Nabilone as an Adjunctive to Gabapentin for Multiple Sclerosis-Induced Neuropathic Pain: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Neuropathic pain (NPP) is a chronic syndrome suffered by patients with multiple sclerosis (MS), for which there is no cure. Underlying cellular mechanisms involved in its pathogenesis are multifaceted, presenting significant challenges in its management. METHODS: A randomized, double-blind, placebo-controlled study involving 15 relapsing-remitting MS patients with MS-induced NPP was conducted to evaluate nabilone combined with gabapentin (GBP). Eligible patients stabilized on GBP (≥1,800 mg/day) with inadequate pain relief were recruited. Nabilone or placebo was titrated over 4 weeks (0.5 mg/week increase) followed by 5-week maintenance of 1 mg oral nabilone (placebo) twice daily. Primary outcomes included two daily patient-reported measures using a 100-mm visual analog scale (VAS), pain intensity (VASpain), and impact of pain on daily activities (VASimpact). Hierarchical regression modeling was conducted on each outcome to determine if within-person pain trajectory differed across study groups, during 63-day follow-up. RESULTS: After adjustment for key patient-level covariates (e.g., age, sex, Expanded Disability Status Scale, duration of MS, baseline pain), a significant group × time(2) interaction term was reported for both the VASpain (P < 0.01) and VASimpact score (P < 0.01), demonstrating the adjusted rate of decrease for both outcomes was statistically greater in nabilone vs placebo study group. No significant difference in attrition rates was noted between treatments. Nabilone was well tolerated, with dizziness/drowsiness most frequently reported. CONCLUSION: Nabilone as an adjunctive to GBP is an effective, well-tolerated combination for MS-induced NPP. The results of this study identify a novel therapeutic combination for use in this population of patients predisposed to tolerability issues that may otherwise prevent effective pain management.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".