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Perfil de autoanticorpos e correlação clínica em um grupo de pacientes com esclerose sistêmica na região sul do Brasil

2011· article· pt· W2051413218 on OpenAlexaff
Carolina de Souza Müller, Eduardo dos Santos Paiva, Valderílio Feijó Azevedo, S. Radominski, José Hermênio Cavalcante Lima Filho

Bibliographic record

VenueRevista Brasileira de Reumatologia · 2011
Typearticle
Languagept
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAutoantibodyOutpatient clinicInternal medicinePopulationDiseaseDermatologyAntibodyImmunology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.048
GPT teacher head0.275
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2011
Admission routes1
Has abstractyes

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