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Record W2187638581 · doi:10.1002/art.39324

Brief Report: Cartilage Thickness Change as an Imaging Biomarker of Knee Osteoarthritis Progression: Data From the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium

2015· article· en· W2187638581 on OpenAlexaboutno aff
F. Eckstein, Jamie E. Collins, Michael C. Nevitt, J.A. Lynch, Virginia B. Kraus, Jeffrey N. Katz, W. Wirth, Ali Guermazi, Frank W. Roemer, David J. Hunter

Bibliographic record

VenueArthritis & Rheumatology · 2015
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersDePuy MitekNIH Clinical CenterGlaxoSmithKlineStrykerAmgenU.S. Public Health ServiceArthritis FoundationAbbVieSanofiNational Institute of Arthritis and Musculoskeletal and Skin DiseasesFoundation for the National Institutes of Health
KeywordsOsteoarthritisMedicineCartilageMagnetic resonance imagingRadiographyKnee painConfidence intervalSagittal planeOdds ratioWOMACTibiaImaging biomarkerCompartment (ship)SurgeryRadiologyInternal medicineAnatomyPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the association of cartilage thickness change over 24 months, as determined by magnetic resonance imaging (MRI), with knee osteoarthritis (OA) progression at 24-48 months. METHODS: This nested case-control study included 600 knees with a baseline Kellgren/Lawrence (K/L) grade of 1-3 from 600 Osteoarthritis Initiative (OAI) participants. Case knees (n = 194) had both medial tibiofemoral radiographic joint space loss (≥0.7 mm) and a persistent increase in the Western Ontario and McMaster Universities Osteoarthritis Index pain score (≥9 on a 0-100 scale) 24-48 months from baseline. Control knees (n = 406) included 200 with neither radiographic nor pain progression, 103 with radiographic progression only, and 103 with pain progression only. Medial and lateral femorotibial cartilage was segmented from sagittal 3T MRIs at baseline, 12 months, and 24 months. Logistic regression was used to assess the association of change in cartilage thickness, with a focus on the central medial femorotibial compartment, and OA progression. RESULTS: Central medial femorotibial compartment thickness loss was significantly associated with case status, with an odds ratio (OR) of 1.9 (95% confidence interval [95% CI] 1.6-2.3) (P < 0.0001). Association with case status reached P < 0.05 for both the central femur (OR 1.8 [95% CI 1.5-2.2]) and the central tibia (OR 1.6 [95% CI 1.3-1.9]). Lateral femorotibial compartment cartilage thickness loss, in contrast, was not significantly associated with case status. A reduction in central medial femorotibial compartment cartilage thickness was strongly associated with radiographic progression (OR 4.0 [95% CI 2.9-5.3]; P < 0.0001) and only weakly associated with pain progression (OR 1.3 [95% CI 1.1-1.6]; P < 0.01). CONCLUSION: Our findings indicate that loss of medial femorotibial cartilage thickness over 24 months is associated with the combination of radiographic and pain progression in the knee, with a stronger association for radiographic progression.

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)0.004
metaresearch head score (Gemma)0.018
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 score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.090
GPT teacher head0.357
Teacher spread0.267 · 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

Citations170
Published2015
Admission routes1
Has abstractyes

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