P.002 Successful Treatment of Supra-Refractory Status Epilepticus Secondary to Anti-N-Methyl-D- Aspartate Receptor Encephalitis With Electroconvulsive Therapy
Bibliographic record
Abstract
Background: Anti-N-Methyl-D-Aspartate (NMDA) receptor encephalitis is an autoimmune disease associated with antibodies against heteromers NR1 and NR2 subunits of the cell surface of the NMDA receptors, causing many psychiatric and neurological symptoms. This includes new-onset refractory status epilepticus. Methods: A 33-year-old previously healthy female developed new-onset refractory status epilepticus caused by anti- NMDA receptor encephalitis without the presence of tumours. Results: The clinical course was complicated by prolonged status epilepticus, which was refractory to many antiepileptic drugs (levetiracetam, phenytoin, carbamazepine, topiramate, lacosamide, valproic acid), ketamine, propofol, midazolam, including inhalation agents (isoflurane). Also, she received first (intravenous immunoglobulin, intravenous methylprednisolone, and plasmapheresis), second-line immunotherapy (rituximab) and prophylaxis bilateral oophorectomy without clinical or electrographic improvement. However, the patient drug-resistant status epilepticus markedly improved both clinically and electrographically following seven sessions of electroconvulsive therapy. Conclusions: Electroconvulsive therapy should be considered as adjuvant therapy for the treatment of immunotherapy resistant encephalitis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".