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Record W2538635756 · doi:10.3390/jfmk1040355

The Effects of Exercise and Kinesio Tape on Physical Limitations in Patients with Knee Osteoarthritis

2016· article· en· W2538635756 on OpenAlexaboutno aff
Paola Castrogiovanni, Angelo Di Giunta, Claudia Guglielmino, Federico Roggio, Domenico M. Romeo, Federica Fidone, Rosa Imbesi, Carla Loreto, Sergio Castorina, Giuseppe Musumeci

Bibliographic record

VenueJournal of Functional Morphology and Kinesiology · 2016
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisMedicinePhysical therapyKnee painAnalgesicVisual analogue scalePhysical medicine and rehabilitationTherapeutic effectSurgeryAnesthesiaAlternative medicine

Abstract

fetched live from OpenAlex

The aim of this study was to investigate the effects of kinesio taping (KT) in combination with moderate adapted exercise on the functional outcome of patients with knee osteoarthritis. We included 66 patients who presented pain and functional impairment with osteoarthritis. At the end of the treatment, only 57 patients remained because nine patients were excluded. Patients were randomly allocated to three treatment groups: (1) exercise group; (2) exercise KT with tension application (stabilizing effect) group; (3) exercise KT without tension application (draining effect) group. We used different methods of investigation: the Western Ontario and McMaster Universities Arthritis Index, the Visual Analogue Scaling Score for Pain, the Timed Up and Go test and analgesic consumption. Our results showed a reduction in knee pain, improvement in knee function and also less need for medication in patients with knee osteoarthritis treated with kinesio taping in combination with exercise for, at least, a period of three months. In conclusion, we can assert that therapeutic knee kinesio taping in association with a moderate adapted training is an effective method for the management of pain and disability limitations in patients with knee osteoarthritis.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.207
Teacher spread0.197 · 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 designObservational
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

Citations50
Published2016
Admission routes1
Has abstractyes

Explore more

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