A multicenter observational study on the distribution of orthopaedic fracture types across 17 low- and middle-income countries
Bibliographic record
Abstract
OBJECTIVES: To describe the regional distribution of fractures sustained by women and health care system characteristics across 17 low- and middle-income countries (LMICs). METHODS: The INternational ORthopaedic MUlticentre Study in fracture care (INORMUS) is an observational study collecting data on patients in LMICs who sustained a fracture or musculoskeletal injury. As a planned analysis for the INORMUS study, we explored differences in fracture locations and demographics reported among 9878 female patients who sustained a fracture within 17 LMICs in 5 regions (China, Africa, India, Other Asia, and Latin America). RESULTS: Half of our study population (49.6%) was ≥60 years of age. Across all regions, 58.3% of patients possessed health insurance. Latin America possessed the highest proportion (88.8%) of health insurance, while in Africa, patients possessed the lowest (18.0%). Falls from standing were the most prevalent mechanism of injury (51.7%) followed by falls from height (12.8%) and motorcycle-related road traffic injuries (9.7%). The majority of the fractures (65.6%) occurred in patients aged 50 and older. Hip fractures were the most common fracture (26.8%), followed by tibia/fibula (12.6%) and spine fractures (9.7%). Open fractures accounted for 7.6% of fractures and were most commonly tibia/fibula fractures (35.1%). Despite these severe injuries, less than one-third (28.8%) of patients were transported for care after sustaining a fracture by ambulance. Regionally, a majority of female patients in Africa were working age and suffered tibia/fibula (21.6%) and femur fractures (14.0%). Patients in the regional category Other Asia, suffered the highest frequencies of open fractures (9.6% low grade, 7.1% high grade), and disproportionately from motorcycle road traffic injuries (29.9%). CONCLUSION: Across all regions, the most significant source of fracture burden was in the elderly, and included common fragility fractures, such as hip fractures. Notable regional deviations in fracture distributions were observed within Africa, and Other Asia. Across all studied LMICs, ambulance usage was low, and health insurance coverage was particularly low in Africa and India.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".