Work Disability in Scleroderma is Greater than in Rheumatoid Arthritis and is Predicted by High HAQ Scores
Bibliographic record
Abstract
OBJECTIVES: To estimate the frequency of work disability (WD) in a cohort of patients with Systemic Sclerosis (SSc) vs an internal control group of patients with rheumatoid arthritis (RA) with a known high frequency of WD; and to investigate the association between WD and other factors including Health Assessment Questionnaire Disability Index (HAQ-DI) scores, HAQ pain, age, sex, disease duration and education level. METHODS: Cross-sectional data on WD status were obtained from a questionnaire sent to all SSc (n = 35 limited [lcSSc], 26 diffuse [dcSSc]) and a subset of RA patients (n=104) from a rheumatology practice. WD data, HAQ-DI scores, and demographic/clinical features (age, sex, high school education, disease duration and SSc disease subtype [dcSSc vs lcSSc]) were recorded. RESULTS: The proportion with WD was 0.56 in SSc (95% CI: 0.43-0.68) vs 0.35 in RA (95% CI: 0.25-0.44), p= 0.009. HAQ-DI scores were significantly higher in work-disabled SSc and RA patients vs those who were employed (p=0.0001, and p <0.0001). Multivariate logistic regression analysis demonstrated that higher HAQ-DI scores (β=1.78, p <0.001), disease type (dcSSc, lcSSc, RA) (β=1.32 for dcSSc, p=0.032), and self-reported disease duration (β=0.04, p=0.042) were significantly associated with WD (R(2)=0.311). Adding a work-related factor (self-reported physically demanding work) improved the regression model (R(2)=0.346) and strengthened the HAQ-DI (β=1.86, p <0.001) and lcSSc (β=1.24, p=0.024) coefficients. CONCLUSION: The frequency of WD in SSc was high and was greater than in RA. SSc (and dcSSc) had significantly more WD than RA. The HAQ-DI was strongly associated with WD in SSc.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".