Health-related quality of life and its related factors in patients with systemic lupus erythematosus in southwest Iran: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Quality of life (QoL) is an important measure in health assessment. It is impacted by unclear factors in Systemic Lupus Erythematosus (SLE) patients. The study aimed to investigate the factors related to QoL in SLE patients. METHODS: This cross-sectional study was performed on 140 (136 women and four men) Iranian SLE patients of Hafiz Hospital from June 2019 to August 2020. The Lupus Erythematosus Quality of Life Questionnaire (LEQoL) was used to evaluate the quality of life. The patients were evaluated with this questionnaire for four weeks in eight dimensions health, emotional health, body image, pain, planning, intimate relationships, and the burden of others. Related factors of LEQoL were evaluated using multivariable linear regression. RESULTS: The mean age was 34.09(8.96) years. The total mean QoL Score was 65.5 ± 22.4. The multivariable analysis showed that duration of disease (β:-1.12, 95% CI:-1.44 to -0.79, P:0.001), physical activity(β:-12.99, 95% CI:-19.2 to -6.13, P:0.001), kidney involvement (β:-9.2, 95% CI:-16.61 to -2.79, P:0.03) and skin involvement(β:-8.7, 95% CI:-17.2 to -0.2, P:0.031) were significantly related to the total mean QOL score of SLE patients. CONCLUSION: The QoL of Iranian patients with SLE was low. Age and gender can be related to the decrease in the QoL of patients with SLE. Increasing the disease duration, physical activity, kidney involvement, and skin involvement can be related to the decrease in the QOL of Iranian patients with SLE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".