A Randomized Comparative Clinical Trial to Evaluate the Efficacy of Vangeshwara Rasa in Diabetic Polyneuropathy
Bibliographic record
Abstract
Export Introduction: Diabetic polyneuropathy (DPN) is a chronic complication that affects up to 50% of diabetics. There is a need for Rasayana, a specialized Ayurvedic drug with active potential that is helpful in the management of DPN. Despite these serious complications, the development of targeted therapies for DPN is lacking. Methods: A single-centric, randomized, comparative open clinical trial was conducted in patients with DPN. Thirty participants were randomized (n = 15 in the control group and n = 15 in the trial group). Koshtashodhana (~mild therapeutic purgation) with Nimbamrutadi Eranda Taila to all patients, followed by Vangeshawara Rasa with a dose of 125 mg twice a day with water in the trial group and Guduchyadi Kashaya with a dose of 40 mL twice a day with an equal quantity of water in the control group for a duration of 45 days. Patients were assessed on signs and symptoms, the toronto clinical scoring system (TCSS), 10 g monofilament, and laboratory investigations during each follow-up for 15 days. Results: Thirty participants were analyzed (n = 15 each). In trial groups, improvements in subjective parameters, sensory motor examinations, frequency of urination, fasting blood sugar, and postprandial blood sugar were obtained (P < 0.05). The effects of both groups were comparable. Conclusion: Vangeshwara Rasa, a Herbo-mineral drug possessing Rasayana potential, has been proven to be safe and effective in the management of DPN. The drug is free from any adverse effects, and 45 days of administration give significant relief from the signs and symptoms of DPN. The present study proves that the results of both the trial group, i.e., Vangeshwara Rasa (Group A), and the control group, i.e., Guduchyadi Kashaya (Group B), were comparable.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".