Sociodemographic, disease, and symptom correlates of fatigue in systemic sclerosis: Evidence from a sample of 659 Canadian Scleroderma Research Group Registry patients
Bibliographic record
Abstract
OBJECTIVE: To assess fatigue levels and demographic, socioeconomic, disease, and psychosocial correlates of fatigue in patients with systemic sclerosis (SSc). METHODS: We conducted a cross-sectional, multicenter study of 659 patients with SSc from the Canadian Scleroderma Research Group Registry. Fatigue was assessed during annual Registry visits with the Short Form 36 (SF-36) health survey vitality subscale. Patients completed measures of depressive symptoms and pain and underwent clinical histories and medical examinations. Kendall's tau was used to assess bivariate association of sociodemographic, medical, and psychosocial variables with fatigue. Multivariable associations of demographic (step 1), socioeconomic (step 2), global disease (step 3), specific disease and lifestyle (step 4), and psychosocial (step 5) factors with fatigue were assessed using hierarchical multiple linear regression. RESULTS: The mean +/- SD score of the patients on the SF-36 vitality subscale was 45.6 +/- 10.8, substantially lower (indicating more fatigue) than the mean +/- SD score for the Canadian general population (65.8 +/- 18.0). In multivariate analysis, higher fatigue was significantly associated with the number of medical comorbidities (standardized beta = -0.11, P = 0.004), breathing problems (standardized beta = -0.23, P < 0.001), the number of gastrointestinal (GI) symptoms (standardized beta = -0.27, P < 0.001), and current smoking (standardized beta = -0.08, P = 0.018). As a group, specific symptom and lifestyle variables predicted the most incremental variance in fatigue (R(2) = 21.6%, P < 0.001), despite being added to the model after demographic, socioeconomic, and global disease duration/severity indicators. Symptoms of depression (beta = -0.42) and pain (beta = -0.21) were also independently associated with fatigue (P < 0.001). CONCLUSION: High levels of fatigue are common in patients with SSc and are independently associated with clinical variables, including number of comorbidities, breathing problems, GI symptoms, and smoking.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".