Pregabalin as long-term treatment of fibromyalgia pain
Bibliographic record
Abstract
Introduction:This study (A0081057) was designed to evaluate the long-term safety and efficacy of pregabalin treatment of fibromyalgia (FM).Methods:In this 1-year, open-label (OL) extension of a 13-week randomized, placebo-controlled trial of pregabalin FM patients had the option of continuing pregabalin at doses of 150 to 600 mg/d. Efficacy was measured by the Short-Form McGill Pain Questionnaire (SF-MPQ), which included sensory and affective pain descriptors, Present Pain Intensity (PPI) index, and a Visual Analog Scale (VAS).Results:429 of 431 screened patients entered OL treatment, 249 (58%) completed, 70 (16.3%) discontinued due to an adverse event (AE), and 110 (25.7%) discontinued for other reasons. Median duration of treatment with pregabalin was 357 days (range, 1-402 days); 114 received pregabalin for ≥1 year. No clinically meaningful increases in dose were noted over the OL treatment period. Weighted mean dose was 414 mg/d in the first 3 months of treatment and 444 mg/d after 9 months of treatment. SF-MPQ sensory, affective, and total scores were improved relative to baseline, VAS pain score decreased 21 points (0-100 scale), and PPI decreased 0.9 point (0-5 scale). The most frequently reported all-causality AEs were dizziness, somnolence, peripheral edema, and increased weight, most of which were mild to moderate in intensity and of limited duration.Conclusions:Pregabalin administered for up to 1 year was generally well tolerated by FM patients without evidence of dose increase over time. The sustained improvement in pain measures during OL treatment was consistent with that in shorter term double-blind trials.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".