Is There a Continuum Between Acute Symptomatic Seizures Secondary to Autoimmune Encephalitis and Autoimmune-Associated Epilepsy?
Bibliographic record
Abstract
Seizure Underreporting in LGI1 and CASPR2 Antibody EncephalitisBaumgartner T, Pitsch J, Olaciregui-Dague K, Hoppe C, Racz A, Rüber T, Becker A, von Wrede R, Surges R. Epilepsia. 2022;63(9): e100-e105. doi:https://doi.org/10.1111/epi.17338. PMID: 35735209Patients with anti-leucine-rich glioma-inactivated1 protein (LGI1) or anti-contactin-associated protein 2 (CASPR2) antibody encephalitis typically present with frequent epileptic seizures. The seizures generally respond well to immunosuppressive therapy, and the long-term seizure outcome seems to be favorable. Consequentially, diagnosing acute symptomatic seizures secondary to autoimmune encephalitis instead of autoimmune epilepsy was proposed. However, published data on long-term seizure outcomes in CASPR2 and LGI1 antibody encephalitis are mostly based on patient reports, and seizure underreporting is a recognized issue. Clinical records from our tertiary epilepsy center were screened retrospectively for patients with LGI1 and CASPR2 antibody encephalitis who reported seizure freedom for at least 3 months and received video-electroencephalography (EEG) for >24 h at follow-up visits. Twenty (LGI1, n = 15; CASPR2, n = 5) of 32 patients with LGI1 (n = 24) and CASPR2 (n = 8) antibody encephalitis fulfilled these criteria. We recorded focal aware and impaired awareness seizures in four of these patients (20%) with reported seizure-free intervals ranging from 3 to 27 months. Our results question the favorable seizure outcome in patients with CASPR2 and LGI1 antibody encephalitis and suggest that the proportion of patients who have persistent seizures may be greater. Our findings underline the importance of prolonged video-EEG telemetry in this population.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".