Short-Term Effect of Topical Cetylated Fatty Acid on Early and Advanced Knee Osteoarthritis: A Multi-Center Study
Bibliographic record
Abstract
OBJECTIVES: This study aims to investigate if short-term topical treatment with cetylated fatty acid (CFA) cream reduces the detrimental effects of early and advanced knee osteoarthritis (OA). PATIENTS AND METHODS: The study included 113 patients (32 males, 81 females; median age 70.0 years; 95% CI: 69.0 to 71.4 years) with knee OA diagnosed according to American College of Rheumatology classification criteria. Each patient underwent knee X-rays, followed by a CFA topical treatment (two applications per day for one week). Before and after the treatment, patients completed a Western Ontario and McMaster Universities Osteoarthritis Index questionnaire. All knee X-rays were classified according to Kellgren-Lawrence scale. RESULTS: After one week of treatment, decreased Western Ontario and McMaster Universities Osteoarthritis Index overall scores and sub-scale scores were observed in the whole cohort (p<0.005) and Kellgren-Lawrence scale grade 3 group (p<0.05). In the Kellgren-Lawrence scale grade 2 group, overall Western Ontario and McMaster Universities Osteoarthritis Index scores and pain and functional ability sub-scale scores improved (p<0.05). CONCLUSION: Administration of topical CFA may mitigate most common symptoms in knee OA. Our findings suggest that topical CFA is effective in all knee OA patients with slightly higher evidence for those with advanced disease.
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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) | 0.001 | 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".