Effectiveness of Ayush Rasayana A and B on the Quality of Life of Older Adults: Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: With advancing age among older adults, the associated debilities increase, indicating a deteriorating health status as there is a gradual loss of muscle mass, strength, and functionality. Ayush Rasayana A and B are coded Ayurvedic medicines developed from herbal extracts. This study has been planned to prevent debilitating conditions and improve the quality of life (QOL) in older adults. OBJECTIVE: This study aimed to assess the effectiveness of Ayush Rasayana A and B on the QOL, quality of sleep, and functionality of older adults, along with the tolerability of the intervention. METHODS: This was a multicenter, open-label, cluster randomized controlled trial conducted with 720 participants aged 60 to 75 years. The participants were divided into 2 groups (intervention and control), with both receiving Ayurvedic ancillary treatment for 3 months. The intervention group additionally received 10 g of Ayush Rasayana A orally once daily at bedtime for 6 days, followed by 1.5 g of Ayush Rasayana B orally twice daily before food for the remaining 84 days. The assessment criteria included the Older People's Quality of Life Questionnaire Brief, Katz Index of Independence in Activities of Daily Living, Pittsburgh Sleep Quality Index, Five Times Sit-to-Stand Test, and shoulder and scapular movements. Any change in hematological and biochemical parameters and occurrence of treatment-emergent adverse events were also assessed during the study period. RESULTS: The recruitment of the participants started in December 2023, and the final follow-up was completed in April 2024. Out of the total 720 enrolled participants, 686 (95.3%) completed the study up to the last follow-up. CONCLUSIONS: This study may provide evidence-based data to establish preventive treatment protocols for enhancing the QOL and functionality among older adults. The study results may also be helpful for the planning of interdisciplinary health policies for improving the health conditions of different populations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58186.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.021 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.046 | 0.006 |
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".