Buprenorphine transdermal system and quality of life in opioid-experienced patients with chronic low back pain
Bibliographic record
Abstract
OBJECTIVES: To evaluate the impact of 12 weeks of treatment with Butrans® (buprenorphine) transdermal system (BTDS) on the health-related quality of life (HRQoL) for patients with chronic low back pain (CLBP), and the maintenance of effects over 52 weeks. RESEARCH DESIGN AND METHODS: A multicenter, enriched, double-blind (DB), randomized trial comparing BTDS 20 μg/h (BTDS 20) against 5 μg/h (BTDS 5) for treatment of opioid-experienced patients with moderate-to-severe CLBP, including a 52-week open-label (OL) extension phase. MAIN OUTCOME MEASURES: QoL was measured with the SF-36v2 survey before and after an OL run-in period with BTDS 20, three times during the DB phase, and seven times over the extension phase. This post hoc analysis tested for SF-36v2 score differences between treatment groups during the DB phase and maintenance of effects over the extension phase. RESULTS: At 12 weeks, BTDS 20 produced larger improvements than BTDS 5 in role limitations due to physical health, bodily pain and overall physical QoL (p < 0.01). Treatment group differences in overall physical QoL were sustained throughout the DB phase. Quality-of-life improvements associated with BTDS 20 persisted through the extension phase. CONCLUSIONS: These data suggest that opioid-experienced moderate-to-severe CLBP patients receiving BTDS 20 exhibited better QoL than patients receiving BTDS 5.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".