Sex Differences in Quality of Life in Patients With Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Systemic lupus erythematosus (SLE) predominantly affects women. Clinical phenotype and outcomes in SLE may vary by sex and are further complicated by unique concerns that are dependent upon sex-defined roles. We aimed to describe sex differences in disease-specific quality of life (QoL) assessment scores using the Lupus Patient-Reported Outcome (LupusPRO) tool in a large international study. METHODS: Cross-sectional data from 1,803 patients with SLE on demographics, self-identified sex status, LupusPRO, and disease activity were analyzed. The LupusPRO tool has 2 constructs: health-related QoL (HRQoL) and non-HRQoL. Disease activity and damage were evaluated using the Safety of Estrogens in Lupus Erythematosus National Assessment version of the Systemic Lupus Erythematosus Disease Activity Index and the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index, respectively. Nonparametric tests were used to compare QoL and disease activity by sex. RESULTS: A total of 122 men and 1,681 women with SLE participated. The mean age was similar by sex, but the damage scores were greater among men. Men fared worse on the non-HRQoL social support domain than women (P = 0.02). When comparing disease and QoL among men and women ages ≤45 years, men were found to have greater damage and worse social support than women. However, women fared significantly worse on lupus symptoms, cognition, and procreation domains with trends for worse functioning on physical health and pain-vitality domains. CONCLUSION: In the largest study of a diverse group of SLE patients, utilizing a disease-specific QoL tool, sex differences in QoL were observed on both HRQoL and non-HRQoL constructs. Although men performed worse in the social support domain, women (especially those in the reproductive age group) fared worse in other domains. These observations may assist physicians in appropriately addressing QoL issues in a sex-focused manner.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".