Effects of obesity on health-related quality of life in juvenile-onset systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: This study evaluated the effects of obesity on health-related quality of life (HRQOL) measures in juvenile-onset systemic lupus erythematosus (jSLE). METHODS: Obesity was defined as a body mass index (BMI) ≥ 95 th percentile according to the Sex-specific Center for Disease Control BMI-For-Age Charts and determined in a multicenter cohort of jSLE patients. In this secondary analysis, the domain and summary scores of the Pediatric Quality of Life (PedsQL) Inventory and the Child Health Questionnaire (CHQ) of obese jSLE patients were compared to those of non-obese jSLE patients as well as historical obese and non-obese healthy controls. Mixed-effects modeling was performed to evaluate the relationship between obesity and HRQOL measures. RESULTS: Among the 202 jSLE patients, 25% (n = 51) were obese. Obesity had a significant negative impact on HRQOL in jSLE, even after adjusting for differences in current corticosteroid use, disease activity, disease damage, gender and race between groups. Obese jSLE patients had lower physical functioning compared to non-obese jSLE patients, and to non-obese and obese healthy controls. Compared to their non-obese counterparts, obese jSLE patients also had worse school functioning, more pain, worse social functioning and emotional functioning. Parents of obese jSLE patients worry more. The CHQ scores for obese jSLE patients were also worse compared to non-obese jSLE patients in several other domains. CONCLUSION: Our study demonstrates the detrimental effects of obesity on patient-reported outcomes in jSLE. This supports the importance of weight management for the therapeutic plan of jSLE.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".