Hippocampal dysfunction after autoimmune encephalitis depending on the antibody type
Bibliographic record
Abstract
BACKGROUND: Comprehensive neurocognitive function analyses of autoimmune encephalitis (AE) patients, especially long-term ones, are rare. This study aims to measure cognitive function in patients diagnosed with AE. METHODS: This case-control study included AE patients (n = 11) with antibodies against NMDA receptor (NMDAR) (n = 4), VGKC (n = 3), GAD (3), and one antibody-negative patient. The control group contained 12 pneumococcal meningo-encephalitis patients (PC). Subgroup analyses compared AE patients with and without NMDAR antibodies. Neurocognitive tests were performed to evaluate verbal and visual memory, face recognition, attentional capacity, incidental learning capacity, and overall cognitive function (Montreal cognitive assessment, MoCA). Limbic structural involvement was assessed through magnetic resonance imaging (MRI). Statistical analyses investigated correlations between antibody status, results of neurocognitive tests, and MRI findings. RESULTS: Follow-up (AE vs. PC) was 33 (11-95) vs. 96 (26-132) months after diagnosis. Neurocognitive functions were normal in both AE and PC groups in all tests except face recognition, which was pathological in both groups. The overall/recognition/long-delay visual memory (p = 0.009/0.008/0.005) and incidental learning (p = 0.017) scores were significantly higher in NMDAR patients compared to non-NMDAR patients. Non-NMDAR patients with right-sided limbic MRI pathologies had significantly lower overall/recognition/long-delay visual memory (p = 0.006/0.044/0.024) and incidental learning (p = 0.009) scores compared to NMDAR patients. CONCLUSIONS: We observed mainly normal neurocognitive functions after autoimmune and bacterial encephalitis. However, compared to NMDAR patients, patients with non-NMDAR autoimmune encephalitis showed a significant and material-specific association between a right-sided hippocampal lesion and limitations in figural-mnestic and incidental learning capacities. Neurocognitive functions in AE patients should be further evaluated prospectively and in more detail.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".