The effect of a multi-herbal product, C. autumnale, W. somnifera, and P. lentiscus, on knee osteoarthritis: a triple-blind randomized clinical trial
Bibliographic record
Abstract
Background and purpose: Osteoarthritis (OA) is a common joint disease that affects millions of people worldwide and is characterized by cartilage degeneration, stiffness, and limited mobility. This clinical trial aimed to investigate the efficacy and safety of a herbal combination of Colchicum autumnale root, Withania somnifera root, and Pistacia lentiscus gum in the relief of knee OA symptoms. Experimental approach: Seventy patients diagnosed with knee OA were randomized to receive the herbal product or a placebo for 6 weeks. Pain and functional outcomes were measured using the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index and Visual Analogue Scale (VAS). The heel-to-thigh distance parameter was also assessed by measuring the distance between the thigh and heel at maximum knee flexion in the prone position. Findings/Results: Significant improvements were observed in WOMAC scores for pain, stiffness, and physical function in the herbal product group compared to placebo at 3 and 6 weeks. VAS scores confirmed these results and showed lower pain intensity in the herbal product group. Heel-to-thigh distance decreased significantly within all groups during the study. Conclusion and implications: This study provided evidence for the efficacy of the herbal combination in the management of knee OA symptoms and was well tolerated by all patients with no severe adverse effects. The observed benefits emphasized the potential of herbal medicines as a complementary approach in the management of knee OA. Further research is needed to fully elucidate the therapeutic mechanisms and optimize the clinical application of this herbal combination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".