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Record W2901218038 · doi:10.1370/afm.2320

Clinic-Based Patellar Mobilization Therapy for Knee Osteoarthritis: A Randomized Clinical Trial

2018· article· en· W2901218038 on OpenAlexaboutno aff
Regina Wing Shan Sit, Keith K.W. Chan, Dan Zou, Dicken Cheong Chun Chan, Benjamin Hon Kei Yip, Ying Ho Chan, Vincent CH Chung, Kenneth Dean Reeves, Samuel Yeung Shan Wong

Bibliographic record

VenueThe Annals of Family Medicine · 2018
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisRandomized controlled trialPhysical therapyMobilizationAlternative medicineSurgeryPathology

Abstract

fetched live from OpenAlex

PURPOSE: We performed a phase 2 randomized clinical trial to evaluate the preliminary effectiveness of a clinic-based patellar mobilization therapy (PMT) in patients with knee osteoarthritis. METHODS: We recruited 208 patients with knee osteoarthritis at primary care clinics in Hong Kong. Patients were randomly assigned (1:1) to the intervention group or the control group. The intervention group received 3 PMT treatment sessions from primary care physicians at 2-month intervals, with concomitant prescription of a home-based vastus medialis oblique muscle exercise. The control group received PMT after the study period. The primary outcome was the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score. Secondary outcomes included the WOMAC composite, function, and stiffness scores; the visual analog scale score for pain; objective physical function tests (30-s chair stand, 40-m walk test, timed up and go test, and EuroQol-5D). All outcomes were evaluated at baseline and at 24 weeks through intention-to-treat analysis. RESULTS: <.001). All secondary outcomes also demonstrated significant between-group differences. CONCLUSIONS: Patellar mobilization therapy has the potential to reduce pain and improve function and quality of life for patients with knee osteoarthritis. Future clinical trials with comparison to other active comparator controls will help determine the overall efficacy and facilitate the deployment of PMT in real-world practice.

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)0.006
metaresearch head score (Gemma)0.002
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 score0.421
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.320
GPT teacher head0.435
Teacher spread0.114 · 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

Citations29
Published2018
Admission routes1
Has abstractyes

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