Autoimmune‐associated seizure disorders
Bibliographic record
Abstract
With the discovery of an expanding number of neural autoantibodies, autoimmune etiologies of seizures have been increasingly recognized. Clinical phenotypes have been identified in association with specific underlying antibodies, allowing an earlier diagnosis. These phenotypes include faciobrachial dystonic seizures with LGI1 encephalitis, neuropsychiatric presentations associated with movement disorders and seizures in NMDA-receptor encephalitis, and chronic temporal lobe epilepsy in GAD65 neurologic autoimmunity. Prompt recognition of these disorders is important, as some of them are highly responsive to immunotherapy. The response to immunotherapy is highest in patients with encephalitis secondary to antibodies targeting cell surface synaptic antigens. However, the response is less effective in conditions involving antibodies binding intracellular antigens or in Rasmussen syndrome, which are predominantly mediated by cytotoxic T-cell processes that are associated with irreversible cellular destruction. Autoimmune encephalitides also may have a paraneoplastic etiology, further emphasizing the importance of recognizing these disorders. Finally, autoimmune processes and responses to novel immunotherapies have been reported in new-onset refractory status epilepticus (NORSE) and febrile infection-related epilepsy syndrome (FIRES), warranting their inclusion in any current review of autoimmune-associated seizure disorders.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".