Efficacy of Virechana in Treating Raised Uric Acid Level in Gouty Arthritis - A Cohort Study
Bibliographic record
Abstract
Vatarakta is a disorder predominantly affecting the joints with presenting symptoms like Sandhishula (pain), Sandhi shotha (swelling), Sandhi Graha (stiffness) Sparsh-asahishnuta (tenderness). Vatarakta in modern view has similarity with Gouty Arthritis. Gout and gouty arthritis though much prevalent in the western countries, it is not uncommon in India. The occurrence of Gout and gouty arthritis is common in the post pubertal males, and post-menopausal females. Hyperuricemia is a predisposing factor for the manifestation of gouty arthritis. The prevalence of gout varies between populations but is around 1% with a strong male predominance (10:1). As treatment given in modern is quite toxic this study on Vatarakta was taken up to find out the possible effects of Ayurvedic therapies in its management. Virechana is one of the Shodhana chikitsa in the management of Vatarakta. The objectives of the study were to study the efficacy of Virechana in reducing the raised uric acid level. Materials and Methods: 20 patients were included in this clinical study. Subjects were given Panchatikta guggulu ghrita for Snehapana, followed by Sarvanga abhyanga with Balaguduchyadi taila and Virechana with Nimbamrita Eranda taila. The total duration of the study was 7 days and follow up was done after 1 week. The assessment was carried based on subjective parameters like Sandhishoola, Sandhigraha and objective parameters like Twak Vaivarnyata, Sparshasahatwa, serum uric acid level, and McGill’s pain scale was done before and after treatment. Results were statistically analyzed using Wilcoxon signed-rank test. Results: Significant results were observed in subjective parameters such as Sandhishoola (85.6%) and Sandhigraha (75%) as well as objective parameter like twak Vaivarnyata (86.4%), Sparshasahatwa (90%), 32.8% serum uric acid level (32.8%), Mac gills pain scale (50%). Conclusion: Virechana with Nimbamritadi eranda taila was effective in the management of Gouty arthritis.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".