Evaluating the Efficacy of Marma Therapy for Pain in Lumbar Disc Herniation With Radiculopathy: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Marma therapy, a traditional Ayurvedic practice, involves the precise stimulation of marmas (vital points that regulate prana [vital energy]) and alleviates musculoskeletal pain and dysfunction. While historical texts describe marma's role in pain relief, no randomized controlled trials have evaluated its efficacy and safety in lumbar disc herniation (LDH)-related radiculopathy. Objective: This study aims to explore the efficacy and safety of marma therapy in a commonly occurring painful condition, namely, radiculopathy due to LDH. Methods: Selected patients with LDH and radiculopathy are randomized into 2 groups using a computer-generated random number sequence. The participants in group 1 (the trial arm) are treated with marma therapy for 4 weeks, and those in group 2 (the control arm) receive physiotherapy for 4 weeks. All the participants in both groups are given an oral medicine, trayodashanga guggulu, an Ayurvedic formulation, for 12 weeks. Results: As of November 2025, a total of 90 patients have been enrolled in both groups. Data analysis is ongoing. The study will be reported following standard guidelines for reporting randomized controlled trials. Clinical trial results will be disseminated through conferences and publication in a peer-reviewed scientific journal. Conclusions: Marma therapy, if proven effective and safe in pain management, can improve the quality of life of patients with LDH. This protocol can be useful in designing large-scale studies to establish this noninvasive and safe treatment as an alternative modality for the management of neurological pain, such as radiculopathy.
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 | 0.048 | 0.041 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.065 | 0.010 |
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".