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Record W4393287822 · doi:10.4103/ayu.ayu_219_17

A comparative clinical study of Janu Basti (medicated oil retention over knee) and Matra Basti (medicated oil enema) with Sahachara Taila along with Adityapaka Guggulu on osteoarthritis of knee joint

2023· article· en· W4393287822 on OpenAlexaboutno aff
Sarvesh Kumar Singh, Kshipra Rajoria, Amit Kumar

Bibliographic record

VenueAYU (An International Quarterly Journal of Research in Ayurveda) · 2023
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEnemaOsteoarthritisKnee JointWOMACPhysical therapyVisual analogue scaleHydrotherapyKnee painSurgeryAlternative medicine

Abstract

fetched live from OpenAlex

Background: Osteoarthritis (OA) of knee is a chronic inflammatory condition of knee joints characterized by pain, swelling, and functional restriction of the joint. In Ayurveda , it can be correlated with Sandhigata Vata . The two most promising therapies for the Ayurveda management are Janu Basti (medicated oil retention over knee) and Matra Basti (medicated oil enema). The present study was conducted to assess the comparative effect of the two Ayurveda procedure which could assist in clinical decision-making for maximum benefit and minimum discomfort for variable requirements of the patients. Aim: The aim of the study was to ascertain the better management among the two therapies. The objective of the study was to assess changes in pain in knee joints through the Visual Analog Scale (VAS) and disability through Western Ontario and McMaster Universities OA Index (WOMAC) from baseline to 30 th day in both the therapies and compare the effect of the both therapies on pain and disability. Materials and methods: In this study, a total of 30 patients having the complaints of OA of knee joint were randomly divided into two groups. Fifteen patients were treated in group A with Janu Basti (external oleation through retention of oil over knee joints for 30 min) with Sahachara Taila along with Adityapaka Guggulu (oral medication) and 15 patients were treated in group B with Matra Basti (enema with medicated oil) with Sahachara Taila along with Adityapaka Guggulu . For the assessment, VAS for pain scoring, WOMAC for disability, Ritchie articular index for tenderness were used, and X-ray were graded on the basis of Kellgren–Lawrence system for OA severity. All the results were calculated by using InStat GraphPad 3 software. For intra-group comparison nonparametric data; “Wilcoxon matched-pairs signed ranks test” and “Paired- t -test” was used. For calculating the inter-group comparison, “Mann–Whitney test” and “unpaired- t -test” was used. All the statistical tests were interpreted as significance at 5% level ( P < 0.05). Results: There were significant changes in VAS, WOMAC score, and tenderness of the affected joint in both the groups. On intergroup comparison, Matra Basti with Sahachara Taila in group B has provided better relief in Sandhigatavata of Janu Snadhi along with Adityapaka Guggulu . Conclusion: The result shows that Ayurvedic management with Matra Basti and Janu Basti along with Adityapaka Guggulu are effective in the management of osteoarthritis (OA) of knee joint. However, Matra Basti along with Adityapaka Guggulu is a better management option than Janu Basti .

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.127
GPT teacher head0.411
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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

Citations3
Published2023
Admission routes1
Has abstractyes

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