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Record W3010766827 · doi:10.1093/rheumatology/kez383

Treatment guidelines in psoriatic arthritis

2019· review· en· W3010766827 on OpenAlexaff
Alexis Ogdie, Laura C. Coates, Dafna D. Gladman

Bibliographic record

VenueLara D. Veeken · 2019
Typereview
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersNiilo Helanderin SäätiöCelgeneNational Institute on Handicapped ResearchNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchNational Institutes of HealthDepartment of Health and Aged Care, Australian GovernmentNational Institute for Health and Care ResearchGilead SciencesAmgenPfizerEli Lilly and Company
KeywordsPsoriatic arthritisMedicinePsoriasisClinical PracticeDiseaseArthritisAlternative medicineMusculoskeletal diseaseDermatologyPhysical therapyIntensive care medicineFamily medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

Psoriatic arthritis (PsA) is a complex inflammatory musculoskeletal and skin disease. The treatment of PsA has changed substantially over the past 10 years. Clinical practice guidelines are developed to help busy clinicians rapidly integrate evolving knowledge of therapeutic management into practice. In this review, we compare PsA treatment recommendations or guidelines developed by one national organization [ACR and National Psoriasis Foundation (NPF) in 2018], one regional organization (EULAR in 2015), and one international organization (the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis in 2015). We examine the development of guidelines in PsA more broadly and examine similarities and differences in the three sets of recommendations.

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)0.017
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.085
GPT teacher head0.378
Teacher spread0.293 · 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".

Quick stats

Citations175
Published2019
Admission routes1
Has abstractyes

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