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Record W2129091021 · doi:10.1586/1744666x.2014.905741

Predictors for clinical outcome in psoriatic arthritis – what have we learned from cohort studies?

2014· review· en· W2129091021 on OpenAlexaff
Lihi Eder, Dafna D. Gladman

Bibliographic record

VenueExpert Review of Clinical Immunology · 2014
Typereview
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsMedicineOligoarthritisPsoriatic arthritisPolyarthritisCohortRheumatoid arthritisDiseaseArthritisPhysical therapyPsoriasisCohort studyInternal medicineImmunology

Abstract

fetched live from OpenAlex

Psoriatic Arthritis (PsA) is a heterogeneous disease that ranges from a mild form of oligoarthritis to destructive polyarthritis. The burden of disease can be severe and comparable to that of rheumatoid arthritis. Identifying predictors of worse outcome may improve the understanding of the underlying mechanisms of the disease and may guide therapeutic management at the individual level. Longitudinal cohort studies identified predictors of long-term outcomes such as joint damage, physical function and work disability in PsA. In general, male gender and lower burden of inflammation at presentation predict better outcome while a delay in diagnosis, disability and joint damage are associated with worse long term outcomes. Several HLA alleles also identify patients who are likely to sustain joint damage.

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)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.282
GPT teacher head0.554
Teacher spread0.272 · 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.

Study designSystematic review
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

Citations25
Published2014
Admission routes1
Has abstractyes

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