Central Sensitization in Psoriatic Arthritis: Relationship With Composite Measures of Disease Activity, Functional Disability, and Health-Related Quality of Life
Bibliographic record
Abstract
Objective To investigate the prevalence of central sensitization (CS) in patients with psoriatic arthritis (PsA) and its association with disease activity and patient-reported outcome measures. Methods This cross-sectional study included adults with PsA without coexisting fibromyalgia (FM). Patients underwent a clinimetric assessment to collect variables regarding disease activity, quality of life (QOL), functional ability, impact of disease, and CS. Spearman ρ was used to examine the relationship between CS Inventory (CSI) scores and other variables. A multivariate analysis was performed to determine the independent contribution of each variable to the 12-item Psoriatic Arthritis Impact of Disease (PsAID-12) score. Results One hundred fifty-seven patients were enrolled. Of them, 45.2% scored a CSI ≥ 40, indicating a high probability of CS. Significant correlations were found between CSI and disease activity, as evaluated by Disease Activity in Psoriatic Arthritis score and Psoriatic Arthritis Disease Activity Score (ρ 0.587 and ρ 0.573, respectively), between CSI and the Health Assessment Questionnaire (ρ 0.607), and between CSI and the 36-item Short Form Health Survey physical component summary and mental component summary scores (ρ −0.405 and ρ −0.483, respectively). In multivariate analysis, CSI score was the principal independent variable (P< 0.001) contributing to PsAID-12 score. Conclusion Patients with PsA with symptoms of CS had higher disease activity, worse functional ability, and worse QOL. The presence of CS is the major contributor in the impact of disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".