Longitudinal Analysis of Fatigue in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To describe the longitudinal course of fatigue in psoriatic arthritis (PsA). METHODS: Our study included 390 patients who attended the University of Toronto Psoriatic Arthritis Clinic between 1998 and 2006 and who completed 2 or more administrations of the modified Fatigue Severity Scale (mFSS) at yearly intervals. Clinical data were used that corresponded to visits in which mFSS was administered. We used linear mixed effects models to examine the relationships of disease-related and nondisease-related variables with mFSS scores across multiple clinic visits, and linear regression models to investigate the association between change in mFSS scores (DeltamFSS) and changes in covariates between visits. RESULTS: Clinical measures of disease activity were related to fatigue over time; however, these relationships disappeared in the context of patient-reported physical disability and pain. Patient-reported measures of physical disability, pain, and psychological distress were most closely related to higher mFSS scores (greater fatigue) across clinic assessments. Fatigue was found to vary over time, at least when assessed at yearly intervals. In general, measures of clinical and functional status at the current visit were more predictive of DeltamFSS in between previous and current visits than change scores in these measures between visits. Comorbid fibromyalgia or hypertension were also associated with greater fatigue across multiple visits and with change in fatigue between visits. CONCLUSION: A combination of factors is associated with fatigue in PsA. The full effect of comorbidities on fatigue warrants further study to better understand the effective management of fatigue in PsA.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".