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POS0105 CHANGES IN RADIOGRAPHIC SIGNS IN PATIENTS WITH HAND OSTEOARTHRITIS DURING 2 YEARS

2023· article· en· W4379521460 on OpenAlexfundaboutno aff
Coen van der Meulen, L.A. van de Stadt, Frits R. Rosendaal, S. van Beest, M. Kloppenburg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersArthritis SocietyDutch Arthritis Society
KeywordsMedicineOsteoarthritisCohortRadiographyLogistic regressionPhysical therapyDemographicsRheumatologyInternal medicineSurgeryPathologyDemography

Abstract

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Background Hand osteoarthritis is a disorder that often evolves slowly. Some patients may have structural progression over a short term. Objectives We aimed to investigate which patients show radiographic progression over 2 years and what their determinants are. Methods Data from the ongoing HOSTAS (Hand OSTeoArthritis in Secondary care) cohort were used, consisting of 538 consecutive patients with primary hand OA diagnosed by their rheumatologist, followed for two years. Hand radiographs were obtained at baseline and year two. Questionnaires regarding demographics, disease and patient characteristics and the Australian Canadian Hand osteoarthritis index (AUSCAN) were collected. Hand radiographs were scored blinded, paired and in chronological order, using the Osteoarthritis Research Society International (OARSI) system (osteophytes (OP) and joint space narrowing (JSN), scored 0-3) per joint (summed for total 0-96). Intraobserver reliability was high, (intra-class correlation (ICC) 0.99 and 1.00 at baseline for OP and JSN sumscores, respectively). Reliability for change scores was high (ICC 0.77 and 0.86, for OP and JSN, respectively). The smallest detectable changes were 0.92 for OP (cut-off 1) and 1.32 for JSN (cut-off 2). Cut-offs were used to classify progressors (increase) or non-progressors (stable or decrease). Additionally, baseline radiographs were scored using the Kellgren-Lawrence system (0-4 per joint, total 0-120). Erosive disease was defined as at least 1 joint in the Verbruggen-Veys erosive or remodeling phase. Progressor and non-progressor groups were analysed for determinants using logistic regression. Results 442 patients had radiographs assessed at baseline and year 2, with mean (SD) age 61 (8.4) years and 85% female. Median (IQR) baseline OP/JSN sumscores were 9 (5-18) and 9 (4-19), respectively. Based on the SDC, 272/417 (65%) participants progressed on OP scores (median [IQR] change 1 [0-2]) and 135/419 (32%) on JSN scores (median [IQR] change 1 [0-2]). Four and 18 had a decrease in OP and JSN, respectively. Progression of OP was positively associated with erosive disease, measures of radiographic damage at baseline and female sex. Progression of JSN was positively associated with age, erosive disease and radiographic damage at baseline. Progression of JSN showed a positive association with changes in AUSCAN scores over 2 years. Conclusion Over 2 years, considerable radiographic progression was seen. Especially patients with erosive disease and the most severe radiographic damage at baseline were at risk for progression. Progression of JSN was associated with changes in pain and function. Progression in JSN was associated with age, whereas OP was with female sex. These findings may potentially represent different underlying pathogenetic mechanisms. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests Coen van der Meulen Grant/research support from: The HOSTAS study is supported by a grant from the Dutch Arthritis Society, paid to the institution, Lotte van de Stadt: None declared, Frits Rosendaal: None declared, Sjoerd van Beest: None declared, Margreet Kloppenburg Grant/research support from: The HOSTAS study is supported by a grant from the Dutch Arthritis Society, paid to the institution.

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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)0.003
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.205
Teacher spread0.198 · 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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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