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Record W1973201749 · doi:10.1002/art.34594

Individual magnetic resonance imaging and radiographic features of knee osteoarthritis in subjects with unilateral knee pain: The Health, Aging, and Body Composition Study

2012· article· en· W1973201749 on OpenAlexfundno aff
M K Javaid, A. Kiran, Ali Guermazi, C. Kent Kwoh, S. Zaïm, Laura Carbone, Tamara Harris, Charles E. McCulloch, Nigel Arden, Nancy E. Lane, David T. Felson, Michael C. Nevitt

Bibliographic record

VenueArthritis & Rheumatism · 2012
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersNational Institute of Nursing ResearchNational Institute on AgingVersus ArthritisMcMaster University
KeywordsMedicineOsteoarthritisMagnetic resonance imagingConfidence intervalOdds ratioKnee painRadiographyKnee JointReceiver operating characteristicRadiologySynovitisPhysical therapyArthritisSurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: Strong associations between radiographic features of knee osteoarthritis (OA) and pain have been demonstrated in persons with unilateral knee symptoms. This study was undertaken to compare radiographic and magnetic resonance imaging (MRI) features of knee OA and assess their ability to discriminate between painful and nonpainful knees in persons with unilateral symptoms. METHODS: The study population included 283 individuals ages 70-79 years with unilateral knee pain who were enrolled in the Health, Aging, and Body Composition Study, a study of weight-related diseases and mobility. Radiographs of both knees were read for Kellgren/Lawrence (K/L) grade and individual radiographic features, and 1.5T MRIs were assessed using the Whole-Organ Magnetic Resonance Imaging Score. The association between structural features and pain was assessed using a within-person case-control design and conditional logistic regression. Receiver operating characteristic (ROC) analysis was then used to test the discriminatory performance of structural features. RESULTS: In conditional logistic analyses, knee pain was significantly associated with both radiographic features (any joint space narrowing grade ≥ 1) (odds ratio 3.20 [95% confidence interval 1.79-5.71]) and MRI features (any cartilage defect scored ≥ 2) (odds ratio 3.67 [95% confidence interval 1.49-9.04]). However, in most subjects, MRI revealed osteophytes and cartilage and bone marrow lesions in both knees, and using ROC analysis, no individual structural feature discriminated well between painful and nonpainful knees. The best-performing MRI feature (synovitis/effusion) was not significantly more informative than K/L grade ≥ 2 (P = 0.42). CONCLUSION: In persons with unilateral knee pain, MRI and radiographic features were associated with knee pain, confirming that structural abnormalities in the knee have an important role in the etiology of pain. However, no single MRI or radiographic finding performed well in discriminating between painful and nonpainful knees. Further work is needed to examine how structural and nonstructural factors influence knee pain.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.975

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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

Citations63
Published2012
Admission routes1
Has abstractyes

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