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Record W1606474382 · doi:10.1002/art.20238

Predictors of pain in children with established juvenile rheumatoid arthritis

2004· article· en· W1606474382 on OpenAlexaff
Peter N. Malleson, Kiem Oen, David A. Cabral, Ross E. Petty, Alan Rosenberg, Mary Cheang

Bibliographic record

VenueArthritis Care & Research · 2004
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsUniversity of SaskatchewanUniversity of ManitobaUniversity of British Columbia
Fundersnot available
KeywordsMedicineJuvenile rheumatoid arthritisPsychosocialCohortDiseasePhysical therapyRheumatoid arthritisInternal medicineVisual analogue scaleJuvenileDemographyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine demographic and disease-related variables that affect pain in a large cohort of patients with juvenile rheumatoid arthritis (JRA). METHODS: Selection criteria were an onset of JRA >/=5 years prior to study and age >/=8 years at the time of the study. Pain was measured by a self-administered 10-cm visual analog scale. Possible explanatory variables studied included age at study, sex, race, onset subtype, active disease duration, active joint count, and physician's global assessment (PGA). RESULTS: In a multiple regression model, active disease duration, PGA, and age at study were independent predictors explaining 22% of the variation in pain scores. Stratified analyses showed an effect of age in the 8-15-year group, but not in older patients. CONCLUSION: Disease-related factors explain only a small proportion of the variation in pain scores. Age has an effect on pain scores only in younger patients. The role of other factors, including psychosocial factors, needs further study.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.266
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.280
Teacher spread0.268 · 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 teacher head, 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

Citations63
Published2004
Admission routes1
Has abstractyes

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