Características laboratoriais de um grupo de pacientes com artrite reumatoide inicial
Bibliographic record
Abstract
INTRODUCTION/OBJECTIVE: To characterize a population of patients with early rheumatoid arthritis (RA) according to laboratory aspects, comparing it with other similar cohorts. METHODS: Data presented are part of a prospective incident cohort study that evaluated 65 patients with early RA, followed for 36 months from the diagnosis at Early Rheumatoid Arthritis Clinic of Hospital Universitário de Brasília (HUB). We recorded demographics, clinical, and laboratory data relevant to the cohort initial assessment, including red blood cells, evidence of inflammatory activity, and presence of autoantibodies (rheumatoid factor (RF)), cyclic citrullinated peptide antibodies (anti-CCP), and antivimentin citrullinated (anti-Sa). RESULTS: There was a preponderance of female (86%) with mean age of 45.6 years. Twelve patients (18.46%) had laboratory diagnosis of anemia (hemoglobin < 12 g / dL). Erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were above the reference value for 51 (78.46%) and 46 (70.76%) patients, respectively. Thirty-two patients (49.23%) were positive for at least one of the RF isotypes, and 28 patients (43.07%) were positive for IgA RF, 19 (29.23%) for IgG, and 32 ( 49.23%) for IgM RF, respectively; 34 patients (52.30%) were positive for at least one of the techniques used in investigation of anti-CCP (CCP2, or CCP3, or CCP3.1), while 9 (13,85%) were positive for anti-Sa. CONCLUSIONS: The laboratory characteristics of patients enrolled in this Brazilian cohort are similar in many respects to those of North-American, European, and Latin-American cohorts previously published.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".