Cupping Therapy for Pain Management and Improving the Quality of Life in Knee Osteoarthritis: A Case Report.
Bibliographic record
Abstract
Background: As one of the most prevalent musculoskeletal diseases, osteoarthritis, causes pain, deterioration in functioning, and reduction in quality of life. The condition that is thought to contribute most to disability worldwide is knee osteoarthritis. Existing pharmacological treatments for osteoarthritis raise safety concerns. In Unani medicine, several non-pharmacological regimens known as Ilāj bi'l Tadbīr (Regimenal therapies) are advised in the management of painful musculoskeletal disorders. Among all these practices, dry cupping (Hijāmah bilā Shart) is unique and recommended as one of the most effective methods for knee osteoarthritis pain management in the majority of classical Unani literature. This report presents a case of knee osteoarthritis treated using cupping therapy. Case presentation: A 57-year-old female patient presented with a 3-year-long history of right knee pain, stiffness, and difficulty in daily activities. The patient was examined clinically before intervention and was diagnosed with right knee osteoarthritis which was further supported by radiological investigations. Cupping therapy was administered over the affected knee joint for 4 weeks. A total of 10 sittings were carried out every 2 days. The patient's symptoms gradually ameliorated, ultimately becoming minimal following the 4-week treatment period. Specifically, the Numerical Pain Rating Scale (NPRS) score decreased from 8 to 2, the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score for stiffness and functional ability improved with a decrease from 50 to 25, and the quality of life score measured by 36-Item Short Form Health Survey (SF-36) improved from 35 to 75. Conclusion: Our case study established cupping therapy's effectiveness as a secure, non-invasive treatment option and opened new possibilities for its application in the management of knee osteoarthritis. However, further research is imperative to establish the efficacy and effectiveness of cupping therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".