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Record W4401219291 · doi:10.3899/jrheum.2024-0593

GRAPPA 2023 Debate: Is Psoriatic Disease Really a Primary Enthesitis That Drives Joint Synovitis? The Enthesitis Hypothesis 25 Years On

2024· article· en· W4401219291 on OpenAlexvenueno aff
Dennis McGonagle, Kerem Abacar, Bruce Kirkham

Bibliographic record

VenueThe Journal of Rheumatology · 2024
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
FundersPfizerEli Lilly and CompanyAmgen
KeywordsEnthesitisEnthesisMedicineDactylitisPsoriatic arthritisSynovitisPsoriasisDermatologyEnthesopathyArthritisTenosynovitisPathologyInternal medicineSurgeryTendon

Abstract

fetched live from OpenAlex

The enthesitis hypothesis posits that enthesitis is a primary lesion and that inflammation at the enthesis initiates the musculoskeletal symptoms of psoriatic arthritis (PsA) and spondyloarthropathies (SpA). The hypothesis suggested that inflamed entheseal tissue near the synovium could trigger cytokine-mediated synovitis, that enthesis bone anchorage could explain osteitis, and that the location of entheses at the soft tissue interface could explain dactylitis. Advances in imaging techniques that allow better visualization of enthesitis lesions and the development of animal models have allowed evolution of the concept of enthesitis as a central mechanistic driver of musculoskeletal symptoms in PsA and SpA. A debate between Drs. Dennis McGonagle and Bruce Kirkham at the Group for Research on Psoriasis and Psoriatic Arthritis (GRAPPA) 2023 annual meeting discussed the data supporting and refuting this hypothesis in PsA and SpA, respectively. The major points of this debate are summarized in this article.

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)0.013
metaresearch head score (Gemma)0.028
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0130.021
Insufficient payload (model declined to judge)0.0070.005

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 head0.019
GPT teacher head0.244
Teacher spread0.225 · 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
GenreCommentary

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

Citations6
Published2024
Admission routes1
Has abstractyes

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