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Record W4390079515 · doi:10.51910/ijhdr.v22icf.1313

Revisiting the Homoeopathic approach to Osteoarthritis- A Review

2023· review· en· W4390079515 on OpenAlexaboutno aff
Dr Parth Aphale, Shashank Dokania, Dr Dharmendra Sharma

Bibliographic record

VenueInternational Journal of High Dilution Research - ISSN 1982-6206 · 2023
Typereview
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHomeopathyWOMACOsteoarthritisMedicinePhysical therapyAlternative medicineInternal medicineTraditional medicinePathology

Abstract

fetched live from OpenAlex

Introduction: Leading the world towards disability and prolonged sufferings, osteoarthritis (OA) multiplies the number of cases to about 113.25% over a decade. Healthcare services of developing nations are knocked down with flooding patients only to understand that the patient has to undergo palliative treatment for his entire life. Homoeopathic principles are way beyond palliation, a much reliable approach on the lines of minimum doses in treating OA. Objective: This article reviews the variable conditions associated with OA and the adverse effects these conditions can have on patients. 7 studies have been reviewed in this article and the effects of Homoeopathic attenuations on OA patients have been studied. Methods: Parameters including oxidant stress, physiotherapy, analog scales, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, erythrocyte lipid peroxidation (LP) and Superoxide dismutase (SOD) levels and Activities of Daily living (ADL) have been compared and results have been outlined before and after treatment with homoeopathic ultra high dilutions. Results: Clinical analysis and statistical data verifies improved WOMAC score, reduction in stiffness and pain in the joints, reduction in marginal deposition of osteocytes, erythrocyte LP and SOD levels post treatment with homoeopathic remedies. 
 
 
 

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.221
GPT teacher head0.514
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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