Inclusion Body Myositis in a Patient with RNA Polymerase III Antibody-positive Systemic Sclerosis
Bibliographic record
Abstract
To the Editor: Inclusion body myositis (IBM) is the most commonly acquired myopathy in patients over 50 years of age and is classified along with polymyositis (PM) and dermatomyositis (DM) under idiopathic inflammatory myopathies1. These myopathies are characterized by chronic muscle weakness and muscle wasting with mononuclear cell infiltration into skeletal muscle. IBM is distinguished from PM and DM on the basis of both histopathologic and clinical features. The majority of patients with IBM are resistant to therapy2. Herein, we present a case of a patient with systemic sclerosis (SSc) who developed IBM 5 years after his initial diagnosis. A 60-year-old man was diagnosed with SSc with diffuse cutaneous scleroderma when he developed Raynaud phenomenon, joint pains, digital ulcers, and a modified Rodnan skin score (mRSS)3 of 22. He started treatment with parenteral methotrexate (MTX; 25 mg/week) for significant itching and redness. He developed esophageal reflux, but no known pulmonary or renal complications. His serum creatine phosphokinase (CPK) level was initially near normal (259 U/l, normal 32–204 U/l) without muscle weakness. His skin disease improved to mRSS 8, and … Address correspondence to Dr. V. Hsu, Director, Rutgers-Robert Wood Johnson Scleroderma Program, Adult Clinical Research Center, Acute Care Building, 3rd floor, 51 French St., New Brunswick, New Jersey 08903, USA. E-mail: hsuvm{at}rwjms.rutgers.edu
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| 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".