Anti-HMGCR Autoantibodies in Juvenile Idiopathic Inflammatory Myopathies Identify a Rare but Clinically Important Subset of Patients
Bibliographic record
Abstract
OBJECTIVE: We aimed to establish the prevalence and clinical associations of anti-HMG-CoA-reductase (anti-HMGCR) in a large UK cohort with juvenile myositis. METHODS: There were 381 patients investigated for anti-HMGCR using ELISA. RESULTS: Anti-HMGCR autoantibodies were detected in 4 patients (1%). These children had no or minimal rash and significant muscle disease. Muscle biopsies were considered distinctive, with widespread variation in fiber size, necrotic fibers, and chronic inflammatory cell infiltrates; all had prolonged elevation of creatine kinase and all ultimately received biologic therapies. CONCLUSION: Anti-HMGCR in UK children with myositis are associated with severe disease that is poorly responsive to standard treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".