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EFFECT OF CIRCUIT TRAINING IN OSTEOARTHRITIS OF KNEE

2017· article· en· W2622219120 on OpenAlexaboutno aff
P. Bhagat, Vaishali Jagtap, Poovishnu Devi T

Bibliographic record

VenueAsian Journal of Pharmaceutical and Clinical Research · 2017
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACCircuit trainingIsometric exerciseVisual analogue scaleOsteoarthritisMedicinePhysical therapyPhysical medicine and rehabilitationAlternative medicine

Abstract

fetched live from OpenAlex

Objectives: The objective of the study is to find the effect of circuit training on quality of life. To find the effect of conventional therapy (interferential therapy [IFT] and isometric exercise) and to find the effect of conventional therapy with or without circuit training in OA knee.Methods: A total of 30 participants of 50-60 years of age, having osteoarthritis (OA) knee were recruited and allocated into two groups and treated with IFT, exercises, and circuit training for 4 weeks. Pre- and post-intervention outcome were measured using Western Ontario and McMaster University OA Index (WOMAC) and visual analog scale (VAS).Result: Both groups showed improvement, but there was an extremely significant improvement on VAS and WOMAC scales in the group treated with circuit training along with conventional treatment (IFT and isometric exercises).Conclusion: From this study, we conclude that circuit training along with IFT and isometric exercises shows an extremely significant effect over IFT and isometric exercises alone in OA knee patients.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.218
GPT teacher head0.534
Teacher spread0.315 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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Same venueAsian Journal of Pharmaceutical and Clinical ResearchSame topicOsteoarthritis Treatment and MechanismsFrench-language works237,207