Cognitive and spatial patterns of amyloid-β burden in Alzheimer's disease with epilepsy
Bibliographic record
Abstract
BackgroundThe risk of unprovoked seizures in patients with Alzheimer's disease (AD) is three-fold higher than the general population. However, no studies to date have reported on amyloid-β (Aβ) deposition in patients with Alzheimer's disease with epilepsy (ADEP).ObjectiveThe aim of this study was to collect clinical and positron emission tomography (PET)/magnetic resonance imaging (MRI) data from ADEP patients to compare and present the clinical characteristics and Aβ deposition patterns in this patient population.MethodsFifteen patients with ADEP, thirty-five patients with AD, twenty-three with late-onset epilepsy (LOEP), and twelve healthy controls were recruited. PET/MRI detected intracranial Aβ deposition, and differences in the brain regions distribution were compared between groups at the region of interest and voxel levels. Demographic data and medical history were further collected, while clinical and cognitive assessments were performed.ResultsIn ADEP patients, the first seizure occurred in the early stages of AD, with focal-onset motor seizures accompanied by impaired consciousness being the predominant seizure type. Diagnosis and initiation of antiseizure medication (ASMs) were significantly delayed compared to LOEP patients. Additionally, the ADEP group showed less Aβ deposition in the middle cingulate gyrus than the AD group and had higher Mini-Mental State Exam and Montreal Cognitive Assessment scores.ConclusionsThis study reveals the clinical features and brain imaging differences between AD patients with and without EP, preliminarily confirming that the spatial deposition pattern of Aβ may be related to epilepsy and ASMs.
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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 | 0.001 |
| 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".