Ethnic Influence in Clinical and Functional Measures of Brazilian Patients with Spondyloarthritis
Bibliographic record
Abstract
OBJECTIVE: Spondyloarthritides (SpA) can present different disease spectra according to ethnic background. The Brazilian Registry of Spondyloarthritis (RBE) is a nationwide registry that comprises a large databank on clinical, functional, and treatment data on Brazilian patients with SpA. The aim of our study was to analyze the influence of ethnic background in SpA disease patterns in a large series of Brazilian patients. METHODS: A common protocol of investigation was prospectively applied to 1318 SpA patients in 29 centers distributed through the main geographical regions in Brazil. The group comprised whites (65%), African Brazilians (31.3%), and people of mixed origins (3.7%). Clinical and demographic variables and various disease index scores were compiled. Ankylosing spondylitis (AS) was the most frequent disease in the group (65.1%); others were psoriatic arthritis (18.3%), undifferentiated SpA (6.8%), enteropathic arthritis (3.7%), and reactive arthritis (3.4%). RESULTS: White patients were significantly associated with psoriasis (p = 0.002), positive HLA-B27 (p = 0.014), and use of corticosteroids (p < 0.0001). Hip involvement (p = 0.02), axial inflammatory pain (p = 0.04), and radiographic sacroiliitis (p = 0.025) were associated with African Brazilian descent. Sex distribution, family history, and presence of peripheral arthritis, uveitis, dactylitis, urethritis, and inflammatory bowel disease were similar in the 3 groups, as well as age at disease onset, time from first symptom until diagnosis, and use of anti-tumor necrosis factor-α agents (p > 0.05). Schober test and thoracic expansion were similar in the 3 groups, whereas African Brazilians had higher Maastricht Ankylosing Spondylitis Enthesitis Scores (p = 0.005) and decreased lateral lumbar flexion (p = 0.003), while whites had a higher occiput-to-wall distance (p = 0.02). African Brazilians reported a worse patient global assessment of disease (p = 0.011). Other index scores and prevalence of work incapacity were similar in the 3 groups, although African Brazilians had worse performance in the Ankylosing Spondylitis Quality of Life questionnaire (p < 0.001). CONCLUSION: Ethnic background is associated with distinct clinical aspects of SpA in Brazilian patients. African Brazilian patients with SpA have a poorer quality of life and report worse disease compared to whites.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".