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Record W2382745640

Effect of Multidisciplinary Treatments on Proprioception in Knee Osteoarthritis

2011· article· en· W2382745640 on OpenAlexaboutno aff
Wei Chen

Bibliographic record

VenueZhongguo kangfu lilun yu shijian · 2011
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisIsometric exerciseProprioceptionMassagePhysical therapyWOMACPhysical medicine and rehabilitationAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

Objective To explore if the treatments with the diclofenac diethylamine emulge import by pulsed ultrasound,massage therapy and quadriceps muscle strengthen training can promote the recovery of prorpioception in patients with knee osteoarthritis.Methods On the basis of health education,30 elderly patients aged 60 or over with knee osteoarthritis were accepted treatments with 10 times of diclofenac diethylamine emulge import by pulsed ultrasound,6 times of massage therapy in 2 weeks,and quadriceps muscle strengthen training once or twice a day.Results There were significant differences in the scores of Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC),the maximum isometric extension strength of involved knees,the average isometric extension strength of involved knees and the reposition accuracy error mean of involved knees before and after the treatments(P0.05).Conclusion The treatments with the diclofenac diethylamine emulge import by pulsed ultrasound,massage therapy and quadriceps muscle strengthen training can not only play a therapeutic effect and shorten the duration of treatment,but also promote the recovery of proprioception in subjects with knee osteoarthritis significantly.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.045
GPT teacher head0.359
Teacher spread0.314 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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