Perfil de autoanticorpos e correlação clínica em um grupo de pacientes com esclerose sistêmica na região sul do Brasil
Bibliographic record
Abstract
OBJECTIVES: To assess the manifestations of systemic sclerosis (SSc), with an emphasis on the analysis of autoantibodies and their clinical correlations, in a population of patients followed up at the SSc Outpatient Clinics of the Hospital de Clínicas of the Universidade Federal do Paraná. METHODOLOGY: Cross-sectional study with 96 patients followed up at the SSc Outpatient Clinics of the hospital between September 2007 and September 2009. RESULTS: Most patients were of the female sex, in their forties or fifties, and the median time of disease was ten years. The limited cutaneous form of SSc was more prevalent. The analysis of the autoantibodies showed the association of anticentromere antibody (ACA) with the following: the limited form of SSc; more advanced age at the time of diagnosis; longer disease time; longer interval between the appearance of the Raynaud's phenomenon (RyP) and the first non-RyP symptom; systemic arterial hypertension (SAH); and cardiac conduction blocks. The antitopoisomerase-1 antibody (ATA-1, previously called anti-Scl-70) was more common in the presence of the diffuse form of SSc, active disease, and digital ulcers. The anti-RNA polymerase III antibody (anti-Pol III) correlated with the diffuse form of SSc, disease activity, and synovitis. CONCLUSIONS: This study emphasizes and confirms the important role of autoantibodies in assessing patients with SSc, allowing the correlation between the autoimmune profile of patients with SSc and specific manifestations of the disease.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".