Injury patterns of patients presenting to a non-governmental hospital in Western Uganda

Abstract

Introduction Injury is a leading cause of morbidity and mortality globally and disproportionately affects low-income countries. While most injury data comes from tertiary care centers in urban settings, the purpose of this study was to describe the characteristics and severity of injury in rural Uganda and the associated treatment patterns and delays in care. Methods This is a retrospective cohort study of a trauma registry that was implemented at Masindi-Kitara Medical Center (MKMC), a rural hospital in Western Uganda. Demographic information, injury characteristics, modified Kampala Trauma Scores (M-KTS), and treatment modalities over a 12 month period were retrospectively collected from paper-based registry forms completed for all injury patients presenting to MKMC. Results A total of 350 patients were entered into the trauma registry. Most patients were male (71.2%) with a median age of 26.5 years. Motorcycle crashes were the most prevalent mechanism of injury (42.3%) with the majority being unhelmeted (83.3%). Soft tissue injury was the most common diagnosis (44.9%). Patients were frequently treated in the outpatient department and then discharged (54.8%). Patients requiring admission or transfer (M-KTS = 11.57 or 11.67) tended to have a lower M-KTS than discharged patients (M-KTS = 12.75). Analgesics (74.6%) and antibiotics (52.9%) were the most common treatments administered. For those patients requiring admission (29.4%), only one in-hospital death was documented. Thirty-nine percent of patients reported a delay in seeking care, most frequently due to lack of transportation (31.5%) with a median time of delay of 11 h. Conclusion Road traffic injuries were the leading cause of injury in Masindi, with a high proportion of injuries associated with unhelmeted motorcycle crashes. Future opportunities to prevent injury and improve care may be seen through improved prehospital care, enforcement of helmet laws, increased access to neurosurgical services, and enactment of hospital quality improvement measures.

The Kampala Trauma Score: A 20-year track record

“…The most frequently mentioned reason for using the KTS for injury severity scoring is that it effectively predicts in-hospital mortality 15–17,21–40 . Several publications mentioned that the KTS compares well with other major scores 11,25,26,28,31,32,38,40–42 .…”

“…11,15,17,24,49,[57][58][59][60] The most commonly mentioned of these is that the KTS limits comparison with other published data that use alternate scoring systems. 17,24,57 studies noted that blood pressure is not always an accurate measure, such as in severely hypotensive patients or morbidly obese patients. 58,59 Another publication noted the KTS does not account for the different physiological and hemodynamic status of young children.…”

“… 11 Each component is straightforward, and relatively easy to collect in most settings, though a few trauma registries in LMICs have experienced difficulty recording respiratory rate. In response, a “modified” version of the KTS (m-KTS) emerged which excludes this variable where respiratory rate data is either unavailable or of low quality 15–17 . All three versions (the KTS, the KTS II, and the m-KTS) require simple addition to calculate and far less time and effort from clinical staff or data collectors than other ISSs.…”

“…of the KTS (m-KTS) emerged which excludes this variable where respiratory rate data is either unavailable or of low quality. [15][16][17] All three versions (the KTS, the KTS II, and the m-KTS) require simple addition to calculate and far less time and effort from clinical staff or data collectors than other ISSs. Recently, a widely accessible "KTS" app for iOS and Androids has been developed that easily does the calculation, further reducing the workload.…”

Piloting a Layperson Prehospital Care System in Rural Uganda

“…They have maintained a hospital-level trauma registry since 2017, which has been previously described in detail. 19 Fifty (50) adult boda drivers from various parts of Masindi were selected for a one-day training course including lectures and small group simulation. Course participants were recruited through the boda driver association and chosen to cover a large portion of the Masindi district.…”