Ayurvedic Therapeutic Regimen as an Add-On to Optimized Conventional Management of Parkinson Disease: Protocol for an Exploratory Randomized Controlled Trial Evaluating Clinical, Cortical Excitability, Neuroimmune, and Autonomic Function Parameters
Bibliographic record
Abstract
Background: Parkinson disease (PD), a progressive neurodegenerative disorder, lacks disease-modifying treatments. Current therapies focus on symptomatic relief, highlighting the need for adjunctive neuroprotective strategies. Ayurveda, a holistic system, shows promise in improving PD clinical outcomes. Objective: This assessor-blinded randomized controlled study aims to systematically evaluate the efficacy of an add-on Ayurveda therapeutic regimen compared to conventional treatment as usual (TAU) in improving the clinical outcomes of PD. Methods: A total of 80 patients with PD, diagnosed according to UK Parkinson's Disease Society Brain Bank criteria, will be randomized into two groups: TAU and add-on Ayurveda. The intervention group will receive Ayurvedic therapy alongside conventional treatment for 180 days, whereas the control group will continue TAU. Assessments will occur at baseline and at 60-, 120-, and 180-day follow-ups, evaluating motor and nonmotor symptoms. Transcranial magnetic stimulation, heart rate variability, and pulmonary function tests will assess cortical excitability, autonomic function, and pulmonary function, respectively. Immunological parameters, including cytokine levels and telomere length, will be analyzed at baseline and at 180 days to explore disease-modifying effects. Liver and renal function tests will monitor safety. Results: As of 2025, a total of 259 patients with PD have been screened for eligibility, of whom 58 participants have been successfully enrolled in the trial. Among these, 33 participants have completed the intervention and follow-up assessments, 14 have discontinued participation, and 11 are currently continuing participation in the study. Recruitment and follow-up are ongoing, and the trial is scheduled for completion in September 2026. Conclusions: This study aims to address the lack of mechanistic evidence and robust data on Ayurveda in PD. By systematically evaluating clinical efficacy and potential biomechanisms, the findings will provide preliminary evidence for Ayurvedic interventions, potentially paving the way for their integration into comprehensive PD management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".