Anti-inflammatory activity of willow bark extract (Salix alba) and its effect on inflammation markers in the human body
Bibliographic record
Abstract
The study aimed to evaluate the anti-inflammatory efficacy and safety of Salix alba bark extract compared to ibuprofen in patients with knee osteoarthritis. A 12-week randomised controlled trial in Ukraine involved 120 patients diagnosed with stage II-III osteoarthritis, divided into two groups: the first received a standardised willow extract (240 mg of salicin per day), the second received ibuprofen (1,200 mg/day). Pain scores on a visual analogue scale decreased from 7.4 ± 1.2 to 3.1 ± 1.5 points (Δ= 4.3; p < 0.001) in the Salix alba group and from 7.6 ± 1.1 to 3.0 ± 1. 4 points (Δ= 4.6; p = 0.12) in the ibuprofen group. Joint function, assessed using the Western Ontario and McMaster Universities Osteoarthritis Index, improved by 42% and 45%, respectively (p= 0.24). C-reactive protein levels decreased by 55% versus 60% (p= 0.18), interleukin-6 by 58% versus 60% (p = 0.29), and tumour necrosis factor-α by 50% versus 52% (p = 0.41). Side effects were reported in 10% of patients in the willow group versus 25% in the control group, mainly gastrointestinal in nature. A moderate correlation was found between blood salicin levels and pain reduction (r = 0.45; p < 0.001). The results proved that Salix alba extract has similar efficacy to ibuprofen, but with a lower risk of complications due to its multifunctional action (inhibition of cyclooxygenases, cytokine modulation, antioxidant effect). The data obtained justify the use of the extract as an alternative to synthetic anti-inflammatory drugs in clinical practice, especially for patients with chronic inflammatory diseases, where long-term use of non-steroidal anti-inflammatory drugs is accompanied by an increased risk of side effects. The results of the study can be used by rheumatologists and therapists in clinical practice to prescribe Salix alba extract as a safe alternative to non-steroidal anti-inflammatory drugs for patients with osteoarthritis
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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 | 0.005 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".