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Record W1999258221 · doi:10.1163/1568569042664468

Effectiveness of two different physical therapy programmes in the treatment of knee osteoarthritis

2004· article· en· W1999258221 on OpenAlexaboutno aff
Emine Handan Tüzün, Aydan Aytar, Levent Eker, Arzu Daşkapan

Bibliographic record

VenueThe Pain Clinic · 2004
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisPhysical therapyWOMACTranscutaneous electrical nerve stimulationPsychological interventionKnee painRheumatologyAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

AbstractAbstractCombined physical therapy interventions traditionally are frequently used in clinical practice for pain relief and to improve physical function in patients with knee osteoarthritis. The aim of the present study was to evaluate the effectiveness of two different physical therapy programmes on patients with knee osteoarthritis. A total 62 patients who fulfilled clinical and radiological criteria of the American College of Rheumatology for primary knee osteoarthritis were randomly allocated to two groups. After hot pack and transcutaneous electrical nerve stimulation applications, the first group was treated with isokinetic exercises and the second group with isotonic exercises. Both groups showed marked decreases of pain and increases of physical function, according to the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index, immediately after treatment and three months later. The patients in both groups also showed a significant improvement in mental health scale of the Medical Outcomes 36-Item Short Form Health Survey (SF-36). In conclusion, the present study showed that both physical therapy intervention programmes are an effective treatment for knee osteoarthritis, but isokinetic exercises work better.Keywords: EXERCISEKNEE OSTEOARTHRITISISOKINETICISOTONIC

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.028
GPT teacher head0.335
Teacher spread0.306 · 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 designOther design
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

Citations14
Published2004
Admission routes1
Has abstractyes

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