Extent and characteristics of self-reported pain in patients with systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: Patients' own experiences of subjective symptoms are scarcely covered, and the objective of this study was to investigate the extent and characteristics of self-reported pain in patients with systemic lupus erythematosus (SLE). METHODS: This study comprised a cross-sectional design where 84 patients with SLE were asked to complete self-assessments: visual analogue scale of pain and the Short-Form McGill Pain Questionnaire. Medical assessments, including ESR, SLAM, SLEDAI, and SLICC, were also performed. RESULTS: Of the study population, 24% reported higher levels of SLE-related pain (≥40 mm on VAS). This group had a significantly shorter disease duration, higher ESR, and higher disease activity, according to the SLAM and SLEDAI, compared to the rest of the study population. This group mainly used the words "tender," "aching," and "burning" to describe moderate and severe pain, and they used a greater number of words to describe their pain. Of the patients with higher levels of pain, 70% reported their present pain as "distressing." The most common pain location for the whole patient population was the joints. Patients rated their disease activity significantly higher than physicians did. CONCLUSION: These findings expand the current knowledge of the extent of SLE-related pain and how patients perceive this pain. The results can contribute to affirmative, supportive and caring communication and especially highlight SLE-related pain in patients with a short disease duration and high disease activity.
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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 | 0.004 |
| 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 | 0.000 | 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".