Pregabalin for the treatment of painful diabetic peripheral neuropathy: a double-blind, placebo-controlled trial
Bibliographic record
Abstract
A randomized, double-blind, placebo-controlled, parallel-group, multicenter, 8-week trial (with subsequent open-label phase) evaluated the effectiveness of pregabalin in alleviating pain associated with diabetic peripheral neuropathy (DPN). For enrollment, patients must have had at baseline: 1- to 5-year history of DPN pain; pain score > or =40 mm (Short-Form McGill Pain Questionnaire [SF-MPQ] visual analogue scale); average daily pain score of > or =4 (11-point numerical pain rating scale [0 = no pain, 10 = worst possible pain]). One hundred forty-six (146) patients were randomized to receive placebo (n = 70) or pregabalin 300 mg/day (n = 76). Primary efficacy measure was endpoint mean pain score from daily patient diaries (11-point numerical pain rating scale). Secondary measures included SF-MPQ scores; sleep interference scores; Patient and Clinical Global Impression of Change (PGIC and CGIC); Short Form-36 (SF-36) Health Survey scores; and Profile of Mood States (POMS) scores. Safety assessment included incidence and intensity of adverse events, physical and neurological examinations, and laboratory evaluations. Pregabalin produced significant improvements versus placebo for mean pain scores (P < 0.0001); mean sleep interference scores SF-36 Bodily Pain subscale (P < 0.0001); total SF-MPQ score (P < 0.01); SF-36 Bodily Pain subscale (P < 0.03); PGIC (P = 0.001); and Total Mood Disturbance and Tension-Anxiety components of POMS (P < 0.03). Pain relief and improved sleep began during week 1 and remained significant throughout the study (P < 0.01). Pregabalin was well tolerated despite a greater incidence of dizziness and somnolence than placebo. Most adverse events were mild to moderate and did not result in withdrawal. Pregabalin was safe and effective in decreasing pain associated with DPN, and also improved mood, sleep disturbance, and quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.007 | 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".