Prevalence and Severity of Burn Scars in Rural Mozambique
Bibliographic record
Abstract
BACKGROUND: Burn injuries are common in low- and middle-income countries (LMICs) and their associated disability is tragic. This study is the first to explore burn scars in rural communities in Mozambique. This work also validated an innovate burn assessment tool, the Morphological African Scar Contractures Classification (MASCC), used to determine surgical need. METHODS: Using a stratified, population-weighted survey, the team interviewed randomly selected households from September 2012 to June 2013. Three rural districts (Chókwè, Nhamatanda, and Ribáuè) were selected to represent the southern, central and northern regions of the country. Injuries were recorded, documented with photographs, and approach to care was gathered. A panel of residents and surgeons reviewed the burn scar images using both the Vancouver Scar Scale and the MASCC, a validated visual scale that categorizes patients into four categories corresponding to levels of surgical intervention. RESULTS: Of the 6104 survey participants, 6% (n = 370) reported one or more burn injuries. Burn injuries were more common in females (57%) and most often occurred on the extremities. Individuals less than 25 years old had a significantly higher odds of reporting a burn scar compared to people older than 45 years. Based on the MASCC, 12% (n = 42) would benefit from surgery to treat contractures. CONCLUSION: Untreated burn injuries are prevalent in rural Mozambique. Our study reveals a lack of access to surgical care in rural communities and demonstrates how the MASCC scale can be used to extend the reach of surgical assessment beyond the hospital through community health workers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".