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Record W1990088027 · doi:10.3899/jrheum.150257

Screening for Psoriatic Arthritis in People with Psoriasis

2015· editorial· en· W1990088027 on OpenAlexvenueno aff
Philip Helliwell

Bibliographic record

VenueThe Journal of Rheumatology · 2015
Typeeditorial
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsnot available
Fundersnot available
KeywordsPsoriasisMedicinePsoriatic arthritisDermatologySubclinical infectionAsymptomaticRheumatologyArthritisDiseaseEnthesopathyInternal medicine

Abstract

fetched live from OpenAlex

Psoriasis is the best biomarker for disease that we have in rheumatology. Seventy percent of people who develop psoriatic arthritis (PsA) will have psoriasis at presentation. The psoriasis may be “hidden” and may deceive the assessing physician, but generally the skin disease is known to the patient, and is obvious to the observer. So, given this strong association, can we predict those people with psoriasis who will go on to develop PsA? Some time ago it was reported that certain phenotypes of psoriasis are associated with the development of psoriatic arthritis: these include psoriasis of the nails, psoriasis of the scalp, and flexural psoriasis1. It is of note that these are all areas that are “hidden” to the examining physician — unless we look, we will never see. Refer to the article of Gorter, et al, who “sent” patients with hidden psoriasis to rheumatologists and fewer than 40% examined these hidden areas. And let us not forget the subclinical disease2. Gisondi, et al were the first to demonstrate subclinical enthesopathy in patients with psoriasis3, and these abnormalities have also been found in other disorders, such as inflammatory bowel disease. However, the exact significance of these abnormalities remains unclear — a well-controlled longitudinal study in asymptomatic patients with psoriasis with (and without) such abnormalities is required to answer that question. Of more importance perhaps is the number of patients who have already developed PsA but remain undiagnosed. Community surveys put this figure at about 15%, and the equivalent figure in secondary care is around 30%4,5. This is, on the face of it, astonishing, and leads to speculation that this is not major disease but minor forms of enthesitis and oligoarthritis that are not affecting the patient. Sadly, this is not the … Address correspondence to Dr. P.S. Helliwell, NIHR Leeds Musculoskeletal Biomedical Research Unit, Leeds Institute for Rheumatology and Musculoskeletal Medicine, Chapel Allerton Hospital, Chapel Town Road, Leeds, LS7 4SA, UK. E-mail: p.helliwell{at}leeds.ac.uk.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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