Outcome clusters and their stability over 1 year in patients with SLE: self-reported and performance-based cognitive function, disease activity, mood and health-related quality of life
Bibliographic record
Abstract
OBJECTIVE: To determine if self-reported fatigue, anxiety, depression, cognitive difficulties, health-related quality of life, disease activity scores and neuropsychological battery (NB) cluster into distinct groups in patients with SLE based on symptom intensity and if they change at 1-year follow-up. METHODS: This is a retrospective analysis of consecutive consenting patients, followed at a single centre. Patients completed a comprehensive NB, the Beck Anxiety Inventory, Beck Depression Inventory, Fatigue Severity Scale, Short-Form Health Survey Physical Component Summary and Mental Component Summary scores and the Perceived Deficits Questionnaire. Disease activity was assessed by Systemic Lupus Erythematosus Disease Activity Index 2000. Ward's method was used for clustering and principal component analysis was used to visualise the number of clusters. Stability at 1 year was assessed with kappa statistic. RESULTS: had severe symptom intensity. At 1-year follow-up, 49% of patients remained in their baseline cluster. The mild cluster had the highest stability (77% of patients stayed in the same cluster), followed by the severe cluster (51%), and moderate cluster had the lowest stability (3%). A minority of patients from mild cluster moved to severe cluster (19%). In severe cluster, a larger number moved to moderate cluster (40%) and fewer to mild cluster (9%). CONCLUSION: Three distinct clusters of symptom intensity were documented in patients with SLE in association with cognitive function. There was a lower tendency for patients in the mild and severe clusters to move but not moderate cluster over the course of a year. This may demonstrate an opportunity for intervention to have moderate cluster patients move to mild cluster instead of moving to severe cluster. Further studies are necessary to assess factors that affect movement into moderate cluster.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".