Refractory Status Epilepticus in a Patient With Aducanumab-Induced Amyloid-Related Imaging Abnormalities
Bibliographic record
Abstract
OBJECTIVE: To report a case of fatal super-refractory status epilepticus associated with amyloid-related imaging abnormalities (ARIA). METHODS: We describe the history, neuroimaging, EEG, and brain pathology findings of a 75-year-old patient with mild cognitive impairment due to Alzheimer disease (homozygous ε4 apolipoprotein status) and a remote history of 3 asymptomatic ARIA episodes, who developed super-refractory status epilepticus related to severe ARIA. RESULTS: The patient was participating in an extended open-label trial of aducanumab when she was admitted to hospital for focal seizures and ARIA in 2 noncontiguous regions of the left frontal and occipital lobes. Despite aggressive treatment with high-dose corticosteroids, sedation, and antiseizure medications, she died from refractory focal status epilepticus. In retrospect, routine surveillance brain magnetic resonance imaging performed 11 weeks before hospitalization had signs of ARIA, which had not been identified. DISCUSSION: Clinicians should be aware that anti-amyloid therapies may cause rare serious adverse events. A high degree of vigilance is required in the interpretation of surveillance imaging for ARIA. Longitudinal studies are justified to further characterize the safety profile of anti-amyloid antibody therapies and identify participants at high risk of serious adverse events.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".