Work disability in systemic lupus erythematosus is prevalent and associated with socio-demographic and disease related factors
Bibliographic record
Abstract
Our objectives were to examine the prevalence of work disability (WD) and factors associated with job loss in systemic lupus erythematosus (SLE) in a large, multi-centered Canadian sample to determine the current prevalence of WD and identify the contribution of disease activity, damage, and co-morbidities with respect to WD in this cohort. Cross-sectional data on WD status from the 1000 Canadian Faces of Lupus database (a multi-center multi-ethnic cohort of SLE patients) along with clinical measures (number of ACR criteria ever, SLICC Damage Index, SLAM, SLEDAI, SF-36 and Charlson Co-morbidity Index scores), demographic features (age, sex, high school education, household income, marital status, disease duration, employment status) and co-morbidities (including self-reported fibromyalgia, arthralgias, depression and fatigue) were used in bivariate and logistic regression analyses. The 1137 SLE patients had a mean age of 50 years (SE 0.75) and mean disease duration was 18 years (SE 0.70); 19.09% were work disabled and 49.78% were employed. Those with WD were more likely than non-WD SLE patients to have: a higher number of ACR criteria for SLE; not completed high school; older age; single marital status; a lower household income; longer disease duration; higher SLICC Damage Index and SLAM scores; lower SF-36 PCS and SF-36 MCS scores; less vigorous activity per week; and fibromyalgia, arthralgias, fatigue and depression (p < 0.05). This contemporary rate of WD is lower than many past reports. Socio-demographic factors, co-morbidities (fibromyalgia and fatigue) and disease related factors were strongly associated with WD. We cannot determine cause and effect as the study was cross-sectional.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".