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Record W4413897237 · doi:10.1002/acr2.70092

A Tale of Many Canadas: Associations of Ancestry With Juvenile Idiopathic Arthritis Categories and Disease Severity at Presentation to Care

2025· article· en· W4413897237 on OpenAlexafffundabout
Stephanie Wong, Lori B. Tucker, Kristin Houghton, David A. Cabral, Mercedes Chan, Kimberly Morishita, Rae S. M. Yeung, Kiem Oen, Ciarán M. Duffy, Roberta Berard, Gaëlle Chédeville, Thomas M. Loughin, Jaime Guzmán

Bibliographic record

VenueACR Open Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsMcGill UniversityMcGill University Health CentreSimon Fraser UniversityUniversity of OttawaLondon Health Sciences CentreSickKids FoundationBC Children's HospitalWestern UniversityUniversity of TorontoUniversity of ManitobaChildren's Hospital of Eastern OntarioHospital for Sick ChildrenUniversity of British Columbia
FundersCanadian Institutes of Health ResearchBC Children's Hospital
KeywordsMedicineOligoarthritisArthritisPolyarthritisAncestry-informative markerDemographyPsoriatic arthritisGenetic genealogyJuvenileJuvenile rheumatoid arthritisCohortDiseaseRheumatologyRheumatoid factorInternal medicinePopulationAllele frequencyGeneticsGenotypeBiology

Abstract

fetched live from OpenAlex

Objective To assess associations of ancestry with juvenile idiopathic arthritis (JIA) categories and clinical Juvenile Arthritis Disease Activity Scores (cJADAS10) at presentation to pediatric rheumatology care in a multicultural country with universal health care. Methods Parents reported their child's ancestry in the Research in Arthritis in Canadian Children Emphasizing Outcomes (ReACCh‐Out) cohort. For each ancestry reported for ≥30 children, we compared JIA category distribution and median cJADAS10 scores among three groups: only that ancestry, with that and other ancestries, and without that ancestry. Chi‐square, Fisher's exact, and Kruskal‐Wallis tests compared the three groups and multivariable linear regression assessed factors associated with cJADAS10 scores. Results Among 1,407 participants, 629 (44.7%) reported more than one ancestry. British ancestry was associated with higher median cJADAS10 scores (7.5) and higher frequency of enthesitis‐related arthritis (18.7%) and psoriatic arthritis (10.0%), French ancestry was associated with lower cJADAS10 scores (5.8) and higher oligoarthritis (51.2%), Indigenous ancestry was associated with higher cJADAS10 scores (11.0) and higher rheumatoid factor–positive polyarthritis (21.9%), Black ancestry was associated with higher rheumatoid factor–positive polyarthritis (16.0%), and Eastern European ancestry was associated with lower cJADAS10 scores (3.6). Associations of ancestry with cJADAS10 scores were largely explained by differences in JIA categories (total R2 = 0.28, with R2 = 0.25 for JIA category alone). Black ancestry was associated with longer time from symptom onset to diagnosis (27 vs 18.9 weeks). Conclusions British and French ancestries had distinct associations with JIA categories and cJADAS10 scores, and many children had multiple ancestries, questioning the use of a single “European” reference group. Higher cJADAS10 scores were largely explained by differences in JIA categories across ancestries. image

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)0.002
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 score0.022
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.316
Teacher spread0.299 · 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
Published2025
Admission routes3
Has abstractyes

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