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Record W4224021925 · doi:10.3899/jrheum.220163

Uveitis in Juvenile Psoriatic Arthritis: Still So Much To Learn

2022· letter· en· W4224021925 on OpenAlexaffvenueabout
Kamiar Mireskandari

Bibliographic record

VenueThe Journal of Rheumatology · 2022
Typeletter
Languageen
FieldMedicine
TopicOcular Diseases and Behçet’s Syndrome
Canadian institutionsSickKids FoundationUniversity of Toronto
Fundersnot available
KeywordsMedicineUveitisPsoriatic arthritisRheumatologyIncidence (geometry)CohortPsoriasisArthritisJuvenile rheumatoid arthritisEpidemiologyDermatologyPopulationPediatricsInternal medicineOphthalmology

Abstract

fetched live from OpenAlex

Psoriatic arthritis (PsA) is a systemic inflammatory disease that includes uveitis as one of its extraarticular associations. Studies involving predominantly adult patients report a significant association between the incidence of uveitis and psoriasis, the risk of which is greatest in patients with severe PsA.1,2 The literature on uveitis in children focuses mainly on risk factors for the more common forms of juvenile idiopathic arthritis (JIA) associated with uveitis and antinuclear antibody (ANA) positivity.3,4 Information on juvenile PsA–associated uveitis (JPsA-U) is scarce, with detailed ophthalmic findings restricted to small case series.5,6 In this issue of The Journal of Rheumatology, Walscheid et al reported the results of a large population-based cohort study on 1862 patients with JPsA.7 Cross-sectional data from the German National Pediatric Rheumatological Database (NPRD) were used to describe prevalence and risk factors for JPsA-U. The authors report that their cohort from 2002 to 2014 had documented uveitis in 6.6% (122/1862). Patients with JPsA-U were more frequently ANA positive (60.3% vs 37.0%, P < 0.001) and younger at JPsA onset (5.3 vs 9.3 yrs, P < 0.001) compared to patients without uveitis. Indeed, uveitis developed more frequently in those aged < 5 years at JPsA onset (17.3% [73/423] vs 3.8% [49/1306], P < 0.001). … Address correspondence to Dr. K. Mireskandari, Department of Ophthalmology and Vision Sciences, Hospital for Sick Children and University of Toronto, 555 University Avenue, Toronto, ON M5G 1X8, Canada. Email: kamiar.mireskandari{at}sickkids.ca.

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0050.011
Open science0.0020.001
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0030.002

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 head0.255
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2022
Admission routes3
Has abstractyes

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