The Impact of Riluzole on Neurobehavioral Outcomes in Preclinical Models of Traumatic and Nontraumatic Spinal Cord Injury: Results From a Systematic Review of the Literature
Bibliographic record
Abstract
STUDY DESIGN: Systematic review. OBJECTIVE: To evaluate the impact of riluzole on neurobehavioral outcomes in preclinical models of nontraumatic and traumatic spinal cord injury (SCI). METHODS: An extensive search of the literature was conducted in Medline, EMBASE, and Medline in Process. Studies were included if they evaluated the impact of riluzole on neurobehavioral outcomes in preclinical models of nontraumatic and traumatic SCI. Extensive data were extracted from relevant studies, including sample characteristics, injury model, outcomes assessed, timing of evaluation, and main results. The SYRCLE checklist was used to assess various sources of bias. RESULTS: The search yielded a total of 3180 unique citations. A total of 16 studies were deemed relevant and were summarized in this review. Sample sizes ranged from 14 to 90, and injury models included traumatic SCI (n = 9), degenerative cervical myelopathy (n = 2), and spinal cord-ischemia (n = 5). The most commonly assessed outcome measures were BBB (Basso, Beattie, Besnahan) locomotor score and von Frey filament testing. In general, rats treated with riluzole exhibited significantly higher BBB locomotor scores than controls. Furthermore, riluzole significantly increased withdrawal thresholds to innocuous stimuli and tail flick latency following application of radiant heat stimuli. Finally, rats treated with riluzole achieved superior results on many components of gait assessment. CONCLUSION: In preclinical models of traumatic and nontraumatic SCI, riluzole significantly improves locomotor scores, gait function, and neuropathic pain. This review provides the background information necessary to interpret the results of clinical trials on the impact of riluzole in traumatic and nontraumatic SCI.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".