Polymyositis: does it really exist as a distinct clinical subset?
Bibliographic record
Abstract
PURPOSE OF REVIEW: To summarize information on polymyositis; diagnosis, definitions, published data and opinions. RECENT FINDINGS: Polymyositis originally referred to inflammatory muscle diseases presenting with muscle weakness and inflammatory cell infiltrates on muscle tissue visible by microscopy. Over time and with improved technology to immunophenotype infiltrating inflammatory cells and characterize muscle fibres, the meaning of polymyositis changed and became more specific. There is ongoing controversy over the term polymyositis, with proponents for a strict definition based on histopathological and immunohistochemical features on muscle biopsies whereas others advocate for a broader clinical and histopathological phenotype. Over the past decades, the discovery of several myositis-specific autoantibodies together with distinct histopathological features have enabled the identification of new subsets previously labelled as polymyositis notably the antisynthetase syndrome and the immune-mediated necrotizing myopathies thus reducing the number of patients classified as polymyositis. SUMMARY: There are still a small number of patients among the idiopathic inflammatory myopathies that can be classified as polymyositis as discussed in this review but the entity is now considered relatively rare.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".