Comparative Study of Pain Reduction and Quality of Life in Patients with Osteoarthritis of the Knee Treated with Nigella Sativa Seed Gelatin Capsule and Drug Treatment
Bibliographic record
Abstract
Introduction: knee osteoarthritis is one of the most important causes of pain and disability in society. The aim of this study was to investigate the level of pain and the quality of life in patients with knee osteoarthritis treated with Nigella Sativa capsules and drug therapy. Materials and Methods: This case-control study was conducted on patients who referred to the Baqiyatallah clinic with complaints of knee osteoarthritis in 2022. A total of 120 patients were randomly divided into two groups, namely, standard treatment (physiotherapy, exercise to strengthen muscles and nutritional recommendations), and the group receiving Nigella Sativa capsules (650 mg, orally and twice a day). Then 36-item Quality of Life Questionnaire, Functional Questionnaire, Western Ontario and Mcmaster Universities Index (WOMAC), and Visual Pain Scale (VAS) were completed for patients in both case and control groups. All the collected data were entered into SPSS software and analyzed using Chi Squared and Student's t-test. In all analyses, the significance limit of the results was p value=0.05. Results: No significant difference was found between the quality of life score of the patients in the case and control groups (p>0.05). However, a significant difference was observed in the visual pain intensity score between the case and control groups (p<0.05). In the sub-scales of the WOMAC questionnaire, there was also a significant difference between the pain score and joint stiffness in the case and control groups (p<0.05). However, there was no significant difference between the physical activity scores of the two groups (p>0.05). Conclusion: The result of our study showed that Nigella Sativa capsules reduces pain, improves dry joints, and reduces visual pain, however it did not have any significant effect on the quality of life.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".