A Single-Blind Placebo Run-In Study of Venlafaxine XR for Activity-Limiting Osteoarthritis Pain
Bibliographic record
Abstract
OBJECTIVE: Osteoarthritis pain is a significant problem for our aging population. Non-steroidal anti-inflammatory drugs and opioids are effective treatments, but have significant adverse effects, so there is a need for alternative treatments. Selective norepinephrine-serotonin reuptake inhibitor antidepressants may provide a new treatment option for osteoarthritis pain. METHODS: We performed a single-blind placebo run-in trial of 150-225 mg of venlafaxine in 18 subjects with activity-limiting osteoarthritis pain. Each subject received 2 weeks of placebo followed by 10 weeks of venlafaxine. The primary outcome was reduction in average pain intensity between 2 and 12 weeks. For subjects not completing the trial, their last observation was carried forward as an imputed outcome. RESULTS: Average pain on the Brief Pain Inventory (BPI) was 4.7 at baseline, 4.4 after the 2-week placebo run-in, and 3.3 at 12 weeks (25% decrease, P = 0.03). Nine subjects (50%) reported at least 30% pain reduction between weeks 2 and 12. The Western Ontario and McMasters University Osteoarthritis Index (WOMAC) pain score at baseline was 2.0, 1.8 after 2 weeks, and 1.7 after 12 weeks. This represented a 6% decrease in pain between weeks 2 and 12 (P = 0.42), with two subjects (11%) reported at least 30% pain relief between weeks 2 and 12 on the WOMAC. Effects on self-reported physical and role function and depression were marginal or non-significant, and observed physical function did not improve. CONCLUSION: Venlafaxine significantly reduced pain intensity on the BPI and marginally improved self-reported function. Venlafaxine should be investigated further in a larger randomized trial for the treatment of osteoarthritis pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".