P.107 Traumatic spinal cord injuries among aboriginal and non-aboriginal populations of Saskatchewan: a prospective outcomes study
Bibliographic record
Abstract
Background: People of aboriginal ancestry are more likely to suffer traumatic spinal cord injury (TSCI) compared to other Canadians; however, outcome studies are limited. This study aims to compare aboriginal and non-aboriginal populations with acute TSCI with respect to: pre-injury baseline, injury severity, treatment, outcomes, and length-of-stay characteristics. Methods: This was a retrospective analysis of 159 patients with TSCI prospectively enrolled in the prospective Rick Hansen Spinal Cord Injury Registry (RHSCIR), Saskatoon site between February 13, 2010 and December 17, 2016. Results: Sixty-two patients consented to the full dataset, which includes ethnic background: 21 ‘aboriginal’ (33.9%); 41 ‘non-aboriginal’ (66.1%). Aboriginal patients were younger, had fewer medical comorbidities and had similar severity of neurological injury and similar outcomes compared to non-aboriginal patients. However, the time to discharge to the community was significantly longer (median 104.0 days versus 38.5 days, p=0.021). While 35% of non-aboriginal patients were discharged home from the acute care site, no aboriginal patients were transferred home directly. Conclusions: This study suggests a need for better allocation of resources for transition to the community for First Nations patients with TSCI in Saskatchewan. We plan a further study to assess outcomes from TSCI for First Nations patients across Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".