Is There an Advantage Over SF-36 with a Quality of Life Measure That Is Specific to Systemic Lupus Erythematosus?
Bibliographic record
Abstract
OBJECTIVE: To assess whether the Lupus Quality of Life (LupusQoL) questionnaire contributed additional information not obtained using the Medical Outcomes Study Short-Form 36 questionnaire (SF-36) in a cohort of patients with systemic lupus erythematosus (SLE). METHODS: Forty-one patients seen at a single center were followed at monthly intervals for 12 months. The LupusQoL and the SF-36 questionnaires were coadministered monthly. Disease activity was determined by the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) every 30 days. We determined the correlation of the 4 comparable domains of both questionnaires. For the 4 noncomparable domains of the LupusQoL we determined the correlation between each domain with the Physical Component Summary scores (PCS) and the Mental Component Summary scores (MCS) of the SF-36. The effect size (ES) and the standardized response mean (SRM) were used to compare the responsiveness of both questionnaires when a clinically significant change in disease activity occurred as determined by SLEDAI-2K. RESULTS: Three hundred seventy-six patient visits were recorded. There was a strong correlation between comparable domains in both questionnaires. For the 4 noncomparable domains of the LupusQoL, there was a correlation with the MCS and PCS of SF-36. The mean scores for comparable domains in both questionnaires were similar. Both questionnaires displayed responsiveness, as determined by ES and SRM among patients who flared and improved, but not among patients in remission, when compared to the previous visit. CONCLUSION: LupusQoL and SF-36 were equivalent in assessing quality of life over time in this group of patients. Both questionnaires are responsive measures of quality of life in patients with SLE flares and improvement.
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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 | 0.040 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".