Effectiveness of a Cucumber Extract Supplement on Articular Pain in Patients with Knee Osteoarthritis: A Randomized Double-Blind Controlled Clinical Trial
Bibliographic record
Abstract
This 8-week randomized double-blind placebo-controlled study aimed to assess the effectiveness of supplementation with an extract of Cucumis sativus L. (20 mg/day) on pain and other variables in patients with knee osteoarthritis (OA) over 40 years. The change in pain intensity using a 1–10 cm visual analog scale (VAS) was the primary endpoint. Fifty-five patients (mean age 50.6 ± 8.6 years) were included (experimental group, n = 29; placebo, n = 26). VAS scores for pain decreased significantly in both study groups, but decreases were higher in the experimental group (between-group p = 0.013). Improvements in pain, stiffness, and physical function according to the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were also significantly higher in the experimental group. The Timed Up and Go test result also decreased significantly in the experimental group. An improvement in muscle function was associated with significant increases in isokinetic and isometric dynamometry variables, particularly for isometric 60°·s−1 and 180°·s−1 knee flexion exercises in the experimental group. Plasma levels of interleukin-1-beta (IL-1β) and matrix metalloproteinase-3 (MMP-3) also decreased significantly in the experimental group. Based on the beneficial effects of cucumber on symptomatology and inflammatory and cartilage degradation biomarkers in knee OA, cucumber extract supplementation may a useful natural approach to maintain healthy joints.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".