Autoimmune brainstem encephalitis: Clinical associations, outcomes, and proposed diagnostic criteria
Bibliographic record
Abstract
OBJECTIVE: We describe neurologic phenotype, clinical associations, and outcomes in autoimmune brainstem encephalitis. METHODS: Medical records of neural-IgG positive autoimmune brainstem encephalitis patients diagnosed at Mayo Clinic (January 1, 2006-December 31, 2022) were reviewed. RESULTS: Ninety-eight patients (57 male) were included. Median age of symptom onset was 51 years (range, 8 months-85 years). Frequent presenting features were ≥1: diplopia (80%), ataxia (78%), dysarthria (68%), vestibulocochlear symptoms (67%), dysphagia (61%), nausea/vomiting (42%), and facial weakness (32%). Altered mental status (11%) was uncommon. Neural antibodies detected were as follows: KLHL-11 (26 patients), GAD65 (high titer, 12), ANNA-1 (anti-Hu, 8), ANNA-2 (anti-Ri, 8), Ma2 (7), IgLON-5 (6), AQP4 (6), MOG (4), glycine receptor (4), GQ1B (4), PCA-1 (anti-Yo, 4), DPPX (2), neurochondrin (2), neurofilament (2), NMDA-R (2), AGNA-1 (SOX-1, 1), ANNA-3 (DACH1, 1), amphiphysin (1), CRMP-5 (1), ITPR-1 (1), PCA-Tr (DNER, 1), and PDE10A (1). Cancer was identified in 55 patients: germ cell (23 patients; 3 extra-testicular), ductal breast adenocarcinoma (8), small cell carcinoma (6, lung 4), adenocarcinomas (6), neuroendocrine carcinoma (3), hematologic (2), squamous cell (2), and other (7). Median modified Ranking score (mRS) at last follow-up was 3 (range, 0-6). Factors associated with poor outcome included abnormal brain MRI, bulbar symptoms, and elevated CSF IgG index. Kaplan-Meier analysis revealed faster progression to wheelchair in patients who were immunotherapy refractory and with elevated CSF IgG index. Diagnostic criteria for autoimmune brainstem encephalitis (definite and probable) are proposed. INTERPRETATION: Autoimmune brainstem encephalitis is a distinct clinical subphenotype of autoimmune encephalitis. Abnormal brain MRI, bulbar symptoms, and elevated CSF-IgG index associate with poor outcome.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".