P.076 Epidemiology of traumatic spinal cord injury patients in New Brunswick
Bibliographic record
Abstract
Background: Characteristics of traumatic spinal cord injury (tSCI) patients admitted to the Saint John Regional Hospital and the Stan Cassidy Center for Rehabilitation from 2011 to 2014 were examined. Methods: Demographic, neurological and functional outcome data for 18 patients, who had consented to participate in a database for tSCI in Canada, was obtained. Results: The majority of patients were male (88.9%), with a mean age of 41. 33 (SD=17.17). The most common causes of tSCI were motor vehicle accidents (41.2%) and falls (29.4%). Cervical spine injuries (70.6%) and an ASIA impairment scale classification of D (38.9%) predominated. The median latency from injury to surgery was 22.67 hours. Functional independence Measure scores (M=64.17, SD=25.84) indicated that motor/functional independence was impaired (M=32.44, SD=19.15) relative to cognitive independence (M=31.83, SD=4.07). Conclusions: The results suggest that characteristics of tSCI patients in New Brunswick are similar to the Canadian tSCI patient population. Emergency care appears to be delivered in a timely fashion. Both centers participate in research registries focused on collecting data related to tSCI, surgical interventions, and patient outcomes. Registries are valuable research tools that allow for an alternative way to examine the quality of care their patients receive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".