracy of The Kampala Trauma Score using Estimated Abbreviated Injury Scale Scores and Physician Opinion

Gardner, Andrew J.; Forson, Paa Kobina; Oduro, George; Dike, Nkechi O.; Stewart, Barclay T; Glover, Paul; Oteng, Rockefeller; Maio, Ron

doi:10.1017/s1049023x17005994

Cited by 5 publications

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“…*Includes choking (1 patient), near-drowning (3), electrical injury (2), sexual assault (2) and non-specified (27). Deidentified data for patients aged less than 18 years were abstracted over a 4-year period from May 2011 to July 2015.…”

Section: Discussionmentioning

confidence: 99%

“…They also allow the development of locally relevant and properly adapted metrics for patient-level risk adjustment and severity scoring, such as the Kampala Trauma Score (KTS) 27,28 . They also allow the development of locally relevant and properly adapted metrics for patient-level risk adjustment and severity scoring, such as the Kampala Trauma Score (KTS) 27,28 .…”

Section: Discussionmentioning

confidence: 99%

“…Several studies 27,28,32 have documented the appropriateness of using the KTS, an aggregate of systolic BP, neurological status, age and respiratory rate, to stratify injury severity. Several studies 27,28,32 have documented the appropriateness of using the KTS, an aggregate of systolic BP, neurological status, age and respiratory rate, to stratify injury severity.…”

Section: Discussionmentioning

confidence: 99%

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Epidemiology of paediatric injuries in Rwanda using a prospective trauma registry

et al. 2020

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Background: Child survival initiatives historically prioritized efforts to reduce child morbidity and mortality from infectious diseases and maternal conditions. Little attention has been devoted to paediatric injuries in resource-limited settings. This study aimed to evaluate the demographics and outcomes of paediatric injury in a sub-Saharan African country in an effort to improve prevention and treatment.Methods: A prospective trauma registry was established at the two university teaching campuses of the University of Rwanda to record systematically patient demographics, prehospital care, initial physiology and patient outcomes from May 2011 to July 2015. Univariable analysis was performed for demographic characteristics, injury mechanisms, geographical location and outcomes. Multivariable analysis was performed for mortality estimates.Results: Of 11 036 patients in the registry, 3010 (27⋅3 per cent) were under 18 years of age. Paediatric patients were predominantly boys (69⋅9 per cent) and the median age was 8 years. The mortality rate was 4⋅8 per cent. Falls were the most common injury (45⋅3 per cent), followed by road traffic accidents (30⋅9 per cent), burns (10⋅7 per cent) and blunt force/assault (7⋅5 per cent). Patients treated in the capital city, Kigali, had a higher incidence of head injury (7⋅6 per cent versus 2⋅0 per cent in a rural town, P < 0⋅001; odds ratio (OR) 4⋅08, 95 per cent c.i. 2⋅61 to 6⋅38) and a higher overall injury-related mortality rate (adjusted OR 3⋅00, 1⋅50 to 6⋅01; P = 0⋅019). Pedestrians had higher overall injury-related mortality compared with other road users (adjusted OR 3⋅26, 1⋅37 to 7⋅73; P = 0⋅007).Conclusion: Paediatric injury is a significant contributor to morbidity and mortality. Delineating trauma demographics is important when planning resource utilization and capacity-building efforts to address paediatric injury in low-resource settings and identify vulnerable populations.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Epidemiology of paediatric injuries in Rwanda using a prospective trauma registry

et al. 2020

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“…The four prediction models we compared with the clinicians’ triage decisions were the Revised Trauma Score (RTS),5 the Glasgow Coma Scale, Age and Systolic Blood Pressure (GAP) score,2 the Kampala Trauma Score (KTS)6 and a prediction model previously published by us, here referred to as the Gerdin et al model 7. The rationale for studying these specific models was that RTS is commonly considered the gold standard of physiological trauma severity scoring,8 KTS has been shown to accurately predict inhospital mortality in both low-income, middle-income and high-income settings,9 10 and both GAP and the Gerdin et al model have been shown to predict short-term trauma mortality 8 11. The models considered age, systolic blood pressure, heart rate, Glasgow Coma Scale score, alert, voice, pain or unresponsive, respiratory rate and number of serious injuries (table 1).…”

Section: Methodsmentioning

confidence: 99%

Comparison of emergency department trauma triage performance of clinicians and clinical prediction models: a cohort study in India

