Topical lidocaine patch 5% may target a novel underlying pain mechanism in osteoarthritis
Bibliographic record
Abstract
Recent literature and animal research has provided insight to potentially new analgesic targets for managing osteoarthritis (OA) pain. Primary afferent neurons located in affected joints express excessive amounts of abnormally functioning sodium (Na) channels on their surface in response to the inflammatory process. These Na channels may play an integral role in production of pain and hyperalgesia. Hence, the authors set out to conduct a 2-week, open-label, multicenter proof-of-concept study to evaluate the effectiveness and safety of lidocaine patch 5% monotherapy in adults with OA pain of the knee (n = 20). Patients with OA of one or both knees who were experiencing inadequate pain relief (defined as an average daily pain intensity of > 4 on a 0 to 10 pain scale) with their current analgesic regimen (i.e. APAP, NSAIDs, COX-2 inhibitors, tramadol) were enrolled and had all analgesic medications discontinued. Treatment with the lidocaine patch 5% resulted in significant improvements in the Western Ontario and McMaster Universities OA Index (WOMAC) pain, stiffness, physical function subscales and composite index (48.4, 41.1, 47.0, and 46.8% improvements respectively, p < 0.01). In addition, significant improvement was noted for pain intensity, pain relief, and pain interference with quality of life as measured by the Brief Pain Inventory (p < 0.05). The lidocaine patch 5% was generally well tolerated and no patients discontinued due to treatment-related adverse events. Given the open-label design, lack of a control group, and small sample size, the findings from our pilot study need to be confirmed by larger randomized controlled trials. Topical lidocaine patch 5% may provide clinicians with a novel, non-systemic therapy for OA pain with a unique mechanism of action.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".