Geomapping of Traumatic Spinal Cord Injury in Canada and Factors Related to Triage Pattern
Bibliographic record
Abstract
Current research indicates that more than half of patients with traumatic spinal cord injury (tSCI) experience delays in transfer and receive surgery >24 h post-injury. The objectives of this study were to determine the geographic distribution of tSCI in Canada relative to specialized treatment facilities, to assess clinical and logistical factors at play for indirect admissions to those facilities, and to explore differences in current time to admission and simulated scenarios in an attempt to assess the potential impact of changes to triage protocols. This study included data from 876 patients with tSCI enrolled in the prospectively collected acute Rick Hansen Spinal Cord Injury Registry (RHSCIR) between January 1, 2010 and December 31, 2013 for whom there were data on the location of their injury. Patients transported directly to a RHSCIR acute facility were more likely to reach the facility within 1 h of injury, whereas those transported indirectly were more likely to arrive 7 h later. Considering the injuries occurring within 40 km of a RHSCIR acute facility (n = 323), 249 patients (77%) were directly and 74 (23%) were indirectly admitted. In the multivariate regression analysis, only older age and longer road distance remained significantly associated with being indirectly admitted to a RHSCIR facility. Compared with the current status, the median time to admission decreased by 20% (3.5 h) in the 100% direct admission scenario, and increased by 102% (8.9 h) in the 100% indirect admission scenario.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".