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Assessment of Juvenile Idiopathic Arthritis Outcomes and Place of Residence in Canada: Identifying Disparities in Care

2025· article· en· W4411846574 on OpenAlexaffvenueabout
Molly J. Dushnicky, Andrea Human, Lori B. Tucker, Shiran Zhong, Jason Gilliland, Michael R. Miller, Jaime Guzmán, Roberta Berard

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsChildren’s Health Research InstituteWestern UniversityBC Children's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineResidenceJuvenileArthritisFamily medicinePhysical therapyGerontologyIntensive care medicineInternal medicineDemography

Abstract

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Objectives Previous research has shown that demographic, health care system, socioeconomic, cultural, and ethnic factors, may be contributors to JIA outcomes.[1,2] We aimed to assess the association of social and environmental factors with JIA outcomes in Canada. Methods Data was collected by the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) National JIA Registry, a registry of children newly diagnosed with JIA that collects and shares longitudinal data on disease course and outcomes. Demographic and clinical characteristics, medications used, and physician and patient-reported outcome measures were obtained for patients enrolled over a 4-year period (February 2017-December 2021). Clinical outcomes were linked to neighborhood-level geographic and sociodemographic factors based on postal code and data from the 2021 Statistics Canada Census. For each patient, the sociodemographic and environmental variables are based on the dissemination area associated with their postal code. We assessed the attainment of two primary outcomes within 6 months of enrollment: 1) clinically inactive disease, as defined by Wallace criteria and 2) pain relief, defined as a pain score <1 reported by patients and parents in 21-point pain scales. Logistic regression was used to evaluate the association of sociodemographic variables with the outcomes of interest. Results A total of 641 patients were included. 41.2% of patients achieved inactive disease within 6 months of enrollment. Table 1 demonstrates associations between the primary outcomes and neighborhood-level data. Greater distance to nearest pediatric rheumatology center was associated with decreased likelihood of attaining inactive disease by 6 months. Every 100 km increase in distance decreased the odds of attaining inactive disease by 10% (OR 0.90, 95% CI 0.81-0.99, P = 0.026). By 6 months, 27.9% of patients and 34.6% of parents reported relief of pain. Higher dwelling density (number of dwellings per square kilometer of the dissemination area) was associated with decreased odds of attaining pain relief reported by the patient (OR 0.67, 95% CI 0.45-0.99, P = 0.043). Table 1: Associations between attainment of clinically inactive disease and pain relief in patients with JIA within 6 months and neighbourhood-level geographic and sociodemographic factors. Conclusion Among Canadian children newly diagnosed with JIA, greater distance to the nearest pediatric rheumatology center was associated with lesser attainment of inactive disease, and higher dwelling density was associated with lesser attainment of pain relief by 6 months. Further analysis will examine the possible role of diagnostic or treatment delays in explaining these relationships. [1.] Lewis KA. J Pediatr Nurs 2017;37: 13-21. [2.] Tesher MS. Curr Rheumatol Rep 2012;14:116-20. Best Abstract on Equity Diversity and Inclusion in Rheumatology Award

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 score0.019
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.006
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.308
Teacher spread0.293 · 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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