Minimizing Errors in Acute Traumatic Spinal Cord Injury Trials by Acknowledging the Heterogeneity of Spinal Cord Anatomy and Injury Severity: An Observational Canadian Cohort Analysis
Bibliographic record
Abstract
Clinical trials of therapies for acute traumatic spinal cord injury (tSCI) have failed to convincingly demonstrate efficacy in improving neurologic function. Failing to acknowledge the heterogeneity of these injuries and under-appreciating the impact of the most important baseline prognostic variables likely contributes to this translational failure. Our hypothesis was that neurological level and severity of initial injury (measured by the American Spinal Injury Association Impairment Scale [AIS]) act jointly and are the major determinants of motor recovery. Our objective was to quantify the influence of these variables when considered together on early motor score recovery following acute tSCI. Eight hundred thirty-six participants from the Rick Hansen Spinal Cord Injury Registry were analyzed for motor score improvement from baseline to follow-up. In AIS A, B, and C patients, cervical and thoracic injuries displayed significantly different motor score recovery. AIS A patients with thoracic (T2-T10) and thoracolumbar (T11-L2) injuries had significantly different motor improvement. High (C1-C4) and low (C5-T1) cervical injuries demonstrated differences in upper extremity motor recovery in AIS B, C, and D. A hypothetical clinical trial example demonstrated the benefits of stratifying on neurological level and severity of injury. Clinically meaningful motor score recovery is predictably related to the neurological level of injury and the severity of the baseline neurological impairment. Stratifying clinical trial cohorts using a joint distribution of these two variables will enhance a study's chance of identifying a true treatment effect and minimize the risk of misattributed treatment effects. Clinical studies should stratify participants based on these factors and record the number of participants and their mean baseline motor scores for each category of this joint distribution as part of the reporting of participant characteristics. Improved clinical trial design is a high priority as new therapies and interventions for tSCI emerge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".