Prehospital care for traumatic spinal cord injury by first responders in 8 sub-Saharan African countries and 6 other low- and middle-income countries: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Traumatic spinal cord injury (TSCI) constitutes a considerable portion of the global injury burden, disproportionately affecting low- and middle-income countries (LMICs). Prehospital care can address TSCI morbidity and mortality, but emergency medical services are lacking in LMICs. The current standard of prehospital care for TSCI in sub-Saharan Africa and other LMICs is unknown. METHODS: This review sought to describe the state of training and resources for prehospital TSCI management in sub-Saharan Africa and other LMICs. Articles published between 1 January 1995 and 1 March 2020 were identified using PMC, MEDLINE, and Scopus databases following PRISMA-ScR guidelines. Inclusion criteria spanned first responder training programs delivering prehospital care for TSCI. Two reviewers assessed full texts meeting inclusion criteria for quality using the Newcastle-Ottawa Scale and extracted relevant characteristics to assess trends in the state of prehospital TSCI care in sub-Saharan Africa and other LMICs. RESULTS: Of an initial 482 articles identified, 23 met inclusion criteria, of which ten were set in Africa, representing eight countries. C-spine immobilization precautions for suspected TSCI patients is the most prevalent prehospital TSCI intervention for and is in every LMIC first responder program reviewed, except one. Numerous first responder programs providing TSCI care operate without C-collar access (n = 13) and few teach full spinal immobilization (n = 5). Rapid transport is most frequently reported as the key mortality-reducing factor (n = 11). Despite more studies conducted in the Southeast Asia/Middle East (n = 13), prehospital TSCI studies in Africa are more geographically diverse, but responder courses are shorter, produce fewer professional responders, and have limited C-collar availability. DISCUSSION: Deficits in training and resources to manage TSCI highlights the need for large prospective trials evaluating alternative C-spine immobilization methods for TCSI that are more readily available across diverse LMIC environments and the importance of understanding resource variability to sustainably improve prehospital TSCI care.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".