et al. 2020

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ObjectiveThe aim of this study was to evaluate and compare the abilities of clinicians and clinical prediction models to accurately triage emergency department (ED) trauma patients. We compared the decisions made by clinicians with the Revised Trauma Score (RTS), the Glasgow Coma Scale, Age and Systolic Blood Pressure (GAP) score, the Kampala Trauma Score (KTS) and the Gerdin et al model.DesignProspective cohort study.SettingThree hospitals in urban India.ParticipantsIn total, 7697 adult patients who presented to participating hospitals with a history of trauma were approached for enrolment. The final study sample included 5155 patients. The majority (4023, 78.0%) were male.Main outcome measureThe patient outcome was mortality within 30 days of arrival at the participating hospital. A grid search was used to identify model cut-off values. Clinicians and categorised models were evaluated and compared using the area under the receiver operating characteristics curve (AUROCC) and net reclassification improvement in non-survivors (NRI+) and survivors (NRI−) separately.ResultsThe differences in AUROCC between each categorised model and the clinicians were 0.016 (95% CI −0.014 to 0.045) for RTS, 0.019 (95% CI −0.007 to 0.058) for GAP, 0.054 (95% CI 0.033 to 0.077) for KTS and −0.007 (95% CI −0.035 to 0.03) for Gerdin et al. The NRI+ for each model were −0.235 (−0.37 to −0.116), 0.17 (−0.042 to 0.405), 0.55 (0.47 to 0.65) and 0.22 (0.11 to 0.717), respectively. The NRI− were 0.385 (0.348 to 0.4), −0.059 (−0.476 to −0.005), −0.162 (−0.18 to −0.146) and 0.039 (−0.229 to 0.06), respectively.ConclusionThe findings of this study suggest that there are no substantial differences in discrimination and net reclassification improvement between clinicians and all four clinical prediction models when using 30-day mortality as the outcome of ED trauma triage in adult patients.Trial registration numberClinicalTrials.gov Registry (NCT02838459).

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“…14 Although trauma prognostication scores such as the KTS and RTS have been extensively compared to each other, 2 there are minimal data evaluating the clinical accuracy of the prolifically used TEWS as compared to trauma scores. 22,23 As a result, it is unclear whether there is additional benefit conferred by the use of injury-specific scores in LMIC settings for acutely injured patients beyond the use of standard triage approaches. This study compared the accuracy of the KTS, RTS, and TEWS in predicting mortality for injured patients at the emergency department (ED) of the Centre Hospitalier Universitaire de Kigali (CHUK), a tertiary care hospital in Rwanda that has implemented use of the TEWS in standard emergency care triage practice.…”

Section: Introductionmentioning

confidence: 99%

Performance of Prognostication Scores for Mortality in Injured Patients in Rwanda

et al. 2021

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Introduction: While trauma prognostication and triage scores have been designed for use in lowerresourced healthcare settings specifically, the comparative clinical performance between trauma-specific and general triage scores for risk-stratifying injured patients in such settings is not well understood. This study evaluated the Kampala Trauma Score (KTS), Revised Trauma Score (RTS), and Triage Early Warning Score (TEWS) for accuracy in predicting mortality among injured patients seeking emergency department (ED) care at the Centre Hospitalier Universitaire de Kigali (CHUK) in Rwanda. Methods: A retrospective, randomly sampled cohort of ED patients presenting with injury was accrued from August 2015-July 2016. Primary outcome was 14-day mortality and secondary outcome was overall facilitybased mortality. We evaluated summary statistics of the cohort. Bootstrap regression models were used to compare areas under receiver operating curves (AUC) with associated 95% confidence intervals (CI). Results: Among 617 cases, the median age was 32 years and 73.5% were male. The most frequent mechanism of injury was road traffic incident (56.2%). Predominant anatomical regions of injury were craniofacial (39.3%) and lower extremities (38.7%), and the most common injury types were fracture (46.0%) and contusion (12.0%). Fourteen-day mortality was 2.6% and overall facility-based mortality was 3.4%. For 14-day mortality, TEWS had the highest accuracy (AUC = 0.88, 95% CI, 0.76-1.00), followed by RTS (AUC = 0.73, 95% CI, 0.55-0.92), and then KTS (AUC = 0.65, 95% CI, 0.47-0.84). Similarly, for facility-based mortality, TEWS (AUC = 0.89, 95% CI, 0.79-0.98) had greater accuracy than RTS (AUC = 0.76, 95% CI, 0.61-0.91) and KTS (AUC = 0.68, 95% CI, 0.53-0.83). On pairwise comparisons, RTS had greater prognostic accuracy than KTS for 14-day mortality (P = 0.011) and TEWS had greater accuracy than KTS for overall (P = 0.007) mortality. However, TEWS and RTS accuracy were not significantly different for 14-day mortality (P = 0.864) or facility-based mortality (P = 0.101). Conclusion: In this cohort of emergently injured patients in Rwanda, the TEWS demonstrated the greatest accuracy for predicting mortality outcomes, with no significant discriminatory benefit found in the use of the trauma-specific RTS or KTS instruments, suggesting that the TEWS is the most clinically useful approach in the setting studied and likely in other similar ED environments. [West J Emerg Med. 2021;22(2)435-444.]

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Diagnostic Accuracy of The Kampala Trauma Score using Estimated Abbreviated Injury Scale Scores and Physician Opinion

Cited by 5 publications

References 0 publications

Epidemiology of paediatric injuries in Rwanda using a prospective trauma registry

Epidemiology of paediatric injuries in Rwanda using a prospective trauma registry

Comparison of emergency department trauma triage performance of clinicians and clinical prediction models: a cohort study in India

Performance of Prognostication Scores for Mortality in Injured Patients in Rwanda

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