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Record W2051340373

Clinical, Laboratory and Radiological Predictors of Extension of Oligoarticular Juvenile Idiopathic Arthritis: A Prospective Study

2012· article· en· W2051340373 on OpenAlexvenueno aff
Hisham M. Habib, Dalia Shaheen, Ghada O. Elsedfy

Bibliographic record

VenueInternational Journal of Clinical Pediatrics · 2012
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiological weaponArthritisProspective cohort studyDiseasePhysical examinationInternal medicineJuvenile rheumatoid arthritisRheumatoid factorJuvenileRheumatoid arthritisClinical phenotypePhysical therapySurgeryPhenotype
DOInot available

Abstract

fetched live from OpenAlex

Background: Juvenile rheumatoid arthritis (JRA) is the most common chronic rheumatic illness in children and is a significant cause of both short- and long-term disabilities. The aim of this study is to detect clinical, laboratory and radiological predictors of oligoarticular juvenile idiopathic arthritis (JIA), which could be used to identify children whose disease is likely to extend to a more severe phenotype.  Methods : This study included 40 oligoarticular JIA patients with no more than two years disease duration. Patients were divided into 2 groups after 6 months of illness into persistent and extended phenotypes. All patients were subjected to clinical, laboratory and conventional radiological assessment.  Results : In extended JIA patients there was a significant increase in age of patients, upper limb joint involvement, bilateral symmetrical arthritis, disease activity and functional outcome measures. Moreover, a significant elevation of ESR and CRP levels and RF positivity, as well as ANA negativity and radiological findings of joint inflammation were evident in extended phenotype.  Conclusion : Many clinical, laboratory and radiological predictors of conversion to extended oligoarticular JIA patients were close to charactertics of polyarticular form of the disease. doi:10.4021/ijcp29w

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)0.007
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.046
GPT teacher head0.406
Teacher spread0.360 · 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.

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

Citations1
Published2012
Admission routes1
Has abstractyes

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