The meaning of non-criteria clinical manifestations in a real-life primary antiphospholipid syndrome cohort
Bibliographic record
Abstract
OBJECTIVES: We aimed to evaluate the prevalence of non-criteria clinical features in patients with primary antiphospholipid syndrome (APS), and to assess their relationship to thrombosis and damage. METHODS: We retrospectively included 177 primary APS patients, and/or patients who only achieved the serological Sydney criteria but had thrombocytopenia and/or haemolytic anaemia. We registered demographics, serology, treatment, thrombotic/obstetric manifestations and non-criteria clinical manifestations (cutaneous, haematologic, renal, heart valve disease, and neurological). We scored the DIAPS and a modified SLICC index. We used logistic regression and reported OR with 95% CI. RESULTS: 78% were women with a median follow-up of 6.7 years. Thrombosis was found in 74% of patients, 29.3% had obstetric features, and 64% had non-criteria clinical manifestations. The frequency of the non-criteria clinical manifestation was: haematologic 40.1%, cutaneous 20.9%, neurologic 18%, cardiac 5% and renal 4.5%. Non-criteria features were associated with LA (OR 2.3, 95% 1.03-5.1) and prednisone use (OR 8.2, 95% CI 1.7-39.3). A DIAPS score ≥1 was associated with thrombosis (OR 53.1, 95% CI 17.8-15.2), prednisone use (OR 0.27, CI 95% 0.09-0.83) and neurological involvement (OR 6.4, 95% CI 1.05-39.8); whereas a modified SLICC ≥ 1 with thrombosis (OR 10.2; IC 95% 4.43-26.1), neurological involvement (OR 6.4, 95%CI 1.05-39.8), obstetric features (OR 0.32 CI 95% 0.12-0,81) and cutaneous features (OR 5.3, CI 95% 1.4-19), especially livedo reticularis (OR 5.45; IC 95% 1.49-19.8). CONCLUSIONS: Non-criteria clinical manifestations are common and associated with LA. Among them, neurologic involvement and the presence of livedo were associated with damage accrual.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| 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".