Musculoskeletal symptoms in systemic lupus erythematosus patients and their impact on health-related quality of life
Bibliographic record
Abstract
OBJECTIVES: To evaluate the musculoskeletal (MSK) symptoms experienced by SLE patients and determine how those symptoms relate to their health-related quality of life (HRQoL). MATERIALS AND METHODS: This is a cross-sectional study that was carried out on 103 adult SLE patients. sociodemographic, clinical, and therapeutic data were recruited. They were asked to complete the following: Nordic Musculoskeletal, Short-Form McGill Pain, and Lupus QoL Questionnaires. RESULTS: The mean age was 30.81 ± 9.44 years. There was a total of 86 females and 17 males (F: M:5:1). Almost all the patients reported MSK symptoms (96.1%). The maximum number of patients reported pain in the right and left wrist and hand (64.1%, 63.1%, respectively). One-fourth (25.2%) described at least five bodily sites of MSK symptoms, while 70.9% had more than five sites of MSK symptoms. Most of the patients described the pain as discomforting (40.8%). Patients with MSK symptoms scored significantly worse in all domains. In addition, the QoL scores of patients with more than 5 body sites of MSK symptoms were significantly lower than those of patients with fewer than 5 sites of MSK symptoms. CONCLUSION: SLE patients have a high MSK burden, and MSK symptoms have a negative impact on HRQoL in these patients.
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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 | 0.001 | 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".