MétaCan
Menu
Back to cohort
Record W2152271013 · doi:10.1002/art.21534

Associations between pain, function, and radiographic features in osteoarthritis of the knee

2005· article· en· W2152271013 on OpenAlexaboutno aff
B Szebenyi, Anthony P. Hollander, Paul Dieppe, Brian Quilty, John C. Duddy, Shane Clarke, John Kirwan

Bibliographic record

VenueArthritis & Rheumatism · 2005
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisMedicineRadiographyKnee painCompartment (ship)Knee JointArthropathyPatellofemoral jointVisual analogue scalePhysical therapyPhysical medicine and rehabilitationOrthodonticsSurgeryPatellaPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the associations between pain, loss of function, and radiographic changes in knee osteoarthritis (OA), taking into account both the patellofemoral and tibiofemoral compartments. METHODS: Both knees of 167 community-based patients with OA in at least 1 of their knees were assessed. Pain was measured by visual analog scale, and function was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index. Anteroposterior standing radiographs with the knee in extension and lateral 30 degrees flexion were obtained and assessed for the Kellgren/Lawrence score and for individual features (osteophytes, joint space narrowing, and subchondral bone sclerosis) in each compartment. RESULTS: Knees with structural changes in both compartments were more likely to be painful and to be associated with loss of function than were knees in which only 1 compartment was affected. The individual feature most strongly associated with pain was subchondral bone sclerosis. CONCLUSION: Studies exploring the associations between structural and symptomatic knee OA need to include an assessment of the patellofemoral compartment, and individual radiographic features rather than a global severity score should be considered in these studies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score0.687

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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

Citations220
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueArthritis & RheumatismSame topicOsteoarthritis Treatment and MechanismsFrench-language works237,207