108 Comparing autoimmune encephalitis variants in a pediatric cohort from Hamilton, Ontario
Bibliographic record
Abstract
Abstract Primary Subject area Neurology Background Autoimmune Encephalitis (AE) is an emerging cause of epilepsy with numerous variants, including anti NMDA-receptor encephalitis, for which there is a detectable antibody. However, it is believed that there are many variants of AE for which an antibody has not yet been discovered. Objectives This study aimed to determine the differences in disease course of AE patients with and without detectable anti-NMDA receptor antibody. Design/Methods This retrospective analysis is part of a Canada-wide project aimed at evaluating the epidemiology and characteristics of AE. Cases with suspected AE were retrieved and screened by two independent reviewers against AE criteria. Those that met criteria were analyzed for trends and stratified into NMDA receptor antibody positive (NMDAr) and negative categories for inter-group analysis. Of 23 cases reviewed, 11 met criteria (aged 1-17 years, 27% males), of which 7 were NMDAr positive. Results The NMDAr subgroup was characterized by behavioural changes, focal seizures, and prodromal fever on presentation, whereas the receptor negative subset had a much higher variability of symptoms, without any distinctive patterns. On average, the NMDAr positive group showed an increase in white blood cell count on CSF analysis, and a slight increase in the proportion of patients presenting with supratentorial lesions on MRI. Both groups had abnormal findings on EEG. However, despite the lack of gross differences in findings, all of the NMDAr positive cases received IVIG (most with corticosteroids as well) while only 2 NMDAr negative patients received immunomodulatory therapy. At discharge 6/7 of the NMDAr patients had some form of residual movement disorder while the NMDAr negative group had more variable residual symptoms at discharge. Conclusion Our findings show that a high index of suspicion in the diagnosis of AE is required due to the indistinct distribution and variety in its presentation. Negative antibody findings should not rule out AE due to the possibility of unidentified antibodies. Future studies should explore why differences in treatment between the two groups exist, and if slight differences in presentation influence clinical decision-making.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".