Burn management capacity in low and middle-income countries: A systematic review of 458 hospitals across 14 countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
IMPORTANCE: More than 90% of thermal injury-related deaths occur in low-resource settings. While baseline assessment of burn management capabilities is necessary to guide capacity building strategies, limited data exist from low and middle-income countries (LMICs). OBJECTIVE: The objective of our review is to assess burn management capacity in LMICs. EVIDENCE REVIEW: A PubMed literature review was performed based on studies assessing baseline surgical capacity in individual LMICs. Seven criteria were used to assess burn management capabilities: presence of surgeon, presence of anesthesiologist, basic resuscitation capabilities, acute burn management, management of burn complications, endotracheal intubation and skin grafts. FINDINGS: Fourteen studies were reviewed using data from 458 hospitals in fourteen countries. Of these, 82.3% (284/345) of hospitals had the capacity to provide basic resuscitation and 84.9% (275/324) were capable of providing acute burn management. Endotracheal intubation was only available at 38.3% (51/133) of hospitals. Moreover, only 35.6% (111/312) and 37.9% (120/317) of hospitals were able to provide skin grafts and treat burn complications, respectively. CONCLUSION: Many hospitals in LMICs are capable of initial burn management and basic resuscitation. However, deficiencies still exist in the capacity to systematically provide advanced burn care. Efforts should be made to better document resources in order to guide burn management resource allocation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| 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 it