Racial and Ethnical Discrepancies and Similarities in the Epidemiology, Survival, and Neurological Outcomes After Acute Traumatic Spinal Cord Injury: A Retrospective Cohort Study Using Data from the NASCIS-1 Trial
Bibliographic record
Abstract
Background Little is known about the impact of race/ethnicity on the clinical and neurological outcomes after acute traumatic spinal cord injury (tSCI). Objectives This study examined the influence of race/ethnicity on the individuals’ survival and neurological recovery within the first year after tSCI. Methods The 306 cases enrolled in the First National Acute Spinal Cord Injury Study (NASCIS-1) were grouped as African American individuals ( n = 84), non-Hispanic White individuals ( n = 159), and other races/ethnicities that included Hispanic individuals ( n = 60) and Asian individuals ( n = 3). Outcome measures included survival and neurological recovery within the first year after tSCI. Data analyses were adjusted for major potential confounders. Results There were 39 females and 267 males with mean age of 31 years who mostly sustained cervical severe tSCI after motor vehicle accidents or falls. The three groups were comparable regarding sex distribution, level and severity of tSCI, level of consciousness at admission, and total received dose of methylprednisolone. African American individuals were significantly older than non-Hispanic White individuals ( p = .0238). African American individuals and individuals of other races/ethnicities more often had a tSCI with open wound caused by missile and water-related accidents than non-Hispanic White individuals ( p < .0001). Survival rates within the first year after tSCI were comparable among the three groups ( p = .3191). Among the survivors, there were no significant differences among the three groups regarding motor and pinprick and light-touch sensory recovery ( p > .0500). Conclusions The results of this study suggest that, while there were few differences among the racial/ethnical groups regarding the epidemiology of tSCI, race/ethnicity did not influence survival rate or neurological recovery within the first year post-tSCI.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".