P.003 Autoimmune Encephalitis and related disorders are not rare in British Columbia
Bibliographic record
Abstract
Background: Autoimmune encephalitis (AE) is a recently described entity that presents with seizures, neuropsychiatric manifestations, and movement disorders. This observational chart review of AE aims to assess the burden of AE and related disorders at two Vancouver academic medical centers. Methods: All patients with Mitogen Laboratory AE antibody testing in 2018 were identified. Electronic hospital records were used to determine patient characteristics. Results: 1266 unique tests were ordered on 315 inpatients and outpatients. Of 37/315 (11.7%) seropositive patients, 26/37 (70.2%) patients had clinical data. Seropositive results included autoantibodies to NMDA (n=3), LG1 (n=2), CASPR2 (n=1) and paraneoplastic autoantibodies included GAD65 (n=2), PNMA2 (n=5), recoverin (n=3). There were four AE cases in 14 seronegative patients based on discharge diagnosis. 15/30 of patients had seizures and three developed status epilepticus. 15 had neuropsychiatric manifestations. 14 had a movement disorder. For inpatients, average length of stay was 24.3 days and there were 5 intensive care unit (ICU) admissions. Immunotherapies used included corticosteroids, PLEX, rituximab, IVIg, and cyclophosphamide. Conclusions: In two hospitals serving approximately two million people in 2018, there were 30 cases of AE in 2018. AE presents with a broad range of neurologic symptoms and seronegative testing does not preclude AE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 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".