Antiphospholipid syndrome–mediated acute cerebrovascular diseases and long-term outcomes
Bibliographic record
Abstract
OBJECTIVES: The antiphospholipid syndrome (APS) is an autoimmune disease associated with thrombotic and non-thrombotic neurologic manifestations. APS is classified as primary (PAPS) or secondary (SAPS) when it co-exists with another autoimmune disease. We aim to describe the spectrum of acute cerebrovascular disease among patients with APS, their differences between stroke subtypes, and long-term functional outcomes. METHODS: Retrospective cohort study including adult (≥18 years) patients with APS followed in the stroke clinic of a tertiary-care reference center for autoimmune diseases in Mexico from 2009 to 2019. RESULTS: We studied 120 cases; 99 (82.5%) women; median age 43 years (interquartile range 35-52); 63.3% with SAPS. Demographics, comorbidities, and antiphospholipid antibodies (aPL) positivity were similar between APS type and stroke subtypes. Amongst index events, we observed 84 (70%) acute ischemic strokes (AIS), 19 (15.8%) cerebral venous thromboses (CVT), 11 (9.2%) intracerebral hemorrhages (ICH), and six (5%) subarachnoid hemorrhages (SAH). Sixty-seven (55.8%) were known patients with APS; the median time from APS diagnosis to index stroke was 46 months (interquartile range 12-96); 64.7% of intracranial hemorrhages (ICH or SAH) occurred ≥4 years after APS was diagnosed (23.5% anticoagulation-related); 63.2% of CVT cases developed before APS was diagnosed or simultaneously. Recurrences occurred in 26 (22.8%) patients, AIS, in 18 (69.2%); intracranial hemorrhage, in eight (30.8%). Long-term functional outcomes were good (modified Rankin Scale ≤2) in 63.2% of cases, during follow-up, the all-cause mortality rate was 19.2%. CONCLUSION: We found no differences between stroke subtypes and APS types. aPL profiles were not associated with any of the acute cerebrovascular diseases described in this cohort. CVT may be an initial thrombotic manifestation of APS with low mortality and good long-term functional outcome.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".