CLINICAL EFFICACY OF VASANTKUSUMAKAR RASA IN DIABETIC PERIPHERAL NEUROPATHY: A RANDOMIZED SINGLE BLIND CLINICAL TRIAL
Bibliographic record
Abstract
Background: Diabetic peripheral neuropathy is the most important and under-treated microvascular complication of Diabetes Mellitus. The symptoms- tingling, numbness, pricking pain, allodynia- generally commence in the legs and show a stocking glove pattern. Few FDA- approved drugs like pregabalin, gabapentin, duloxetine are used as a part of management of diabetic peripheral neuropathy in the contemporary medicine. They are effective for symptomatic relief but are associated with significant adverse effects. Post-covid era has evolved as the most promising one for exploration of alternative medicine. Rasaushadhis (herbo-mineral/ metallic compounds) are potent drugs that are thought to work at cellular level. Vasantkusumakar Rasa is a promising drug for diabetic complications as earlier studies have proven its protective effects on nerves via anti-oxidant, micronutrient and immune-modulatory effects. This study was intended to assess its efficacy and safety in diabetic peripheral neuropathy.Methodology: A double-arm single blind randomized clinical trial was conducted on 30 subjects having diabetic peripheral neuropathy, randomized into two groups- 15 in each. Control group was treated with placebo drug (125mg twice daily with water) and trial group was treated with Vasantkusumakar Rasa (125mg twice daily with cow’s ghee). A 30-day follow up (30th, 60th and 90th day) was planned for this study. Conventional anti-diabetic medications were continued in both the groups. Reduction in signs and symptoms using Toronto Clinical Scoring System score and indifference between the serum creatinine and liver function tests were primary outcomes; reduction in Vibration perception threshold using biothesiometer, Visual Analogue Scale and HbA1c were secondary outcomes. Paired t-test and 2 sample t-test were used for statistical analysis.Results: Vasantkusumakar Rasa posed a significant effect on diabetic peripheral neuropathy as p value is <0.05 for TCSS and VPT scores in trial group as compared to control group. Clinical safety of Vasantkusumakar Rasa was also evident as no adverse effects were observed on RFT and LFT parameters in trial group. (p value> 0.05)Conclusion: Vasantkusumakar Rasa is a promising Rasaushadhi that may prove to be beneficial in reducing symptoms of DPN as an add-on drug along with the conventional modern medications.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".