Co‐pathology in Alzheimer's disease and Lewy body disease and its association with neuropsychiatric symptoms
Bibliographic record
Abstract
BACKGROUND: Mixed neuropathology is common in dementia, but the clinical implications for neuropsychiatric symptoms (NPSs) are not well characterized. METHODS: In a population-based post mortem study, cases with Alzheimer's disease neuropathological change (ADNC) and Lewy body disease (LBD) were identified with any comorbid neuropathology (limbic-predominant age-related transactive response DNA-binding protein 43 encephalopathy neuropathological change (LATE-NC), cerebrovascular disease, LBD, and ADNC, respectively). Post mortem interviews collected information regarding NPSs and cognition to explore associations between each co-pathology and NPSs across the whole cohort, as well as in participants without dementia. RESULTS: Co-existing neuropathology was frequent, even among individuals without clinical dementia. In cases with ADNC, comorbid neocortical LBD pathology was associated with hallucinations, regardless of cognitive status. However, ADNC co-pathology in LBD was linked to a greater NPS burden in the full cohort but not in individuals without dementia. DISCUSSION: Lewy bodies are associated with hallucinations independent of cognitive impairment, whereas ADNC co-pathology may contribute to NPS only when widespread and associated with cognitive dysfunction. HIGHLIGHTS: Neuropathological heterogeneity is high even in clinical stages without dementia. Neocortical but not limbic or brainstem LBD co-pathology is associated with hallucinations. LBs are associated with hallucinations independent of cognitive status. ADNC co-pathology is not associated with NPSs in LBD without dementia. LATE co-pathology is associated with increased risk of dementia but not NPS. Vascular co-pathology is associated with increased risk of delusions in ADNC.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".