Unani Regimenal Approaches for Pain, Function and Quality of Life in Knee Osteoarthritis: A Rapid Scoping Review of Current Evidence
Bibliographic record
Abstract
Background: Knee osteoarthritis (KOA) is a prevalent degenerative joint disorder that leads to chronic pain and disability. Conventional therapies provide only limited long-term relief and are often associated with adverse effects and high cost. In Unani medicine, KOA is closely related to Wajaʹ al-Rukba, categorized under joint disorders, and managed through various regimenal therapies. Objective: This scoping review aimed to evaluate the effectiveness of Unani regimenal therapies in the management of KOA. Methods: A systematic search was conducted across PubMed, Google Scholar, and other relevant databases for studies published between January 2009 and March 2024. Keywords included “Knee osteoarthritis, Wajaʹ al-Rukba, Unani medicine, Greco-Arab medicine.” Eligible studies consisted of clinical trials, observational studies, and case studies assessing outcomes such as the Visual Analogue Scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Knee Injury and Osteoarthritis Outcome Score (KOOS). Results: A total of relevant Unani regimenal therapies were identified, including Hijama (cupping), Dalk (massage), Tadhīn (oiling), Takmīd (fomentation), Ḍimād (poultice), Irsaal-e-‘Alaq (leech therapy), and Qai (emesis). Across multiple studies, these therapies demonstrated statistically significant improvements in pain reduction and functional outcomes (p<0.001 in several trials). Notably, no major adverse effects were reported. Conclusion: Existing evidence suggests that Unani regimenal therapies are effective and safe in improving pain and function among KOA patients. However, most studies to date are small-scale, single-center, and methodologically heterogeneous. Larger, well-designed randomized controlled trials are needed to validate these findings and establish Unani therapies as cost-effective, complementary options in KOA management. Keywords: Wajaʹ al-Rukba, Unani medicine, Cupping, Massage, Fomentation, Traditional medicine
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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 | 0.017 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.025 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| 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".