Clinical and laboratory characteristics of Brazilian versus non-Brazilian primary antiphospholipid syndrome patients in AntiPhospholipid Syndrome Alliance for Clinical Trials and InternatiOnal Networking (APS ACTION) clinical database and repository
Bibliographic record
Abstract
BACKGROUND: Antiphospholipid syndrome (APS) is characterized by episodes of thrombosis, obstetric morbidity or both, associated with persistently positive antiphospholipid antibodies (aPL). Studying the profile of a rare disease in an admixed population is important as it can provide new insights for understanding an autoimmune disease. In this sense of miscegenation, Brazil is characterized by one of the most heterogeneous populations in the world, which is the result of five centuries of interethnic crosses of people from three continents. The objective of this study was to compare the clinical and laboratory characteristics of Brazilian vs. non-Brazilian primary antiphospholipid syndrome (PAPS) patients. METHODS: We classified PAPS patients into 2 groups: Brazilian PAPS patients (BPAPS) and PAPS patients from other countries (non-BPAPS). They were compared regarding demographic characteristics, criteria and non-criteria APS manifestations, antiphospholipid antibody (aPL) profile, and the adjusted Global Antiphospholipid Syndrome Score (aGAPSS). RESULTS: We included 415 PAPS patients (88 [21%] BPAPS and 327 [79%] non-BPAPS). Brazilian patients were significantly younger, more frequently female, sedentary, obese, non-white, and had a higher frequency of livedo (25% vs. 10%, p < 0.001), cognitive dysfunction (21% vs. 8%, p = 0.001) and seizures (16% vs. 7%, p = 0.007), and a lower frequency of thrombocytopenia (9% vs. 18%, p = 0.037). Additionally, they were more frequently positive for lupus anticoagulant (87.5% vs. 74.6%, p = 0.01), and less frequently positive to anticardiolipin (46.6% vs. 73.7%, p < 0.001) and anti-ß2-glycoprotein-I (13.6% vs. 62.7%, p < 0.001) antibodies. Triple aPL positivity was also less frequent (8% vs. 41.6%, p < 0.001) in Brazilian patients. Median aGAPSS was lower in the Brazilian group (8 vs. 10, p < 0.0001). In the multivariate analysis, BPAPS patients still presented more frequently with livedo, cognitive dysfunction and sedentary lifestyle, and less frequently with thrombocytopenia and triple positivity to aPL. They were also less often white. CONCLUSIONS: Our study suggests a specific profile of PAPS in Brazil with higher frequency of selected non-criteria manifestations and lupus anticoagulant positivity. Lupus anticoagulant (not triple positivity) was the major aPL predictor of a classification criteria event.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.001 |
| 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".