Utility of Robin Murphy’s Homoeopathic Medical Repertory (HMR) in the Management of Osteoarthritis: A Case Series
Bibliographic record
Abstract
Introduction: Osteoarthritis (OA) is a chronic degenerative joint disorder prevalent among the elderly, leading to pain, stiffness, and reduced mobility. Conventional management primarily offers symptomatic relief, highlighting the need for individualized and holistic therapeutic approaches. Case Summary: This case series presents three female patients aged 63, 65, and 66 years suffering from bilateral knee OA for 3–5 years. Each case was analyzed using the Homoeopathic Medical Repertory (HMR) to determine individualized prescriptions based on characteristic mental and physical symptoms. Pulsatilla Nigricans, Bryonia Alba and Calcarea Carbonicum were prescribed according to totality and susceptibility, along with auxiliary measures like mild exercises and postural care. Result and Conclusion: Patient progress was assessed objectively using the Western Ontario and McMaster Universities Arthritis Index (WOMAC). The overall improvement ranged between 59% and 63%, indicating notable relief in pain, stiffness, and physical function. These outcomes highlight the therapeutic potential of individualized homoeopathic management guided by HMR and support its integration into clinical practice for chronic degenerative conditions like OA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".