P.002 Increased epileptiform activity during N2 and slow wave sleep in Alzheimer’s Disease
Bibliographic record
Abstract
Background: Recent evidence shows that epileptiform activity (EA) in sleep can present early in Alzheimer’s Disease (AD) with faster cognitive decline. Existing literature examining sleep, AD and seizures is mostly qualitative. We conducted a systematic review to quantify the sleep stage most associated with EA in AD and amnestic mild cognitive impairment (aMCI)Methods: We searched MEDLINE and Embase using MeSH terms: “Alzheimer’s Disease” AND “Epilepsy” OR “Seizures’’ AND “Sleep” OR “REM” (rapid eye movement sleep). We extracted data to determine the EA distribution across sleep stages. We averaged percentages across studies. If a study had AD and aMCI subgroups, we averaged percentages to represent that study. Results: 4/14 articles had quantitative sleep stage EA data from a total of 111 AD or aMCI patients. Most EA occurred in the non-REM stage (N2; 36.1±17.8%). EA next most frequently occurred in slow-wave sleep (SWS; 34.1±9.9%), N1 (15.5±6.7%), and REM (14.4±11.6%). Conclusions: N2 and slow-wave sleep were most associated with sleep EA in AD or aMCI. This suggests the importance of therapeutic interventions that may decrease N2 and slow-wave sleep and increase REM. Future studies could explore whether it is the quantity or quality of the N2 and slow-wave sleep that is associated with EA.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".