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Record W4403991116 · doi:10.1002/art.43049

Characterizing Nonarticular Pain at Early Rheumatoid Arthritis Diagnosis: Evolution Over the First Year of Treatment and Impact on Remission in a Prospective Real‐World Early Rheumatoid Arthritis Cohort

2024· article· en· W4403991116 on OpenAlexafffund
Charis F. Meng, Yvonne Lee, Orit Schieir, Marie‐France Valois, Margaret A. Butler, Gilles Boire, Glen Hazlewood, Hugues Allard‐Chamard, Carol Hitchon, D. Tin, Carter Thorne, Louis Bessette, Janet Pope, Susan J. Bartlett, Vivian P. Bykerk

Bibliographic record

VenueArthritis & Rheumatology · 2024
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsWestern UniversityUniversité LavalUniversity of TorontoSouthlake Regional Health CenterUniversity of ManitobaArthritis Research Centre of CanadaMcGill UniversityUniversity of CalgaryUniversité de Sherbrooke
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesAbbVie CanadaPfizer CanadaHospital for Special SurgeryPfizer
KeywordsNapMedicineRheumatoid arthritisCohortInternal medicineGeeArthritisOdds ratioPhysical therapyOddsConfidence intervalGeneralized estimating equationLogistic regressionPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Our objective was to characterize nonarticular pain (NAP) at early rheumatoid arthritis (RA) diagnosis, the evolution over the first year of treatment, associations with active RA inflammation, and the impact on remission. METHODS: This real-world, longitudinal multicenter cohort study observed participants with active early RA (symptoms <1 year and Clinical Disease Activity Index [CDAI] >2.8) enrolled between January 2017 and January 2022 who completed a body pain diagram over 1 year. Participants were grouped by prespecified definitions of NAP: (1) none, (2) regional, or (3) widespread. Rheumatologists performed joint counts. Descriptive statistics summarized the frequency and evolution of NAP patterns over 1 year. Chi-square tests compared the proportions of tender and/or swollen joints by the presence of pain in each NAP section. Multiadjusted generalized estimating equations regression models estimated associations of NAP patterns with remission outcomes. RESULTS: Participants (N = 392) were 70% female, with a mean ± SD age of 56 ± 14 years and mean ± SD symptoms duration of 5.1 ± 2.7 months. More than half reported NAP at baseline, with most (73%) presenting with regional NAP. Common patterns of regional NAP were axial (40%) and pain in upper quadrants (17%). A total of 43% of those with regional NAP persisted or worsened over 1 year, whereas 73% of those with widespread NAP resolved or improved. Joint inflammation was more frequently reported in areas with NAP versus areas without NAP. Regional and widespread NAP were associated with lower odds of reaching CDAI remission (adjusted odds ratio 0.42, 95% confidence interval 0.26-0.70 and adjusted odds ratio 0.30, 95% confidence interval 0.12-0.74), respectively. CONCLUSION: Regional NAP is common and persistent in early RA and impacts remission. RA activity may contribute to NAP. More attention to NAP in RA care is warranted.

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)0.002
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.007
GPT teacher head0.255
Teacher spread0.248 · 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

Citations9
Published2024
Admission routes2
Has abstractyes

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