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Record W2592181034 · doi:10.3899/jrheum.161544

Composite Measures of Impact and Activity in Psoriatic Arthritis: A Conceptual Framework

2017· letter· en· W2592181034 on OpenAlexvenueno aff
William Tillett

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typeletter
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsoriatic arthritisOligoarthritisDiseasePolyarthritisPhysical therapyRheumatologyClinical trialArthritisInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Considerable progress has been made in recent years to improve outcome measurement in psoriatic arthritis (PsA). The Outcome Measures in Rheumatology (OMERACT) initiative has recently endorsed an updated “core outcome set” of disease domains that should be measured in clinical trials and observational studies of PsA1. There are also a range of clinical, patient-reported, and composite clinical measures of disease that have been validated for use in PsA2. In this setting the Psoriatic Arthritis Impact of Disease (PsAID) measure3 has been developed, and a validation study of the PsAID in an Italian cohort of patients has been undertaken. Results of that study are published in this issue of The Journal . Which measures should clinicians use for the assessment of PsA and where does the PsAID fit into the existing collection of measurement tools? It is first helpful to remind ourselves of what should be measured to adequately identify the clinical spectrum of PsA. It is well established that PsA is a heterogeneous disease affecting multiple disease domains including joints, skin, entheses, spine, nails, eyes, and axial skeleton4. Further, we know the disease phenotype varies (polyarthritis, oligoarthritis, spondyloarthritis, mutilans, and distal interphalangeal arthritis), and patients can transition between phenotype during disease course5,6. It is, therefore, a challenge to assess this heterogeneous disease and, historically, assessing only peripheral articular disease has underrepresented the totality of disease burden, thus leading to an incomplete understanding of treatment effect on extraarticular domains of disease. There have, therefore, been efforts to develop a composite disease activity measure that identified the wide range of PsA disease expression: and several measures are now available. These candidate composite measures include, but are not limited to, the Disease Activity in Psoriatic Arthritis (DAPSA)7, the Psoriatic Arthritis … Address correspondence to Dr. W. Tillett, Royal National Hospital for Rheumatic Diseases, Upper Borough Walls, Bath, BA1 1RL, UK. E-mail: w.tillett{at}nhs.net

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)0.039
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.038
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0110.008
Science and technology studies0.0020.012
Scholarly communication0.0070.008
Open science0.0060.005
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.304
Teacher spread0.275 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations7
Published2017
Admission routes1
Has abstractyes

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