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Record W1964121585 · doi:10.3899/jrheum.120320

Quantitative Radiographic Features of Early Knee Osteoarthritis: Development Over 5 Years and Relationship with Symptoms in the CHECK Cohort

2012· article· en· W1964121585 on OpenAlexvenueaboutno aff
M.B. Kinds, A.C. Marijnissen, J. W. J. Bijlsma, Maarten Boers, Floris P. J. G. Lafeber, Paco M J Welsing

Bibliographic record

VenueThe Journal of Rheumatology · 2012
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersErasmus Medisch CentrumUniversiteit LeidenLeids Universitair Medisch CentrumMedisch Spectrum Twente
KeywordsMedicineOsteoarthritisCohortRadiographyCohort studyArthropathyPhysical therapyInternal medicineSurgeryPathologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate whether computer-assisted, interactive digital analysis of knee radiographs enables identification of different quantitative features of joint damage, and to evaluate the relationship of such features with each other and with clinical characteristics during 5-year followup in early osteoarthritis (OA). METHODS: Knee radiographs from the Cohort Hip and Cohort Knee (CHECK) study, including 1002 individuals with early OA complaints, were evaluated for different measures with knee images digital analysis (KIDA). To aid definition of different radiographic features of OA, principal component analysis of KIDA was used. Features were correlated (Pearson) to each other, evaluated for changes over time, and related to clinical outcome (Western Ontario and McMaster Universities Osteoarthritis Index for pain and function) using baseline, 2-year, and 5-year followup data. RESULTS: The identified radiographic features were joint space width (JSW: minimum, medial, lateral), varus angle, osteophyte area, eminence height, and bone density. The features progressed in severity at different times during followup: early (medial JSW, osteophyte area), late (minimum and lateral JSW, eminence height), and both early and late (varus angle, bone density). Correlations between different radiographic features varied between timepoints. The JSW features were most strongly related to each other (largest r = 0.82), but also, e.g., osteophytes and bone density were correlated (largest r = 0.33). The relationships with clinical outcome varied over time, but were most commonly found for osteophyte area and JSW. CONCLUSION: In this early OA cohort, different radiographic features were identified that progressed at different rates between timepoints. The relations between radiographic features and with clinical outcome varied over time. This implies that longitudinal evaluation of different features can improve insight into progression of OA.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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 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

Citations34
Published2012
Admission routes2
Has abstractyes

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