P.087 Successful response to rituximab in a patient with Aβ related angiitis
Bibliographic record
Abstract
Background: Aβ-related angiitis (AβRA) is a rare presentation of cerebral amyloid angiopathy, where vasculitis results from an auto-immune reaction to amyloid deposits in leptomeningeal and cortical vessel walls. Anti-CD20 monoclonal antibodies, such as rituximab, have demonstrated efficacy in systemic small vessel vasculitides, particularly in refractory cases. The efficacy of rituximab in AβRA remains unknown. Methods: Patient chart, functional measures, and laboratory findings were reviewed from the time of patient admission until 12 months after discharge. Results: A 61-year-old man presented with headache and altered mental status. Brain MRI revealed multiple cortical infarcts, leptomeningeal enhancement, and cortical microbleeds, and brain biopsy ultimately confirmed the diagnosis of AβRA. The patient developed new ischemic lesions despite corticosteroid pulse, and intravenous cyclophosphamide was halted after four weeks due to iatrogenic acute hepatitis. Rituximab was initiated and led to sustained clinical improvement with no subsequent relapses. Maintenance therapy involved gradually tapered low-dose oral steroids and rituximab at 6- and 12-months post-induction. Conclusions: This report suggests that rituximab may be effective in inducing remission and preventing relapses in biopsy-proven case of AβRA. Controlled studies are needed to better assess the efficacy and tolerability of anti-CD20 antibodies in cerebral vasculitis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".