Examining Self‐Reported Executive Function and Its Relationship to Patient‐Reported Outcomes and Disease‐Related Factors in Youth With Childhood‐Onset Lupus: A Cross‐Sectional Study
Bibliographic record
Abstract
OBJECTIVE: Up to 60% of youth with childhood-onset systemic lupus erythematosus (cSLE) experience cognitive dysfunction, impacting their quality of life and medication adherence. This study explored self-reported executive function (EF) and its links to patient-reported outcomes and disease-related factors in cSLE. METHODS: This cross-sectional study compared patients aged 10 to 17 years with cSLE to age- and sex-matched controls. The Behavior Rating Inventory of Executive Function Self-Report Global Executive Composite (GEC) T score measured daily EF activities, whereas Patient-Reported Outcomes Measurement Information System (PROMIS) questionnaires assessed pain, sleep, fatigue, anxiety, and depression. Group differences in GEC and correlations with PROMIS scores were analyzed. For patients with cSLE, hierarchical regression evaluated GEC variance explained by income, PROMIS scores, and disease-related factors (activity, damage, and glucocorticoid use). RESULTS: We recruited 94 participants, including 52 patients with cSLE and 42 controls. The analysis revealed no group difference in GEC T scores. In the cSLE group, worse depression and sleep disturbance correlated with worse GEC T scores, whereas pain interference and fatigue correlated with GEC in both groups. The hierarchical regression model explained 30% (P = 0.003) of EF variability in cSLE. PROMIS measures accounted for 14% (P = 0.013) of EF variability when controlling for household income. Disease-related factors contributed an additional 14% of EF variability, with higher disease activity and lower glucocorticoid use associated with worse GEC T scores. CONCLUSION: Self-reported EF was similar in patients with cSLE and control patients but correlated uniquely with depression, sleep disturbance, disease activity, and glucocorticoid use. Further research is needed to improve EF in cSLE.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".