P.034 Temporal lobe epilepsy associated with autoimmune conditions: a review
Bibliographic record
Abstract
Background: Epilepsy mediated by immune cells must be identified early since immunotherapy has been associated with better clinical outcomes. This provides an overview of autoimmune TLE, emphasizing recent developments in its pathophysiology, imaging, and therapeutic interventions. Methods: Web-based research using advanced features of databases. Results: Epilepsy caused by immune dysfunction leads to inflammation of the brain. Inflammation play a role in the development of seizures. Proinflammatory molecules found to be overexpressed in neurons and glia of individuals with DRE, provoke a proinflammatory cytokines in the plasma and CSF. Autoimmune epilepsy is characterized by focal seizures refractory to ASMs accompanied by other neurological manifestations, as described by clinical scoring systems.Scoring systems are available to identify patients who are likely to be positive. The MRI findings include signal hyperintensities in the affected brain regions. EEG performed to exclude nonconvulsive seizures. Seizures resulting from autoimmune encephalitis are caused by antibodies to surface antigens and intracellular antigenes. Conclusions: Pathogenesis proposed to involve antibody-mediated ictogenesis. Immunotherapy is effective in autoimmune encephalitis with a positive prognosis if detected early. Limbic encephalitis has been shown to have a detrimental effect on cognition, mood, and behavior. Neuropsychology is an important outcome criterion for tracking disease progression and treatment success.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".