Pregabalin in the treatment of post‐traumatic peripheral neuropathic pain: a randomized double‐blind trial
Bibliographic record
Abstract
BACKGROUND: Pregabalin is effective in the treatment of peripheral and central neuropathic pain. This study evaluated pregabalin in the treatment of post-traumatic peripheral neuropathic pain (including post-surgical). METHODS: Patients with a pain score >or=4 (0-10 scale) were randomized and treated with either flexible-dose pregabalin 150-600 mg/day (n = 127) or placebo (n = 127) in an 8-week double-blind treatment period preceded by a 2-week placebo run-in. RESULTS: Pregabalin was associated with a significantly greater improvement in the mean end-point pain score vs. placebo; mean treatment difference was -0.62 (95% CI -1.09 to -0.15) (P = 0.01). The average pregabalin dose at end-point was approximately 326 mg/day. Pregabalin was also associated with significant improvements from baseline in pain-related sleep interference, and the Medical Outcomes Study sleep scale sleep problems index and sleep disturbance subscale (all P < 0.001). In the all-patient group (ITT), pregabalin was associated with a statistically significant improvement in the Hospital Anxiety and Depression Scale anxiety subscale (P < 0.05). In total, 29% of patients had moderate/severe baseline anxiety; treatment with pregabalin in this subset did not significantly improve anxiety. More patients reported global improvement at end-point with pregabalin than with placebo (68% vs. 43%; overall P < 0.01). Adverse events led to discontinuation of 20% of patients from pregabalin and 7% from placebo. Mild or moderate dizziness and somnolence were the most common adverse events in the pregabalin group. CONCLUSION: Flexible-dose pregabalin 150-600 mg/day was effective in relieving neuropathic pain, improving disturbed sleep, improving overall patient status, and was generally well tolerated in patients with post-traumatic peripheral neuropathic pain.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.009 | 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".