Effect of Transdermal Microneedle Patch Plus Nonsteroidal Anti-Inflammatory Drug in Knee Osteoarthritis: A Randomized, Double-Blind Study
Bibliographic record
Abstract
Purpose: No recent clinical study has shown the efficacy of transdermal microneedle patch (TDM) plus nonsteroidal antiinflammatory drug (NSAID) in early knee osteoarthritis (OA). This study aimed to determine the effect of TDM plus NSAID on synovial hypertrophy, knee pain, and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) score in osteoarthritic knees. Methods: A randomized, controlled, double-blind trial was conducted. One hundred participants, aged 40–70 years, with painful knee OA and radiographic nonstructural changes were randomly assigned into two groups to undergo TDM plus NSAID (ketorolac 30 mg) or TDM (placebo) at the medial joint line of the knee twice (once weekly). The synovial thickness was measured using ultrasonography at pretreatment, weeks 1, 2, and 4. The visual analog scale (VAS) for pain, WOMAC score, and adverse events (AEs) were also recorded. Results: The TDM plus NSAID group demonstrated a significant reduction in synovial thickness and VAS at weeks 2 and 4 compared with the placebo group (P<0.05). At week 4, the mean synovial thickness reduction was 1.1 and 0.3 mm, and the mean VAS reduction was 3.2 and 1.7 for the TDM plus NSAID and placebo groups, respectively. The mean WOMAC scores at week 4 were significantly reduced (5.7 and 0.9 for the TDM plus NSAID and placebo groups, respectively). No complication and treatment-related AEs occurred. Conclusions: TDM plus NSAID significantly reduced synovitis and improved the pain score in knee OA after 2 weeks. The WOMAC score improved at week 4 without any AEs. Thai Clinical Trials Registry (TCTR), TCTR identification number is TCTR20200613001.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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".