Myositis-Specific Antibodies and Myositis-Associated Antibodies in Patients With Idiopathic Inflammatory Myopathies From the PANLAR Myositis Study Group
Bibliographic record
Abstract
BACKGROUND: Dermatomyositis (DM) and polymyositis (PM) are forms of idiopathic inflammatory myopathies (IIMs), which are associated with the production of autoantibodies that are useful in the diagnosis and prognosis of the disease. OBJECTIVE: The aim of this study was to determine the frequency of antinuclear autoantibodies (ANAs), myositis-specific autoantibodies (MSAs), and myositis-associated autoantibodies (MAAs) in 6 Latin American countries. METHODS: Two hundred ten patients with IIM were included in this cross-sectional study from 2014 to 2017: 112 from Mexico, 46 from Colombia, 20 from Peru, 16 from the Dominican Republic, 10 from Argentina, and 6 from Guatemala. Antinuclear autoantibodies were detected by indirect immunofluorescence on HEp-2 cells. MSAs and MAAs were tested by a line immunoassay method. Mann-Whitney U and χ2 tests were used for statistical analysis. RESULTS: Of the 210 IIM patients, 139 (66.2%) had DM, 59 (28%) PM, and 12 (5.7%) juvenile DM. The mean age was 43.5 (6-79 years); 158 (75.2%) were female, and 52 (24.8%) were male. The overall frequency of ANA was 60%. The most frequent patterns were fine speckled (AC-4) (78.3%) and cytoplasmic (AC-19) (6.45%). The most frequent MSA were anti-Mi-2 (38.5%) and anti-Jo-1 (11.9%). Anti-Mi-2 was more frequent in patients from Colombia (40.1%). The MAA more frequent were anti-Ro-52/TRIM21 (17.6%) and anti-PM-Scl75 (7.5%). CONCLUSIONS: This is the first study of ANA, MSA, and MAA in patients from 6 countries from the Panamerican League against Rheumatism myositis study group. We observed a general prevalence of 60% of ANA. In relation to MSA and MAA, anti-Mi-2 was the more frequent (38.5%).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".