Lewy Bodies, Vascular Risk Factors, and Subcortical Arteriosclerotic Leukoencephalopathy, but not Alzheimer Pathology, are Associated with Development of Psychosis in Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: The neuropathological correlates of psychosis in Alzheimer's disease (AD) is unclear, with some studies reporting a correlation between psychosis and increased AD pathology while others have found no association. OBJECTIVE: To determine the demographic, clinical, and neuropathological features associated with psychotic symptoms in clinically attributed and neuropathologically proven AD. METHOD: We separately reviewed two overlapping groups of clinically diagnosed (cAD) AD patients with neuropathology data and neuropathologically definite (npAD) cases (regardless of clinical diagnosis) from the NACC database, and explored the relationships between psychosis and clinical variables, neuropathologic correlates, and vascular risk factors. Delusions and hallucinations, defined according to the NPI-Q, were analyzed separately. RESULTS: 1,073 subjects in the database fulfilled our criteria (890 cAD and 728 npAD patients). 34% of cAD and 37% of npAD had psychotic symptoms during their illness. Hallucinations were associated with greater cognitive and functional impairments on the MMSE and CDR, while delusional patients showed less impairment on CDR, consistent across cAD and npAD groups. Burden of AD pathology appears to relate to presence of psychotic symptoms in the clinical AD group, but this result is not confirmed in the neuropathologically confirmed group suggesting the findings in the clinical group were due to misdiagnosis of AD. Lewy body pathology, subcortical arteriosclerotic leukoencephalopathy, and vascular risk factors, including a history of hypertension and diabetes, were associated with the development of psychosis. METHOD: Vascular and Lewy body pathologies and vascular risk factors are important modifiers of the risk of psychosis in AD.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".