35 MoCA performance as an indicator of NSAb positivity in focal epilepsy: A preliminary analysis
Bibliographic record
Abstract
Objective: Researchers are increasingly finding that the presence of neuronal surface antibodies (NSAb) may account for a larger percentage of outpatient epilepsy cases than previously thought (Elisak et al., 2018; Brenner et al., 2013). However, systematic NSAb screening is not included in standard epilepsy care (Kambadja et al., 2022). The Montreal Cognitive Assessment (MoCA; Nasreddine, 2005) is one of the most commonly used screening tools among physicians (Judge et al., 2019) across various neurological conditions, and has previously been validated in populations with autoimmune encephalitis (Hebert et al., 2018). Because patients with NSAb associated epilepsy often present with cognitive dysfunction (Greco et al., 2006), a MoCA is often administered as part of standard clinical care. The present analysis compared MoCA performance profiles in epilepsy patients with and without the presence of serum NSAbs. We explored what specific cognitive profile, as defined by the MoCA, may predict NSAb positivity. Participants and Methods: Forty-eight epilepsy patients were enrolled through an outpatient epilepsy clinic or during non-intensive or elective hospital stays. Participants were eligible if they met one of three diagnostic categories: focal epilepsy of unknown cause (n = 33), lesional focal epilepsy (n = 5), or generalized epilepsy (n = 4). All participants signed consent, underwent a comprehensive interview, which included MoCA testing, and serum NSAb testing paralleling standard clinical practice. Mann-U Whitney tests were run to compare overall MoCA and subgroup domain performance between groups. Results: Six patients (13%), all with focal epilepsy of unknown cause, had positive NSAb panels (LGI1: n = 3; GAD65: n = 2; CASPR2: n = 1). There was no significant difference in overall MoCA scores between participants with focal epilepsy of unknown cause who were antibody positive versus negative, and antibody positive versus antibody negative lesional or generalized epilepsy. However, when analyzing by MoCA subgroup, we found that antibody positive patients performed significantly worse on delayed recall than antibody negative patients with focal epilepsy of unknown cause (Mdn = 1.5 vs 3), U(Nantibodynegative=27, Nantibodypositive=6) = 69.00, p = .02. There was no significant difference in other MoCA cognitive domain tests, and delayed recall scores did not significantly differ between antibody positive patients and those with lesional focal and generalized epilepsy. Conclusions: These preliminary findings suggest that episodic memory impairment, as measured by delayed recall on the MoCA, may predict NSAb antibody positivity among patients with focal epilepsy of unknown cause. This may relate to specific predilection of the hippocampal regions in antibody-mediated epileptogenesis and pathology.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".