The effect of Sativex in neuropathic pain and spasticity in spinal cord injury
Bibliographic record
Abstract
Introduction: Neuropathic pain and spasticity after spinal cord injury represent significant but still unresolved problems, which cause considerable suffering and reduced quality of life for patients with spinal cord injury. Treatment of neuropathic pain and spasticity is complicated and patients often receive incomplete relief from present available and recommended treatment. Cannabinoids has shown efficacy on both neuropathic pain and spasticity in patients with spinal cord injury, but the studies one the topic has been too small to make a general conclusion for patients with spinal cord injury. Aims: To investigate the effect of Sativex (cannabinoid agonist given as an oral mucosal spray), on neuropathic pain and spasticity in patients with spinal cord injury. Methods: A randomized, double-blind, placebo-controlled crossover study. We will include 30 patients with neuropathic pain and 30 patients with spasticity. Because many patients have dual symptoms, we expect to include 50 patients. A numeric rating scale for pain intensity and spasticity (0-10 point) will be used to measure primary outcome. Present status: Due to recent changes by the Danish Health and Medicines Authority, it is presently illegal to drive when using Sativex, which impedes the inclusion of patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".