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Record W203439151 · doi:10.3233/ies-2010-0385

The effect of two exercise programs on various functional outcome measures in patients with osteoarthritis of the knee: A randomized controlled clinical trial

2010· article· en· W203439151 on OpenAlexaboutno aff
Ali Sallı, Nilay Şahin, Akın Başkent, Hatice Uğurlu

Bibliographic record

VenueIsokinetics and Exercise Science · 2010
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical therapyOsteoarthritisRandomized controlled trialMedicineOutcome (game theory)Physical medicine and rehabilitationAlternative medicineInternal medicineMathematics

Abstract

fetched live from OpenAlex

We aimed to investigate the effects of isometric and combined concentric-eccentric (C-E) isokinetic types of exercise applied to the knee muscles in patients with knee osteoarthritis (OA) in an attempt to identify which type of exercise would be most effective in terms of pain relief, functional status, quality of life, and muscular strength. This was a controlled trial in which 71 patients were randomized into three groups. The first group was assigned to C-E, the second group to isometric isokinetic exercises, while the third, control group, was only given paracetamol. A visual analog scale for pain, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Short From-36 (SF-36) for functional status and quality of life, and the isokinetic test for muscular strength were evaluated. Significant improvements were recorded in all groups for pre and post-treatment pain, the WOMAC and the SF-36 (P< 0.001). Among the exercise groups, improvement was significantly better in the C-E, isokinetic exercise group as compared with the isometric exercise group (P < 0.001). Isokinetic exercises are recommended as a treatment modality. However, the long-term effects of these exercises on pain and osteoarthritis progression need to be investigated.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.280
Teacher spread0.268 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized 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

Citations49
Published2010
Admission routes1
Has abstractyes

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