Organ manifestations influence differently the responsiveness of 2 lupus disease activity measures, according to patients' or physicians' evaluations of recent lupus activity.
Bibliographic record
Abstract
OBJECTIVE: To determine (1) which organ system manifestations contribute to the overall responsiveness of the Systemic Lupus Activity Measure (SLAM, revised 1991 with minor modifications as SLAM-R) and the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI); and (2) whether responsive items differ for physicians and patients. METHODS: Blinded data were obtained from repeated visits of 76 patients in the Study of Methotrexate in Lupus Erythematosus. At each visit, physicians and patients reported improvement, no change, or deterioration, and physicians then completed SLAM-R and SLEDAI. Items in SLAM-R and SLEDAI were grouped by organ system. The generalized estimating equations approach was used to measure associations between change in organ system activity and physician or patient perception of change in overall disease activity. The outcomes assessed, in separate analyses, were improvement and deterioration from the previous visit. RESULTS: Seventy-six patients contributed a total of 471 observations. The strongest correlates of physician-reported improvement were decreased constitutional, gastrointestinal (GI), and musculoskeletal involvement (components of SLAM-R), and decreased musculoskeletal (MSK) and central nervous system involvement (SLEDAI). Improvement reported by patients was most strongly associated with decreases in erythrocyte sedimentation rate and MSK and reticuloendothelial activity (SLAM-R), and in MSK activity (SLEDAI). Increased integument and MSK subscores (SLAM-R) and serosal and MSK subscores (SLEDAI) were associated with overall deterioration reported by physicians. Patient-reported deterioration was associated with increased GI subscores (SLAM-R) and with no changes in organ system involvement in SLEDAI. CONCLUSION: Organ systems associated with reported change in overall SLE activity differed between SLAM-R and SLEDAI, between patients and physicians, and between each direction of change.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".