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Record W4280527969 · doi:10.3899/jrheum.220263

Spondyloarthritis Among Patients With Uveitis: Can We Improve Referral Pathways?

2022· editorial· en· W4280527969 on OpenAlexaffvenueabout
Lihi Eder

Bibliographic record

VenueThe Journal of Rheumatology · 2022
Typeeditorial
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsMedicineRheumatologyReferralInternal medicineAnkylosing spondylitisUveitisSpondylitisBack painPhysical therapyFamily medicineOphthalmologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

Delays in diagnosis remain a major gap in the care of patients with axial spondyloarthritis (axSpA). Despite efforts to improve awareness among family physicians and nonrheumatologist specialists, the average duration from onset of symptoms to diagnosis of axSpA is approximately 8 years,1 which is one of the longest in rheumatology. Such delays in diagnosis are associated with late initiation of therapy and worse disease outcomes. Acute anterior uveitis (AAU), the most common extraarticular manifestation in SpA, affects 50% of patients and has been associated with longer delays in diagnosis.2 For many patients, AAU is the first encounter with a medical specialist, offering a unique opportunity for an early referral to rheumatology. Thus, studying the association between these 2 conditions could inform the development of more effective referral pathways from ophthalmology to rheumatology, ultimately improving early diagnosis of axSpA. In this edition of The Journal of Rheumatology, van Bentum et al describe the effect of an initiative aimed to increase awareness and referrals to rheumatology of patients with AAU and chronic back pain (CBP) seen in academic and community ophthalmology centers in Amsterdam.3 The referral criteria comprised an accepted definition of CBP (back pain of ≥ 3 months’ duration that started prior to the age of 45 years) among patients with new or recurrent AAU. All patients were assessed by a rheumatologist for clinical signs and symptoms of axSpA. Additionally, radiographic assessment of the sacroiliac joints was performed and HLA-B27 status determined in all patients. Magnetic resonance imaging (MRI) of the spine was performed only if deemed clinically necessary for diagnostic purposes. Among patients with AAU and CBP, the study found a prevalence of 23% (19 out of 81 patients) for previously undiagnosed axSpA, which was almost … Address correspondence to Dr. L. Eder, 76 Grenville Street, Women’s College Hospital, Toronto, ON M5S 1B2, Canada. Email: Lihi.eder{at}wchospital.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)0.005
metaresearch head score (Gemma)0.036
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0050.006
Open science0.0030.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0130.002

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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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

Citations2
Published2022
Admission routes3
Has abstractyes

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