Trauma care and referral patterns in Rwanda: implications for trauma system development
Bibliographic record
Abstract
BACKGROUND: Trauma remains a leading cause of death worldwide. The development of trauma systems in low-resource settings may be of benefit. The objective of this study was to describe operative procedures performed for trauma at a tertiary care facility in Kigali, Rwanda, and to evaluate geographical variations and referral patterns of trauma care. METHODS: We retrospectively reviewed all prospectively collected operative cases performed at the largest referral hospital in Rwanda, the Centre Hospitalier Universitaire de Kigali (CHUK), between June 1 and Dec. 1, 2011, for injury-related diagnoses. We used the Pearson χ² and Fisher exact tests to compare cases arising from within Kigali to those transferred from other provinces. Geospatial analyses were also performed to further elucidate transfer patterns. RESULTS: Over the 6-month study period, 2758 surgical interventions were performed at the CHUK. Of these, 653 (23.7%) were for trauma. Most patients resided outside of Kigali city, with 337 (58.0%) patients transferred from other provinces and 244 (42.0%) from within Kigali. Most trauma procedures were orthopedic (489 [84.2%]), although general surgery procedures represented a higher proportion of trauma surgeries in patients from other provinces than in patients from within Kigali (28 of 337 [8.3%] v. 10 of 244 [4.1%]). CONCLUSION: To our knowledge, this is the first study to highlight geographical variations in access to trauma care in a low-income country and the first description of trauma procedures at a referral centre in Rwanda. Future efforts should focus on maturing prehospital and interfacility transport systems, strengthening district hospitals and further supporting referral institutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".