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Enthesitis: A hallmark of psoriatic arthritis

2018· review· en· W2782126098 on OpenAlexaff
Gurjit S. Kaeley, Lihi Eder, Sibel Zehra Aydın, Marwin Gutiérrez, Catherine Bakewell

Bibliographic record

VenueSeminars in Arthritis and Rheumatism · 2018
Typereview
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of OttawaOttawa HospitalUniversity of TorontoWomen's College Hospital
FundersNovartis Pharmaceuticals Corporation
KeywordsEnthesitisMedicinePsoriatic arthritisEnthesisAnkylosing spondylitisSpondyloarthropathyDactylitisMagnetic resonance imagingRadiologyDermatologyPsoriasisPathologyInternal medicineTendon

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the growing importance of enthesitis in patients with psoriatic arthritis (PsA) and discuss the advantages and disadvantages of clinical and imaging methods currently used to assess enthesitis. METHODS: PubMed literature searches were conducted using the terms psoriatic arthritis, entheses, enthesitis, pathology, imaging, ultrasound, magnetic resonance imaging, clinical, and indices. Articles were deemed relevant if they provided insight into the pathology, monitoring, and/or diagnosis of enthesitis in PsA, or if they discussed clinical or imaging indices used to assess enthesitis. RESULTS: Enthesitis is an early manifestation of PsA that is associated with increased disease activity and reduced quality of life. A variety of clinical indices exist to assess enthesitis in PsA; however, the Leeds Enthesitis Index and Maastricht Ankylosing Spondylitis Enthesitis Score index have been the most frequently used indices in recent clinical trials. Limitations of these indices include an inability to discern structural involvement, risk of missing subclinical enthesitis, and lack of sensitivity in detecting enthesitis, especially in patients with central sensitization and/or pain amplification. Such limitations have led to the emergent importance of imaging techniques in the assessment of enthesitis. Although there have been recent advances in magnetic resonance imaging, ultrasound (US) appears to be the preferred method for detecting enthesitis because it allows for accurate assessment of the soft-tissue components of entheses and also for new bone formation. Hypoechogenicity, increased thickness of tendon insertion, calcifications, enthesophytes, erosions, and Doppler activity have been identified as important US characteristics of enthesitis. CONCLUSION: Enthesitis is thought to be integrally involved in the pathogenesis of PsA and is associated with worse prognostic outcomes in patients with PsA. A validated US index with entheses that are less confounded by mechanical factors and obesity would be the most effective measure of enthesitis in PsA. As imaging techniques continue to advance, our understanding of enthesitis and its involvement in PsA will also improve.

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)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.298
Teacher spread0.278 · 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
GenreReview

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".

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Citations189
Published2018
Admission routes1
Has abstractyes

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