P.030 Clinical findings, immunotherapy and neuroimaging results in Pediatric Anti-NMDA Receptor Encephalitis
Bibliographic record
Abstract
Background: Anti-NMDAR Encephalitis is an autoimmune disease of children and adults which most often presents with sub-acute psychiatric disturbance or seizures, but includes a broad group of potential clinical manifestations. Routine neuroimaging, such as cerebral MRI, is often nonspecific or normal. Methods: This study reports a series of retrospectively reviewed pediatric patients with AntiNMDAR encephalitis with emphasis on the evolution of clinical features over time, cerebral MRI, 18-FDG Positron emission tomography (PET) findings, and post illness neurocognitive features. Results: Four cases of Antibody confirmed AntiNMDAR encephalitis were included, two male and two female, of a mean of 13 years of age. Patients had a mean of three symptom categories by presentation, though many of these were subtle, progressing to 6.5 by the end of the first month. MRI, CSF and EEG were abnormal for one, three and all patients, respectively. All patients had abnormal cerebral PET scans, and all displayed some temporal lobe hypermetabolism on either initial or repeat cerebral PET Scan. Conclusions: Anti-NMDAR encephalitis is a variable disorder with an evolving clinical presentation in children. Temporal hypermetabolism on cerebral PET may be a time dependent feature of the disorder.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".