The LupusQoL and Associations with Demographics and Clinical Measurements in Patients with Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Having developed and validated a disease-specific health-related quality of life (HRQOL) measure for patients with systemic lupus erythematosus (SLE), the LupusQoL, we determined its relationship to demographic and clinical measurements in a group of patients with SLE. METHODS: A group of 322 outpatients completed the LupusQoL. Demographic (age, sex, marital status, ethnicity) and clinical variables (disease duration, disease activity, damage) were recorded. Associations between the 8 LupusQoL domains and age, disease duration, disease activity, and damage were explored using Spearman's correlation coefficients. Differences in LupusQoL scores were examined for sex and marital status using the Mann-Whitney U test. Ethnic groups were compared using ANOVA. RESULTS: All domains of LupusQoL were impaired, with fatigue (56.3) being the worst affected and body image (80.0) the least. The correlations between the LupusQoL domain scores and age (r = -0.01 to -0.22) and disease duration (r = 0 to 0.16) were absent or weak. Similarly, there were no significant differences in the LupusQoL scores regarding sex, marital status, or the 3 main ethnic groups (Black-Caribbean, Asian, White). Although there were statistically significant correlations between the scores of the LupusQoL domains and some scores of the British Isles Lupus Assessment Group index (r = -0.22 to 0.09) and the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (r = -0.29 to 0.21), these were weak. CONCLUSION: HRQOL was impaired in this cohort of outpatients with SLE as assessed by the validated lupus-specific LupusQoL. There were no clinically important associations between the 8 domains of the LupusQoL and clinical or demographic variables in this group of patients. Thus, the LupusQoL is a relatively independent outcome measure in patients with SLE.
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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 | 0.004 | 0.001 |
| 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) | 0.000 | 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".