Prehospital transport of patients with spinal cord injury in Nigeria
Bibliographic record
Abstract
BACKGROUND: A well-organized and efficient prehospital transport is associated with improved outcome in trauma patients. In Nigeria, there is paucity of information on prehospital transport of patients with spinal cord injury (SCI) and its relation to mortality. OBJECTIVE: To determine if prehospital transportation is a predictor of mortality in patients with SCI in Nigeria. DESIGN: Prospective cohort study METHODS: Prehospital transport related conditions, injury arrival intervals and persons that brought patients with SCI to the casualty were noted. Data analyzed using descriptive statistics, the chi-square test and multiple logistic regressions. MAIN OUTCOME MEASURES: Mortality within 6 weeks on admission RESULTS: 168 patients with SCI presented in the casualty during this review period. Majority (67.9%) presented after 24 hrs of the injury. Majority (58.3%) were conveyed into the casualty by their relatives. Salon car (54.2%) was the most common mode of transportation where majority (55.4%) laid on their back during the transfer. Majority (75%) of the patients had multiple hospital presentation before reporting in our casualty. The mortality observed was 16.7%. Multivariate analysis after adjusting for age, gender, and means of transportation revealed that age (OR= 63.41, 95% CI= 9.24-43.53), crouched position during transfer (OR= 23.52, 95% CI= 7.26-74.53), presentation after 24 hrs (OR=5.48, 95% CI=3.20-16.42) and multiple hospital presentation (OR= 7.94, 95% CI= 1.89-33.43) were associated with mortality within 6 weeks of admission. CONCLUSION: A well-organized and efficient prehospital transport would reduce mortality in spinal cord injured patients. Public enlightenment campaign on factors that could reduce road traffic injury would help reduce mortality.
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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) | 0.001 | 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".