1013 Novel Quantitative EEG Exposures and Risk of Incident MCI and Dementia in Older Women
Bibliographic record
Abstract
We and others have reported that quantitative EEG indices may serve as biomarkers for predicting onset of dementia or cognitive decline. We tested whether newly derived EEG indices predict onset of mild cognitive impairment (MCI), dementia, or clinically significant cognitive decline in older women. 294 older women (82.3 ± 3.2 years) without cognitive impairment completed overnight polysomnography in 2002–2004, and returned for cognitive testing 5 years later. Women were classified at follow-up as normal, MCI or dementia based on neuropsychological evaluation. Baseline EEG was analyzed for alpha-intrusion (%NREM sleep with alpha power>30μV2), normalized overall power (average of ratios [patient/group average] of power in different frequency bands) and Odds-Ratio-Product (ORP; an index of sleep depth) in different stages. Logistic regression was used to determine the association of EEG exposures and risk of incident MCI or dementia, and clinically significant cognitive decline based on 3MS scores (>= 5 points decline), adjusting for race, age, and education levels. At follow-up, 188 women were classified as cognitively normal, 60 as MCI, and 46 as dementia. 78 of 284 women experienced cognitive decline based on the 3MS. Older women with higher alpha intrusion were more likely to experience cognitive decline (OR=1.37; 95% CI 1.07–1.75 per 1 standard deviation increase), or develop MCI or dementia (OR=1.29; 1.01 - 1.64) during follow-up. Those with higher normalized overall power experienced increased risk of both cognitive decline (OR=1.34; 1.02 - 1.75) and MCI/dementia (OR=1.45; 1.11 - 1.88). Higher average ORP, both overall and during REM sleep, suggested a protective effect for development of dementia (p < .10 for both). Quantitative EEG parameters may help identify older adults at risk of future development of MCI/dementia and significant cognitive decline. Further studies are needed to confirm these findings. The Study of Osteoporotic Fractures (SOF) is supported by National Institutes of Health funding. The National Institute on Aging (NIA) provides support under the following grant numbers: R01 AG005407, R01 AR35582, R01 AR35583, R01 AR35584, R01 AG005394, R01 AG027574, R01 AG027576, and R01 AG026720.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".