P.220 Mechanism of injury is associated with neurological outcomes in cervical sensorimotor complete traumatic spinal cord injury
Bibliographic record
Abstract
Background: There is significant heterogeneity in neurological recovery after complete (ASIA A) traumatic spinal cord injury (tSCI). Neurological recovery is often associated with a conversion to a higher letter grade of the American Spinal Injury Association’s impairment scale (ASIA). The mechanism of injury (MOI) may play a significant role in the primary injury and should be considered for greater precision in care. Methods: We isolated ASIA A cervical tSCI patients from three multicenter prospective randomized controlled trials (NACTN, STASCIS, Sygen). Chi-square test with pairwise comparisons with Bonferroni corrections was performed to compare the proportion of ASIA A patients that converted to a higher ASIA grade between different MOI. Results: We identified 486 complete cervical tSCI patients. For patients who developed tSCI as a result of a fall, a significant proportion converted to a higher ASIA grade by 52 weeks (p = 0.009). For patients who developed tSCI as a result of a sports injury, a significantly smaller proportion did not convert to a higher ASIA grade compared to those that converted (p = 0.034). Conclusions: Due to the difference in outcomes, tSCI patients should be treated differently depending on their mechanism of injury.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".