Pain in autoimmune inflammatory myopathies: a scoping review
Bibliographic record
Abstract
BACKGROUND: Pain is considered a priority for research by adult patients with autoimmune inflammatory myopathy (AIM) and their families. Our aim was to review the literature for studies reporting on pain in adult AIM and to summarise their findings. METHODS: A scoping review was conducted searching for studies in PubMed and MEDLINE including more than five adult patients with AIM and assessing pain using a patient-reported outcome measure. Study population characteristics, pain measurement and clinical correlates of pain were extracted using a standardised protocol. RESULTS: The search strategy identified 2831 studies with 33 meeting inclusion criteria. Most studies used visual analogue scales (n=14) and/or the Medical Outcomes Study 36-Item Short Form Bodily Pain Scale (n=17). Frequency of pain and/or myalgias ranged from 64% to 100%. Subjects with AIM had significantly more pain than the general population and comparable pain to other chronic rheumatic diseases. Insufficient results were available to identify significant clinical correlates of pain in AIM. CONCLUSION: This review suggests that the burden of pain in AIM is considerable. Still, due to the heterogeneity and low quality of the evidence, significant knowledge gaps persist. Studies are needed to characterise pain trajectories of patients with AIM.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".