The Effect of the Presence of Fibromyalgia on Common Clinical Disease Activity Indices in Patients with Psoriatic Arthritis: A Cross-sectional Study
Bibliographic record
Abstract
OBJECTIVE: To study the effect of the presence of fibromyalgia (FM) on common clinical disease activity indices in patients with psoriatic arthritis (PsA). METHODS: Seventy-three consecutive outpatients with PsA (mean age 51.7 yrs; 42 females, 57.5%) were enrolled in a prospective cross-sectional study. FM was determined according to American College of Rheumatism criteria (2010 and 1990). All patients underwent clinical evaluation of disease activity and completed the Health Assessment Questionnaire (HAQ), the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Dermatology Life Quality Index, and the Leeds Enthesitis Index (LEI). Disease activity was evaluated using the Composite Psoriatic Disease Activity Index (CPDAI), minimal disease activity (MDA), and the Disease Activity Index for Psoriatic Arthritis (DAPSA) scores. RESULTS: The overall prevalence of FM was 17.8% (13 patients), and all but 1 were women (12 patients, 92.3%, p = 0.005). CPDAI and DAPSA scores were significantly higher in patients with coexisting PsA and FM (9.23 ± 1.92 and 27.53 ± 19.23, respectively) than in patients with PsA only (4.25 ± 3.14 and 12.82 ± 12.71, respectively; p < 0.001 and p = 0.003). None of the patients with FM + PsA met the criteria for MDA, whereas 26 PsA-only patients did (43.3%, p = 0.003). HAQ, BASDAI, and LEI scores were significantly worse in patients with PsA and associated FM. CONCLUSION: Coexisting FM is related to worse scores on all tested measures in patients with PsA. Its influence should be taken into consideration in the treatment algorithm to avoid unnecessary upgrading of treatment.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".