P.050 Autoimmune encephalitis associated with GAD65 antibodies: brief review of the relevant literature
Bibliographic record
Abstract
Background: Recently, many cases of autoimmune encephalitis with positive GAD65 (Glutamic acid decarboxylase) antibodies have been described in the literature. However, it remains an understudied topic. Methods: We conducted a search on reported cases of anti-GAD65 encephalitis. Specific variables were identified as general characteristics, clinical manifestations, MRI and EEG findings, concomitant systemic autoimmune disorders and cancer, and outcome and autoantibodies findings. Results: We identified a total of 58 cases, from one to 70 years old. It most frequently presented with seizures (97%) and memory impairment (59%). It commonly occurred in association with systemic autoimmune disease, particularly diabetes (28%). Brain MRI was usually abnormal (78%); involvement of temporal lobes was more frequent than multifocal abnormalities (59% vs 16%). GAD65 antibodies were reported positive in CSF and/or serum (31% in serum only). Other antibodies such as GABABR, GABAAR and VGKC were concurrently reported positive in some cases (19%). However, we found that the vast majority of cases were not tested for all those cell-surface antibodies. Overall, no distinctive pattern of clinical and paraclinical findings was found. Persistent impairments were common. Optimal treatment remained undefined. Conclusions: Prospective studies recruiting patients with autoimmune encephalitis are needed to better elucidate the contributions of GAD65 autoantibodies, and to evaluate treatment and outcomes 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".