Cognitive resilience and severe Alzheimer’s disease neuropathology
Bibliographic record
Abstract
Cognitive resilience in Alzheimer's disease (AD) can be defined as retention of high cognition despite presence of considerable cerebral AD lesions. We sought to identify factors associated with this phenomenon. Data were obtained from National Alzheimer's Coordinating Centre (NACC) dataset. Subjects with severe AD neuropathology, based on National Institute on Aging-Reagan (NIA-Reagan) criteria, no other primary neuropathology, and a ≤ 2-year interval between last follow-up and death were included. Mini-mental status examination score ≥ 24 was used as a proxy for normal cognition. In total, 654 cases were included; 59 (9%) were cognitively resilient. Multivariable logistic regression model showed that resilient participants were more educated, had a lower body mass index (BMI), were more likely to be lifetime/recent smoker or use an anticoagulant/antiplatelet agent, compared with cognitively impaired subjects. In addition to expected protective factors such as higher education and lower BMI, our results showed that smoking (especially recent smoking) and anticoagulant/antiplatelet consumption are associated with resilience to clinical cognitive expression of severe AD pathology. Pharmacological approaches using this information might be explored for clinical AD amelioration.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".