Potential of diacerein in combination with aerobic exercise in comprehensive treatment of knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis is a common degenerative disease characterized by cartilage destruction and inflammatory changes in the synovial membrane. Obesity and metabolic syndrome are significant risk factors that exacerbate inflammatory processes and contribute to the progression of osteoarthritis. Modern treatment methods include both pharmacological agents and non-pharmacological approaches such as aerobic exercise. AIM: To evaluate and compare the effectiveness of diacerein combined with aerobic physical activity (Nordic walking) in the comprehensive treatment of knee osteoarthritis. MATERIALS AND METHODS: The study involved 65 patients aged 45 to 70 years with knee osteoarthritis and metabolic syndrome. The participants were divided into three groups. The first group received diacerein (Artrocare); the second group was engaged in Nordic walking; the third group – a combination of these methods. The visual analog scale of pain, Western Ontario and McMaster University Osteoarthritis (WOMAC) index, quality of life (Short Form-36), glycated hemoglobin levels, and other biochemical parameters were assessed over 16 weeks of observation. RESULTS: The study demonstrated statistically significant reductions in pain levels and improvements in functional parameters in all the groups. The greatest improvements were observed in the group receiving combined therapy. The method showed a significantly positive impact on quality of life and reduced the need for analgesics in comorbid patients. Additionally, the patients with metabolic syndrome showed improved biochemical parameters with the combination of diacerein and Nordic walking. CONCLUSIONS: The combined use of diacerein and Nordic walking is an effective and safe method for treating knee osteoarthritis, particularly in patients with metabolic syndrome. This approach significantly reduces pain, improves joint function, and enhances overall quality patient’s life.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".