Efficacy and Safety of <i>Ayurveda</i> Compound Formulations in <i>Sthoulya</i> (Obesity) Management: A Multi-centric Clinical Trial
Bibliographic record
Abstract
Background: Ayurveda offers a rich repository of medicinal formulations that have been traditionally used for various health conditions, including obesity. Scientific validation is essential to establish their efficacy and safety in contemporary healthcare. Aim: In this present study, it was aimed to evaluate the clinical efficacy and safety of Navaka Guggulu (NG) with Brihat Manjishtadi Kwatha (BMK) and Tryushnadi Guggulu (TG) with BMK for the treatment of Sthoulya (Obesity). Methods: A prospective, open-label, multi-centric clinical trial was conducted on 240 participants with 20% excess weight than desirable weight, age-adjusted BMI above the 85th percentile, and WHR >0.8 (females) and >0.95 (males). Participants were randomized into two groups: Group I received NG 1 gm twice daily and BMK 50 ml twice daily, while Group II received TG 1 gm twice daily and BMK 50 ml twice daily for 12 weeks. Outcomes were assessed through physical examination, BMI, WHR, EOSS (Edmonton Obesity Scoring System), and laboratory parameters. A paired t-test was used for statistical analysis. Results: Statistical analysis revealed a significant improvement in disease-specific parameters and chief complaints, including polyphagia, polydipsia, and excessive sweating. The mean values of BMI, waist circumference (WC), and WHR were found to be improved in both groups before and after the treatment, as well as during follow-up at the end of the 16th week. Statistical analysis of the EOSS score and laboratory parameters also revealed a significant upshot in both groups. All the interventions were useful in managing the clinical features and biomarkers; also, no clinically significant adverse event was observed. Conclusion: Ayurveda compound formulations NG, TG and BMK are remarkably useful and safe in managing obesity (Sthaulya) in the prescribed dose and comportment. Further, a double-masked, Randomized Controlled Trial (RCT) with an extended follow-up period is recommended to validate these findings. Major Findings: The study showed significant reductions in BMI, waist circumference, and WHR in both intervention groups. Clinical symptoms like polyphagia, polydipsia, and excessive sweating improved notably, with better EOSS scores. No serious adverse effects were reported, indicating the safety and efficacy of the Ayurvedic formulations.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".