Dimensions of fatigue in systemic lupus erythematosus: relationship to disease status and behavioral and psychosocial factors.
Bibliographic record
Abstract
OBJECTIVE: To characterize the experience of fatigue in patients with systemic lupus erythematosus (SLE) using a multidimensional assessment and to delineate contributors to physical and mental dimensions of fatigue. METHODS: Fatigue in 130 women with SLE was assessed using the Multidimensional Fatigue Inventory (MFI-20). Participants completed standardized questionnaires assessing sleep quality, depressed mood, social support, and leisure-time physical activity. A clinical examination determined disease activity, cumulative damage, and whether patients fulfilled American College of Rheumatology criteria for fibromyalgia (FM). A series of hierarchical multiple regressions were computed to identify contributors to physical and mental fatigue. RESULTS: Patients scored high on all 5 MFI-20 fatigue dimensions, with general fatigue and physical fatigue having the highest scores. A hierarchical multiple regression showed that greater disease damage and disease activity, the presence of FM, depressed mood, sleep disturbance, and less participation in leisure-time physical activity contributed to higher physical fatigue scores. The results of the second model found depressed mood to be the strongest determinant of mental fatigue. Disease-related variables were not associated with mental fatigue. CONCLUSION: Fatigue in SLE is multidimensional and multidetermined, with physical and mental aspects likely having different etiologies. A multidimensional assessment of fatigue in SLE is needed to tailor and optimize interventions aimed at alleviating fatigue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".